310 results on '"Albuquerque, L. G."'
Search Results
2. Genetic parameters and investigation of genotype × environment interactions in Nellore × Hereford crossbred for resistance to cattle ticks in different regions of Brazil
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Ayres, D. R., Pereira, R. J., Boligon, A. A., Baldi, F., Roso, V. M., and Albuquerque, L. G.
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- 2015
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3. Genetic evaluation of lactation persistency in the Gyr breed by using a two-trait random regression model
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González-Herrera, L. G., primary, Pereira, R. J., additional, El Faro, L., additional, and Albuquerque, L. G., additional
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- 2022
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4. Genome‐wide interaction study reveals epistatic interactions for beef lipid‐related traits in Nellore cattle
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Amorim, S. T., primary, Stafuzza, N. B., additional, Kluska, S., additional, Peripolli, E., additional, Pereira, A. S. C., additional, Muller da Silveira, L. F., additional, Albuquerque, L. G., additional, and Baldi, F., additional
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- 2021
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5. Genetic associations between temperament and performance traits in Nellore beef cattle
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SantʼAnna, A. C., Baldi, F., Valente, T. S., Albuquerque, L. G., Menezes, L. M., Boligon, A. A., and Paranhos da Costa, M. J.R.
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- 2015
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6. Analysis of genetic correlations of hip height with selection indices and mature weight in Nelore cattle
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Boligon, A. A., Carvalheiro, R., Ayres, D. R., and Albuquerque, L. G.
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- 2013
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7. Linear and Poisson models for genetic evaluation of tick resistance in cross-bred Hereford x Nellore cattle
- Author
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Ayres, D. R., Pereira, R. J., Boligon, A. A., Silva, F. F., Schenkel, F. S., Roso, V. M., and Albuquerque, L. G.
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- 2013
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8. Genome‐enabled prediction of reproductive traits in Nellore cattle using parametric models and machine learning methods
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Alves, A. A. C., primary, Espigolan, R., additional, Bresolin, T., additional, Costa, R. M., additional, Fernandes Júnior, G. A., additional, Ventura, R. V., additional, Carvalheiro, R., additional, and Albuquerque, L. G., additional
- Published
- 2020
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9. Selection strategies for dairy buffaloes: economic and genetic consequences
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Seno, L. O., Fernández, J., Cardoso, V. L., García-Cortes, L. A., Toro, M., Santos, D. O., Albuquerque, L. G., de Camargo, G. M.F., and Tonhati, H.
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- 2012
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10. Genetic associations of visual scores with subsequent rebreeding and days to first calving in Nellore cattle
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Boligon, A. A., Ayres, D. R., Pereira, R. J., Morotti, N. P., and Albuquerque, L. G.
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- 2012
- Full Text
- View/download PDF
11. Genome‐wide interaction study reveals epistatic interactions for beef lipid‐related traits in Nellore cattle.
- Author
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Amorim, S. T., Stafuzza, N. B., Kluska, S., Peripolli, E., Pereira, A. S. C., Muller da Silveira, L. F., de Albuquerque, L. G., and Baldi, F.
- Subjects
LIPOPROTEIN receptors ,PHYSIOLOGY ,CATTLE ,MEAT quality ,GENETIC variation ,LIPIDS ,LOW density lipoprotein receptors - Abstract
Summary: Gene–gene interactions cause hidden genetic variation in natural populations and could be responsible for the lack of replication that is typically observed in complex traits studies. This study aimed to identify gene–gene interactions using the empirical Hilbert–Schmidt Independence Criterion method to test for epistasis in beef fatty acid profile traits of Nellore cattle. The dataset contained records from 963 bulls, genotyped using a 777 962k SNP chip. Meat samples of Longissimus muscle, were taken to measure fatty acid composition, which was quantified by gas chromatography. We chose to work with the sums of saturated (SFA), monounsaturated (MUFA), polyunsaturated (PUFA), omega‐3 (OM3), omega‐6 (OM6), SFA:PUFA and OM3:OM6 fatty acid ratios. The SNPs in the interactions where P<10‐8 were mapped individually and used to search for candidate genes. Totals of 602, 3, 13, 23, 13, 215 and 169 candidate genes for SFAs, MUFAs, PUFAs, OM3s, OM6s and SFA:PUFA and OM3:OM6 ratios were identified respectively. The candidate genes found were associated with cholesterol, lipid regulation, low‐density lipoprotein receptors, feed efficiency and inflammatory response. Enrichment analysis revealed 57 significant GO and 18 KEGG terms (P < 0.05), most of them related to meat quality and complementary terms. Our results showed substantial genetic interactions associated with lipid profile, meat quality, carcass and feed efficiency traits for the first time in Nellore cattle. The knowledge of these SNP–SNP interactions could improve understanding of the genetic and physiological mechanisms that contribute to lipid‐related traits and improve human health by the selection of healthier meat products. [ABSTRACT FROM AUTHOR]
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- 2022
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12. Genomic reaction norm models exploiting genotype × environment interaction on sexual precocity indicator traits in Nellore cattle
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Mota, L. F. M., primary, Fernandes, G. A., additional, Herrera, A. C., additional, Scalez, D. C. B., additional, Espigolan, R., additional, Magalhães, A. F. B., additional, Carvalheiro, R., additional, Baldi, F., additional, and Albuquerque, L. G., additional
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- 2020
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13. Large expert-curated database for benchmarking document similarity detection in biomedical literature search
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Brown, P, Zhou, Y, Tan, A, El-Esawi, M, Liehr, T, Blanck, O, Gladue, D, Almeida, G, Cernava, T, Sorzano, C, Yeung, A, Engel, M, Chandrasekaran, A, Muth, T, Staege, M, Daulatabad, S, Widera, D, Zhang, J, Meule, A, Honjo, K, Pourret, O, Yin, C, Zhang, Z, Cascella, M, Flegel, W, Goodyear, C, van Raaij, M, Bukowy-Bieryllo, Z, Campana, L, Kurniawan, N, Lalaouna, D, Huttner, F, Ammerman, B, Ehret, F, Cobine, P, Tan, E, Han, H, Xia, W, Mccrum, C, Dings, R, Marinello, F, Nilsson, H, Nixon, B, Voskarides, K, Yang, L, Costa, V, Bengtsson-Palme, J, Bradshaw, W, Grimm, D, Kumar, N, Martis, E, Prieto, D, Sabnis, S, Amer, S, Liew, A, Perco, P, Rahimi, F, Riva, G, Zhang, C, Devkota, H, Ogami, K, Basharat, Z, Fierz, W, Siebers, R, Tan, K, Boehme, K, Brenneisen, P, Brown, J, Dalrymple, B, Harvey, D, Ng, G, Werten, S, Bleackley, M, Dai, Z, Dhariwal, R, Gelfer, Y, Hartmann, M, Miotla, P, Tamaian, R, Govender, P, Gurney-Champion, O, Kauppila, J, Zhang, X, Echeverria, N, Subhash, S, Sallmon, H, Tofani, M, Bae, T, Bosch, O, Cuiv, P, Danchin, A, Diouf, B, Eerola, T, Evangelou, E, Filipp, F, Klump, H, Kurgan, L, Smith, S, Terrier, O, Tuttle, N, Ascher, D, Janga, S, Schulte, L, Becker, D, Browngardt, C, Bush, S, Gaullier, G, Ide, K, Meseko, C, Werner, G, Zaucha, J, Al-Farha, A, Greenwald, N, Popoola, S, Rahman, S, Xu, J, Yang, S, Hiroi, N, Alper, O, Baker, C, Bitzer, M, Chacko, G, Debrabant, B, Dixon, R, Forano, E, Gilliham, M, Kelly, S, Klempnauer, K, Lidbury, B, Lin, M, Lynch, I, Ma, W, Maibach, E, Mather, D, Nandakumar, K, Ohgami, R, Parchi, P, Tressoldi, P, Xue, Y, Armitage, C, Barraud, P, Chatzitheochari, S, Coelho, L, Diao, J, Doxey, A, Gobet, A, Hu, P, Kaiser, S, Mitchell, K, Salama, M, Shabalin, I, Song, H, Stevanovic, D, Yadollahpour, A, Zeng, E, Zinke, K, Alimba, C, Beyene, T, Cao, Z, Chan, S, Gatchell, M, Kleppe, A, Piotrowski, M, Torga, G, Woldesemayat, A, Cosacak, M, Haston, S, Ross, S, Williams, R, Wong, A, Abramowitz, M, Effiong, A, Lee, S, Abid, M, Agarabi, C, Alaux, C, Albrecht, D, Atkins, G, Beck, C, Bonvin, A, Bourke, E, Brand, T, Braun, R, Bull, J, Cardoso, P, Carter, D, Delahay, R, Ducommun, B, Duijf, P, Epp, T, Eskelinen, E, Fallah, M, Farber, D, Fernandez-Triana, J, Feyerabend, F, Florio, T, Friebe, M, Furuta, S, Gabrielsen, M, Gruber, J, Grybos, M, Han, Q, Heinrich, M, Helantera, H, Huber, M, Jeltsch, A, Jiang, F, Josse, C, Jurman, G, Kamiya, H, de Keersmaecker, K, Kristiansson, E, de Leeuw, F, Li, J, Liang, S, Lopez-Escamez, J, Lopez-Ruiz, F, Marchbank, K, Marschalek, R, Martin, C, Miele, A, Montagutelli, X, Morcillo, E, Nicoletti, R, Niehof, M, O'Toole, R, Ohtomo, T, Oster, H, Palma, J, Paterson, R, Peifer, M, Portilla, M, Portillo, M, Pritchard, A, Pusch, S, Raghava, G, Roberts, N, Ross, K, Schuele, B, Sergeant, K, Shen, J, Stella, A, Sukocheva, O, Uversky, V, Vanneste, S, Villet, M, Viveiros, M, Vorholt, J, Weinstock, C, Yamato, M, Zabetakis, I, Zhao, X, Ziegler, A, Aizat, W, Atlas, L, Bridges, K, Chakraborty, S, Deschodt, M, Domingues, H, Esfahlani, S, Falk, S, Guisado, J, Kane, N, Kueberuwa, G, Lau, C, Liang, D, Liu, E, Luu, A, Ma, C, Ma, L, Moyer, R, Norris, A, Panthee, S, Parsons, J, Peng, Y, Pinto, I, Reschke, C, Sillanpaa, E, Stewart, C, Uhle, F, Yang, H, Zhou, K, Zhu, S, Ashry, M, Bergsland, N, Berthold, M, Chen, C, Colella, V, Cuypers, M, Eskew, E, Fan, X, Gajda, M, Gonzalezlez-Prendes, R, Goodin, A, Graham, E, Groen, E, Gutierrez-Sacristan, A, Habes, M, Heffler, E, Higginbottom, D, Janzen, T, Jayaraman, J, Jibb, L, Jongen, S, Kinyanjui, T, Koleva-Kolarova, R, Li, Z, Liu, Y, Lund, B, Lussier, A, Mier, P, Moore, M, Nagler, K, Orme, M, Pearson, J, Prajapati, A, Saito, Y, Troder, S, Uchendu, F, Verloh, N, Voutchkova, D, Abu-Zaid, A, Bakkach, J, Baumert, P, Dono, M, Hanson, J, Herbelet, S, Hobbs, E, Kulkarni, A, Liu, S, Loft, N, Reddan, T, Senghore, T, Vindin, H, Xu, H, Bannon, R, Chen, B, Cheung, J, Cooper, J, Esnakula, A, Feghali, K, Ghelardi, E, Gnasso, A, Horbar, J, Lai, H, Ma, R, Pan, Z, Peres, M, Pranata, R, Seow, E, Sydes, M, Testoni, I, Westermair, A, Yang, Y, Afnan, M, Albiol, J, Albuquerque, L, Amir, S, Amiya, E, Amorim, R, An, Q, Andersen, S, Aplin, J, Argyropoulos, C, Asmann, Y, Assaeed, A, Atanasov, A, Atchison, D, Avery, S, Avillach, P, Baade, P, Backman, L, Badie, C, Baldi, A, Ball, E, Bardot, O, Barnett, A, Basner, M, Batra, J, Bazanova, O, Beale, A, Beddoe, T, Bell, M, Berezikov, E, Berners-Price, S, Bernhardt, P, Berry, E, Bessa, T, Billington, C, Birch, J, Blakely, R, Blaskovich, M, Blum, R, Boelaert, M, Bogdanos, D, Bosch, C, Bourgoin, T, Bouvard, D, Boykin, L, Bradley, G, Braun, D, Brownlie, J, Bruhl, A, Burt, A, Butler, L, Byrareddy, S, Byrne, H, Cabantous, S, Calatayud, S, Candal, E, Carlson, K, Casillas, S, Castelvetro, V, Caswell, P, Cavalli, G, Cerovsky, V, Chagoyen, M, Chen, D, Chen, H, Chen, J, Chen, Y, Cheng, C, Cheng, J, Chinapaw, M, Chinopoulos, C, Cho, W, Chong, L, Chowdhury, D, Chwalibog, A, Ciresi, A, Cockcroft, S, Conesa, A, Cook, P, Cooper, D, Coqueret, O, Corea, E, Costa, A, Costa, E, Coupland, C, Crawford, S, Cruz, A, Cui, H, Cui, Q, Culver, D, D'Angiulli, A, Dahms, T, Daigle, F, Dalgleish, R, Danielsen, H, Darras, S, Davidson, S, Day, D, Degirmenci, V, Demaison, L, Devriendt, K, Ding, J, Dogan, Y, Dong, X, Donner, C, Dressick, W, Drevon, C, Duan, H, Ducho, C, Dumaz, N, Dwarakanath, B, Ebell, M, Eisenhardt, S, Elkum, N, Engel, N, Erickson, T, Fairhead, M, Faville, M, Fejzo, M, Festa, F, Feteira, A, Flood-Page, P, Forsayeth, J, Fox, S, Franks, S, Frentiu, F, Frilander, M, Fu, X, Fujita, S, Galea, I, Galluzzi, L, Gani, F, Ganpule, A, Garcia-Alix, A, Gedye, K, Giordano, M, Giunta, C, Gleeson, P, Goarant, C, Gong, H, Gora, D, Gough, M, Goyal, R, Graham, K, Grande-Perez, A, Graves, P, Greidanus, H, Grice, D, Grunau, C, Gumulya, Y, Guo, Y, Gurevich, V, Gusev, O, Hacker, E, Hage, S, Hagen, G, Hahn, S, Haller, D, Hammerschmidt, S, Han, J, Han, R, Handfield, M, Hapuarachchi, H, Harder, T, Hardingham, J, Heck, M, Heers, M, Hew, K, Higuchi, Y, Hilaire, C, Hilton, R, Hodzic, E, Hone, A, Hongoh, Y, Hu, G, Huber, H, Hueso, L, Huirne, J, Hurt, L, Idborg, H, Ikeo, K, Ingley, E, Jakeman, P, Jensen, A, Jia, H, Jia, S, Jiang, J, Jiang, X, Jin, Y, Jo, D, Johnson, A, Johnston, M, Jonscher, K, Jorens, P, Jorgensen, J, Joubert, J, Jung, S, Junior, A, Kahan, T, Kamboj, S, Kang, Y, Karamanos, Y, Karp, N, Kelly, R, Kenna, R, Kennedy, J, Kersten, B, Khalaf, R, Khalid, J, Khatlani, T, Khider, T, Kijanka, G, King, S, Kluz, T, Knox, P, Kobayashi, T, Koch, K, Kohonen-Corish, M, Kong, X, Konkle-Parker, D, Korpela, K, Kostrikis, L, Kraiczy, P, Kratz, H, Krause, G, Krebsbach, P, Kristensen, S, Kumari, P, Kunimatsu, A, Kurdak, H, Kwon, Y, Lachat, C, Lagisz, M, Laky, B, Lammerding, J, Lange, M, Larrosa, M, Laslett, A, Laverman, G, Leclair, E, Lee, K, Lee, M, Li, G, Lieb, K, Lim, Y, Lindsey, M, Line, P, Liu, D, Liu, F, Liu, H, Lloyd, V, Lo, T, Locci, E, Loidl, J, Lorenzen, J, Lorkowski, S, Lovell, N, Lu, H, Lu, W, Lu, Z, Luengo, G, Lundh, L, Lysy, P, Mabb, A, Mack, H, Mackey, D, Mahdavi, S, Maher, P, Maher, T, Maity, S, Malgrange, B, Mamoulakis, C, Mangoni, A, Manke, T, Manstead, A, Mantalaris, A, Marsal, J, Marschall, H, Martin, F, Martinez-Raga, J, Martinez-Salas, E, Mathieu, D, Matsui, Y, Maza, E, Mccutcheon, J, Mckay, G, Mcmillan, B, Mcmillan, N, Meads, C, Medina, L, Merrick, B, Metzger, D, Meunier, F, Michaelis, M, Micheau, O, Mihara, H, Mintz, E, Mizukami, T, Moalic, Y, Mohapatra, D, Monteiro, A, Montes, M, Moran, J, Morozov, S, Mort, M, Murai, N, Murphy, D, Murphy, S, Murray, S, Naganawa, S, Nammi, S, Nasios, G, Natoli, R, Nguyen, F, Nicol, C, van Nieuwerburgh, F, Nilsen, E, Nobile, C, O'Mahony, M, Ohlsson, S, Olatunbosun, O, Olofsson, P, Ortiz, A, Ostrikov, K, Otto, S, Outeiro, T, Ouyang, S, Paganoni, S, Page, A, Palm, C, Paradies, Y, Parsons, M, Parsons, N, Pascal, P, Paul, E, Peckham, M, Pedemonte, N, Pellizzon, M, Petrelli, M, Pichugin, A, Pinto, C, Plevris, J, Pollesello, P, Polz, M, Ponti, G, Porcelli, P, Prince, M, Quinn, G, Quinn, T, Ramula, S, Rappsilber, J, Rehfeldt, F, Reiling, J, Remacle, C, Rezaei, M, Riddick, E, Ritter, U, Roach, N, Roberts, D, Robles, G, Rodrigues, T, Rodriguez, C, Roislien, J, Roobol, M, Rowe, A, Ruepp, A, van Ruitenbeek, J, Rust, P, Saad, S, Sack, G, Santos, M, Saudemont, A, Sava, G, Schrading, S, Schramm, A, Schreiber, M, Schuler, S, Schymkowitz, J, Sczyrba, A, Seib, K, Shi, H, Shimada, T, Shin, J, Shortt, C, Silveyra, P, Skinner, D, Small, I, Smeets, P, So, P, Solano, F, Sonenshine, D, Song, J, Southall, T, Speakman, J, Srinivasan, M, Stabile, L, Stasiak, A, Steadman, K, Stein, N, Stephens, A, Stewart, D, Stine, K, Storlazzi, C, Stoynova, N, Strzalka, W, Suarez, O, Sultana, T, Sumant, A, Summers, M, Sun, G, Tacon, P, Tanaka, K, Tang, H, Tanino, Y, Targett-Adams, P, Tayebi, M, Tayyem, R, Tebbe, C, Telfer, E, Tempel, W, Teodorczyk-Injeyan, J, Thijs, G, Thorne, S, Thrift, A, Tiffon, C, Tinnefeld, P, Tjahjono, D, Tolle, F, Toth, E, Del Tredici, A, Tsapas, A, Tsirigotis, K, Turak, A, Tzotzos, G, Udo, E, Utsumi, T, Vaidyanathan, S, Vaillant, M, Valsesia, A, Vandenbroucke, R, Veiga, F, Vendrell, M, Vesk, P, Vickers, P, Victor, V, Villemur, R, Vohl, M, Voolstra, C, Vuillemin, A, Wakelin, S, Waldron, L, Walsh, L, Wang, A, Wang, F, Wang, Y, Watanabe, Y, Weigert, A, Wen, J, Wham, C, White, E, Wiener, J, Wilharm, G, Wilkinson, S, Willmann, R, Wilson, C, Wirth, B, Wojan, T, Wolff, M, Wong, B, Wu, T, Wuerbel, H, Xiao, X, Xu, D, Xue, B, Yalcin, S, Yan, H, Yang, E, Yang, W, Ye, Y, Ye, Z, Yli-Kauhaluoma, J, Yoneyama, H, Yu, Y, Yuan, G, Yuh, C, Zaccolo, M, Zeng, C, Zevnik, B, Zhang, L, Zhang, Y, Zhao, Y, Zhou, M, Zuberbier, T, Aanei, C, Ahmad, R, Al-Lawama, M, Alanio, A, Allardyce, J, Alonso-Caneiro, D, Atack, J, Baier, D, Bansal, A, Benezeth, Y, Berbesque, C, Berrevoet, F, Biedermann, P, Bijleveld, E, Bittner, F, Blombach, F, van den Bos, W, Boudreau, S, Bramoweth, A, Braubach, O, Cai, Y, Campbell, M, Catry, T, Chen, X, Cheng, S, Chung, H, Chavez-Fumagalli, M, 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- Abstract
Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical science.
- Published
- 2019
14. Large expert-curated database for benchmarking document similarity detection in biomedical literature search
- Author
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R., van de Mortel, T., Moss, W. N., Moultos, O. A., Mukherjee, M., Nakayama, K., Narayan, E., Navaratnarajah, Neumann, P. -A., Nie, J., Nie, Y., Niemeyer, F., Nolan, F., Nwaiwu, O., Oldenmenger, W. H., Olumayede, E., Ou, J., Pallebage-Gamarallage, M., Pearce, S. P., Pelkonen, T., Pelleri, M. C., Pereira, J. L., Pheko, M., Pinto, K. A., Piovesan, A., Pluess, M., Podolsky, I. M., Prescott, J., Qi, D., Qi, X., Raikou, V. D., Ranft, A., Rhodes, J., Rotge, J. -Y., Rowe, A. D., Saggar, M., Schuon, R. A., Shahid, S., Shalchyan, V., Shirvalkar, P., Shiryayev, O., Singh, J., Smout, M. J., Soares, A., Song, C., Srivastava, K., Srivastava, R. K., Sun, J., Szabo, A., Szymanski, W., Tai, C. N. P., Takeuchi, H., Tanadini-Lang, S., Tang, F., Tao, W., Theron, G., Tian, C. F., Tian, Y. -S., Tuttle, L. M., Valenti, A., Verlot, P., Walker, M., Wang, J., Welter, D., Winslade, M., Wu, D., Wu, Y. -R., Xiao, H., Xu, B., Xu, Z., Yang, D., Yang, M., Yankilevich, P., You, Y., Yu, C., Zhan, J., Zhang, G., Zhang, K., Zhang, T., Zhao, G., Zhao, J., Zhou, X., Zhu, Z., Ajani, P. A., Anazodo, U. C., Bagloee, S. A., Bail, K., Bar, I., Bathelt, J., Benkeser, D., Bernier, M. L., Blanchard, A. M., Boakye, D. W., Bonatsos, V., Boon, M. H., Bouboulis, G., Bromfield, E., Brown, J., Bul, K. C. M., Burton, K. J., Butkowski, E. G., Carroll, G., Chao, F., Charrier, E. E., Chen, Y. -C., Chenguang, Choi, J. R., Christoffersen, T., Comel, J. C., Cosse, C., Cui, Y., van Dessel, P., Dhaval, Diodato, D., Duffey, M., Dutt, A., Egea, L. G., El-Said, M., Faye, M., Fernandez-Fernandez, B., Foley, K. G., Founou, L. L., Fu, F., Gadelkareem, R. A., Galimov, E., Garip, G., Gemmill, A., Gouil, Q., Grey, J., Gridneva, Z., Grothe, M. J., Grebert, T., Guerrero, F., Guignard, L., Haenssgen, M. J., Hasler, D., Holgate, J. Y., Huang, A., Hulse-Kemp, A. M., Jean-Quartier, C., Jeon, S. -M., Jia, Y., Jutzeler, C., Kalatzis, P., Karim, M., Karsay, K., Keitel, A., Kempe, A., Keown, J. R., Khoo, C. M., Khwaja, N., Kievit, R. A., Kosanic, S., Koutoukidis, D. A., Kramer, P., Kumar, D., Kirag, N., Lanza, G., Le, T. D., Leem, J. W., Leightley, D., Leite, A., Lercher, L., Li, Y., Lim, R., Lima, L. R. A., Lin, L., Ling, T., Liu, Y., Liu, Z., Lu, Y., Lum, F. M., Luo, H., Machhi, J., Macleod, A., Macwan, I., Madala, H. R., Madani, N., de Maio, N., Makowiecki, K., Mallinson, D. J., Margelyte, R., Maria, C., Markonis, Y., Marsili, L., Mavoa, S., Mcwilliams, L., Megersa, M., Souto-Maior, C., Menichetti, J., Mercieca-Bebber, R., Miller, J. J., Minde, D. -P. M., Minges, A., Mishra, E., Mishra, V. R., Moores, C., Morrice, N., Moskalensky, A. E., Navarin, N., Negera, E., Nolet, P., Nordberg, A., Norden, R., Nowicki, J. P., Olova, N., Olszewski, P., Onzima, R., Pan, C. -L., Park, C., Park, D. I., Park, S., Patil, C. D., Pedro, S. A., Perry, S. R., Peter, J., Peterson, B. M., Pezzuolo, A., Pozdnyakov, I., Qian, S., Qin, L., Rafe, A., Raote, I., Raza, A., Rebl, H., Refai, O., Regan, T., Richa, T., Richardson, M. F., Robinson, K. R., Rossoni, L., Rouet, R., Safaei, S., Schneeberger, P. H. H., Schwotzer, D., Sebastian, A., Selinski, J., Seltmann, S., Sha, F., Shalev, N., Shang, J. -L., Singer, J., Singh, M., Smith, T., Solomon-Moore, E., Song, L., Soraggi, S., Stanley, R., Steckhan, N., Strobl, F., Subissi, L., Supriyanto, I., Surve, C. R., Suzuki, T., Syme, C., Sorelius, K., Tang, Y., Tantawy, M., Tennakoon, S., Teseo, S., Toelzer, C., Tomov, N., Tovar, M., Tran, L., Tripathi, S., Tuladhar, A. M., Ukubuiwe, A. C., Ung, C. O. L., Valgepea, K., Vatanparast, H., Vidal, A., Wang, Q., Watari, R., Webster, R., Wei, J., Wibowo, D., Wingenbach, T. S. H., Xavier, R. M., Xiao, S., Xiong, P., Xu, S., Yao, R., Yao, W., Yin, Q., Zaitsu, M., Zeineb, Z., Zhan, X. -Y., Zhang, R., Zhang, W., Zheng, S., Zhou, B., Ahmad, H., Akinwumi, S. A., Albery, G. F., Alhowimel, A., Ali, J., Alshehri, M., Alsuhaibani, M., Anikin, A., Azubuike, S. O., Bach-Mortensen, A., Baltiansky, L., Bartas, M., Belachew, K. Y., Bhardwaj, V., Binder, K., Bland, N. S., Boah, M., Bullen, B., Calabro', Giovanna Elisa, Callahan, T. J., Cao, B., Chalmers, K., Chang, W., Che, Z., Chen, A. T. Y., Chen, Z., Choi, Y., Chowdhury, M. A. K., Christensen, M. R., Cooke, R. S. C., Cottini, M., Covington, N. V., Cunningham, C., Delarocque, J., Devos, L., Dhar, A. R., Ding, K. -F., Dong, K., Dong, Z., Dreyer, N., Ekstrand, C., Fardet, T., Feleke, B. E., Feurer, T., Freitas, A., Gao, T., Gebremedhin, Giganti, F., Grabowski, P., Guerra-Mora, J. R., Guo, C., Guo, X., Gupta, H., He, S., Heijne, M., Heinemann, S., Hogrebe, A., Huang, Z., Iskander-Rizk, S., Iyer, L. M., Jahan, Y., James, A. S., Joel, E., Joffroy, B., Jegousse, C., Kambondo, G., Karnati, P., Kaya, C., Ke, A., Kelly, D., Kickert, R., Kidibule, P. E., Kieselmann, J. P., Kim, H. J., Kitazawa, T., Lamberts, A., Liang, H., Linn, S. N., Litfin, T., Liusuo, W., Lygirou, V., Mahato, A. K., Mai, Z. -M., Major, R. W., Mali, S., Mallis, P., Mao, W., Marvin-Dowle, K., Mason, L. D., Merideth, B., Merino-Plaza, M. J., Merlaen, B., Messina, R., Mishra, A. K., Muhammad, J., Musinguzi, C., Nanou, A., Naqash, A., Nguyen, J. T., Nguyen, T. T. H., Ni, D., Nida, Notcovich, S., Ohst, B., Ollivier, Q. R., Osses, D. F., Peng, X., Plantinga, A., Pulia, M., Rafiq, M., Raman, A., Raucher-Chene, Rawski, R., Ray, A., Razak, L. A., Rudolf, K., Rusch, P., Sadoine, M. L., Schmidt, A., Schurr, R., Searles, S., Sharma, S., Sheehan, B., Shi, C., Shohayeb, B., Sommerlad, A., Strehlow, J., Sun, X., Sundar, R., Taherzadeh, G., Tahir, N. D. M., Tang, J., Testa, J., Tian, Z., Tingting, Q., Verheijen, G. P., Vickstrom, C., Wang, T., Wang, X., Wang, Z., Wei, P., Wilson, A., Wyart, Yassine, A. -A., Yousefzadeh, A., Zare, A., Zeng, Z., Zhang, H., Zhou, J., Zhu, D., Adamo, V., Adeyemo, A. A., Aggelidou, M., Al-Owaifeer, A. M., Al-Riyami, A. Z., Alzghari, S. K., Andersen, V., Angus, K., Asaduzzaman, M., Asady, H., Ato, D., Bai, X., Baines, R. L., Ballantyne, M., Ban, B., Beck, J., Ben-Nafa, W., Black, E., Blancher, A., Blankstein, R., Bodagh, N., Borges, P., Brooks, A., Brox-Ponce, J., Brunetti, A., Canham, C. D., Carninci, P., Carvajal, R., Chang, S. C., Chao, J., Chatterjee, P., Chen, L., Chhatriwalla, A. K., Chikowe, I., Chuang, T. -J., Collevatti, R. G., Cornejo, D. A. V., Cuenda, A., Dao, M., Dauga, D., Deng, Z., Devkota, K., Doan, L. V., Elewa, Y. H. A., Fan, D., Faruk, M., Feifei, S., Ferguson, T. S., Fleres, F., Foster, E. J., Foster, S., Furer, T., Gao, Y., Garcia-Rivera, E. J., Gazdar, A., George, R. B., Ghosh, S., Gianchecchi, E., Gleason, J. M., Hackshaw, A., Hall, A., Hall, R., Harper, P., Hogg, W. E., Huang, G., Hunter, K. E., Ijzerman, A. P., Jesus, C., Jian, G., Lewis, J. S., Kanj, S. S., Kaur, H., Kheir, F., Kichatova, V. S., Kiyani, M., Klein, R., Kovesi, T., Kraschnewski, J. L., Kumar, A. P., Labutin, D., Lazo-Langner, A., Leclercq, G., Li, M., Li, Q., Li, T., Liao, W. -T., Liao, Z. -Y., Lin, J., Lizer, J., Lobreglio, G., Lowies, C., Lu, C., Majeed, H., Martin, A., Martinez-Sobrido, L., Meresh, E., Middelveen, M., Mohebbi, A., Mota, J., Mozaheb, Z., Muyaya, L., Nandhakumar, A., Ng, S. H. X., Obeidat, M., Oh, D. -H., Owais, M., Pace-Asciak, P., Panwar, A., Patterson, C., Penagos-Tabaree, F., Pianosi, P. T., Pinzi, V., Pridans, C., Psaroulaki, A., Pujala, R. K., Pulido-Arjona, L., Qi, P. -F., Rahman, P., Rai, N. K., Rassaf, T., Refardt, J., Ricciardi, Walter, Riess, O., Rovas, A., Sacks, F. M., Saleh, S., Sampson, C., Schmutz, A., Sepanski, R., Sharma, N., Spearman, P., Subramaniapillai, M., Swali, R., Tan, C. M., Tellechea, J. I., Thomas, L. -M., Tong, X., Vavvas, D. G., Veys, R., Vitriol, V., Wang, H. -D., Waugh, J., Webb, S. A., Williams, B. A., Workman, A. D., Xiang, T., Xie, L. -X., Xu, T., Yang, C., Yoon, J. G., Yuan, C. M., Zaritsky, A., Zhao, H., Zuckerman, H., Lyu, R., Pullan, W., Calabro G. E. (ORCID:0000-0003-0259-3797), and Ricciardi W. (ORCID:0000-0002-5655-688X)
- Abstract
Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical science.
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- 2019
15. Reaction norm for yearling weight in beef cattle using single-step genomic evaluation
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Oliveira, D. P. [UNESP], Lourenco, D. A. L., Tsuruta, S., Misztal, I., Santos, D. J. A. [UNESP], Araujo Neto, F. R. de, Aspilcueta-Borquis, R. R., Baldi, F. [UNESP], Carvalheiro, R. [UNESP], Camargo, G. M. F. de [UNESP], Albuquerque, L. G. [UNESP], Tonhati, H. [UNESP], Universidade Estadual Paulista (Unesp), Univ Georgia, Fed Inst Sci & Technol Goiano, and Fed Univ Grande Dourados UFGD
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performance traits ,genotype by environment ,Bos taurus indicus ,genomic prediction - Abstract
Made available in DSpace on 2018-11-29T08:13:36Z (GMT). No. of bitstreams: 0 Previous issue date: 2018-01-01 Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) When the environment on which the animals are raised is very diverse, selecting the best sires for different environments may require the use of models that account for genotype by environment interaction (G x E). The main objective of this study was to evaluate the existence of G x E for yearling weight (YW) in Nellore cattle using reaction norm models with only pedigree and pedigree combined with genomic relationships. Additionally, genomic regions associated with each environment gradient were identified. A total of 67,996 YW records were used in reaction norm models to calculate EBV and genomic EBV. The method of choice for genomic evaluations was single-step genomic BLUP (ssGBLUP). Traditional and genomic models were tested on the ability to predict future animal performance. Genetic parameters for YW were obtained with the average information restricted maximum likelihood method, with and without adding genomic information for 5,091 animals. Additive genetic variances explained by windows of 200 adjacent SNP were used to identify genomic regions associated with the environmental gradient. Estimated variance components for the intercept and the slope in traditional and genomic models were similar. In both models, the observed changes in heritabilities and genetic correlations for YW across environments indicate the occurrence of genotype by environment interactions. Both traditional and genomic models were capable of identifying the genotype by environment interaction; however, the inclusion of genomic information in reaction norm models improved the ability to predict animals' future performance by 7.9% on average. The proportion of genetic variance explained by the top SNP window was 0.77% for the regression intercept (BTA5) and 0.82% for the slope (BTA14). Single-step GBLUP seems to be a suitable model to predict genetic values for YW in different production environments. Sao Paulo State Univ, Dept Anim Sci, FCAV, BR-14884900 Jaboticabal, Brazil Univ Georgia, Dept Anim & Dairy Sci, Athens, GA 30602 USA Fed Inst Sci & Technol Goiano, Campus Rio Verde, BR-75901970 Rio Verde, Go, Brazil Fed Univ Grande Dourados UFGD, Coll Agr Sci, Dourados, MS, Brazil Sao Paulo State Univ, Dept Anim Sci, FCAV, BR-14884900 Jaboticabal, Brazil CAPES: PDSE 012708/2013-05 FAPESP: 2009/16118-5
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- 2018
16. Contemporary group alternatives for genetic evaluation of milk yield in small populations of dairy cattle
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Pereira, R. J., primary, Schenkel, F. S., additional, Ventura, R. V., additional, Ayres, D. R., additional, El Faro, L., additional, Machado, C. H. C., additional, and Albuquerque, L. G., additional
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- 2019
- Full Text
- View/download PDF
17. Genome‐enabled prediction of reproductive traits in Nellore cattle using parametric models and machine learning methods.
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Alves, A. A. C., Espigolan, R., Bresolin, T., Costa, R. M., Fernandes Júnior, G. A., Ventura, R. V., Carvalheiro, R., and Albuquerque, L. G.
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PARAMETRIC modeling ,MACHINE learning ,ARTIFICIAL neural networks ,GENETIC correlations ,RANDOM forest algorithms ,CATTLE - Abstract
Summary: This study aimed to assess the predictive ability of different machine learning (ML) methods for genomic prediction of reproductive traits in Nellore cattle. The studied traits were age at first calving (AFC), scrotal circumference (SC), early pregnancy (EP) and stayability (STAY). The numbers of genotyped animals and SNP markers available were 2342 and 321 419 (AFC), 4671 and 309 486 (SC), 2681 and 319 619 (STAY) and 3356 and 319 108 (EP). Predictive ability of support vector regression (SVR), Bayesian regularized artificial neural network (BRANN) and random forest (RF) were compared with results obtained using parametric models (genomic best linear unbiased predictor, GBLUP, and Bayesian least absolute shrinkage and selection operator, BLASSO). A 5‐fold cross‐validation strategy was performed and the average prediction accuracy (ACC) and mean squared errors (MSE) were computed. The ACC was defined as the linear correlation between predicted and observed breeding values for categorical traits (EP and STAY) and as the correlation between predicted and observed adjusted phenotypes divided by the square root of the estimated heritability for continuous traits (AFC and SC). The average ACC varied from low to moderate depending on the trait and model under consideration, ranging between 0.56 and 0.63 (AFC), 0.27 and 0.36 (SC), 0.57 and 0.67 (EP), and 0.52 and 0.62 (STAY). SVR provided slightly better accuracies than the parametric models for all traits, increasing the prediction accuracy for AFC to around 6.3 and 4.8% compared with GBLUP and BLASSO respectively. Likewise, there was an increase of 8.3% for SC, 4.5% for EP and 4.8% for STAY, comparing SVR with both GBLUP and BLASSO. In contrast, the RF and BRANN did not present competitive predictive ability compared with the parametric models. The results indicate that SVR is a suitable method for genome‐enabled prediction of reproductive traits in Nellore cattle. Further, the optimal kernel bandwidth parameter in the SVR model was trait‐dependent, thus, a fine‐tuning for this hyper‐parameter in the training phase is crucial. [ABSTRACT FROM AUTHOR]
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- 2021
- Full Text
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18. Prediction of meat quality traits in Nelore cattle by near-infrared reflectance spectroscopy
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Magalhães, A F B, Teixeira, G H de A, Ríos, A C H, Silva, D B dos S, Mota, L F M, Muniz, M M M, Medeiros-De-morais, Camilo De lelis, de Lima, K M G, Cunha Júnior, L C, Baldi, F, Carvalheiro, R, Oliveira, H N de, Chardulo, L A L, Albuquerque, L G de, Magalhães, A F B, Teixeira, G H de A, Ríos, A C H, Silva, D B dos S, Mota, L F M, Muniz, M M M, Medeiros-De-morais, Camilo De lelis, de Lima, K M G, Cunha Júnior, L C, Baldi, F, Carvalheiro, R, Oliveira, H N de, Chardulo, L A L, and Albuquerque, L G de
- Abstract
The main definition for meat quality should include factors that affect consumer appreciation of the product. Physical laboratory analyses are necessary to identify factors that affect meat quality and specific equipment is used for this purpose, which is expensive and destructive, and the analyses are usually time consuming. An alternative method to performing several beef analyses is near-infrared reflectance spectroscopy (NIRS), which permits to reduce costs and to obtain faster, simpler, and non-destructive measurements. The objective of this study was to evaluate the feasibility of NIRS to predict shear force (WBSF), marbling, and color (*a=redness; b*=yellowness and L*=lightness) in meat samples of uncastrated male Nelore cattle, that were approximately 2-year-old. Samples of longissimus thoracis (n=644) were collected and spectra were obtained prior to meat quality analysis. Multivariate calibration was performed by partial least squares regression. Several preprocessing techniques were evaluated alone and in combination: raw data, reduction of spectral range, multiplicative scatter correction, and 1st derivative. Accuracies of the calibration models were evaluated using the root mean square error of calibration (RMSEC), root mean square error of prediction (RMSEP), coefficient of determination in the calibration (R²C) and prediction (R²P) groups. Among the different preprocessing techniques, the reduction of spectral range provided the best prediction accuracy for all traits. The NIRS showed a better performance to predict WBSF (RMSEP = 1.42kg, R²P = 0.40) and b* color (RMSEP = 1.21, R²P = 0.44), while its ability to accurately predict L* (RMSEP = 1.98, R²P = 0.16) and a* (RMSEP = 1.42, R²P = 0.17) was limited. NIRS was unsuitable to predict subjective meat quality traits such as marbling in Nelore cattle.
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- 2018
19. Reaction norm for yearling weight in beef cattle using single-step genomic evaluation1
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Oliveira, D P, primary, Lourenco, D A L, additional, Tsuruta, S, additional, Misztal, I, additional, Santos, D J A, additional, de Araújo Neto, F R, additional, Aspilcueta-Borquis, R R, additional, Baldi, F, additional, Carvalheiro, R, additional, de Camargo, G M F, additional, Albuquerque, L G, additional, and Tonhati, H, additional
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- 2018
- Full Text
- View/download PDF
20. Genome scan for postmortem carcass traits in Nellore cattle
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Júnior, G. A. Fernandes [UNESP], Costa, R. B. [UNESP], De Camargo, G. M.F. [UNESP], Carvalheiro, R. [UNESP], Rosa, G. J.M., Baldi, F. [UNESP], Garcia, D. A. [UNESP], Gordo, D. G.M. [UNESP], Espigolan, R. [UNESP], Takada, L. [UNESP], Magalhães, A. F.B. [UNESP], Bresolin, T. [UNESP], Feitosa, F. L.B. [UNESP], Chardulo, L. A.L. [UNESP], De Oliveira, H. N. [UNESP], De Albuquerque, L. G. [UNESP], Universidade Estadual Paulista (Unesp), CNPq, Univ Wisconsin, Dept Zootecnia, and University of Wisconsin–Madison
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beef cattle ,genome-wide association study ,backfat thickness ,carcass weight ,single-step genomic BLUP approach ,ribeye area - Abstract
Made available in DSpace on 2018-11-26T17:55:57Z (GMT). No. of bitstreams: 0 Previous issue date: 2016-10-01 Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Carcass traits measured after slaughter are economically relevant traits in beef cattle. In general, the slaughter house payment system is based on HCW. Ribeye area (REA) is associated with the amount of the meat in the carcass, and a minimum of backfat thickness (BFT) is necessary to protect the carcass during cooling. The aim of this study was to identify potential genomic regions harboring candidate genes affecting those traits in Nellore cattle. The data set used in the present study consisted of 1,756 Nellore males with phenotype records. A subset of 1,604 animals had both genotypic and phenotypic information. Genotypes were generated based on a panel with 777,962 SNPs from the Illumina Bovine HD chip. The SNP effects were calculated based on the genomic breeding values obtained by using the single-step GBLUP approach and a genomic matrix re-weighting procedure. The proportion of the variance explained by moving windows of 100 consecutive SNPs was used to assess potential genomic regions harboring genes with major effects on each trait. The top 10 non-overlapping SNP-windows explained 8.72%, 11.38%, and 9.31% of the genetic variance for REA, BFT, and HCW, respectively. These windows are located on chromosomes 5, 7, 8, 10, 12, 20, and 29 for REA; chromosomes 6, 8, 10, 13, 16, 17, 18, and 24 for BFT; and chromosomes 4, 6, 7, 8, 14, 16, 17, and 21 for HCW. For REA, there were identified genes (CDKN2A and CDKN2B) involved in the cell cycle biological process which affects many aspects of animal growth and development. The SLC38A1 and SLC38A2 genes, both from SLC38 AA transporter family, was also associated with REA. The AA transporters are essential for cell growth and proliferation, acting as carriers of tissue nutrient supplies. Various genes identified for BFT (SORCS2, AQP3, AQP7, CDC42BPA, ASIP, and ACSS2) have been associated with lipid metabolism in different mammal species. One of the most promising genes identified for HCW was the PLAG1. There is evidence, in the literature, that this gene is located in putative QTL affecting carcass weight in beef cattle. Our results showed several genomic regions containing plausible candidate genes that may be associated with carcass traits in Nellore cattle. Besides contributing to a better understanding of the genetic control of carcass traits, the identified genes can also be helpful for further functional genomic studies. UNESP, Fac Ciencias Agr & Vet, BR-14884000 Jaboticabal, SP, Brazil CNPq, Brasilia, DF, Brazil Univ Wisconsin, Madison, WI 53706 USA UNESP, Fac Med Vet & Zootecnia, BR-18618970 Botucatu, SP, Brazil Dept Zootecnia, Via Acesso Paulo Donato Castellane S-N, BR-14884900 Jaboticabal, SP, Brazil UNESP, Fac Ciencias Agr & Vet, BR-14884000 Jaboticabal, SP, Brazil UNESP, Fac Med Vet & Zootecnia, BR-18618970 Botucatu, SP, Brazil FAPESP: 2009/16118-5 FAPESP: 2015/06140-4
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- 2016
21. Comparison of models for the genetic evaluation of reproductive traits with censored data in Nellore cattle
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Garcia, D. A. [UNESP], Rosa, G. J. M., Valente, B. D., Carvalheiro, R. [UNESP], Albuquerque, L. G. [UNESP], Universidade Estadual Paulista (Unesp), University of Wisconsin–Madison, and Univ Wisconsin
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Days to calving ,Beef cattle ,Age at first calving ,Bayesian models - Abstract
Made available in DSpace on 2018-12-11T17:28:44Z (GMT). No. of bitstreams: 0 Previous issue date: 2016-06-01 Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) In typical genetic evaluation, often some females have missing records due to reproductive failure and due to voluntary and involuntary culling before the breeding season. These partially or unobserved phenotypes are known as censored records and their inclusion into genetic evaluations might lead to better inferences and breeding value predictions. Then, the objective was to compare prediction ability of models in which the phenotypic expression of age at the first calving (AFC) and days to calving (DC) were considered to be censored and uncensored in a Nellore cattle population. Age at first calving and days to calving were analyzed as following: uncensored animals (LM); penalization of 21 d (PLM); censored records simulated from truncated normal distributions (CLM); threshold-linear model in which censored records were handled as missing (TLM) or coded as the upper AFC/DC value within contemporary group (PTLM); and Weibull frailty hazard model (WM). Pearson correlations (PC), the percentage of the 10% best bulls in common (pTOP10%), accuracy of estimated breeding values (r), and a cross-validation scheme were performed. Heritability estimates for AFC were 0.18, 0.12, 0.12, 0.17, 0.14, and 0.07 for LM, PLM, CLM, TLM, PTLM, and WM, respectively. PC and pTOP10% were higher among linear models and smaller between these models and WM. The models provided similar r of sire breeding values. Heritability estimates for DC were 0.03, 0.08, 0.06, 0.02, 0.07, and 0.10 for LM, PLM, CLM, TLM, PTLM, and WM, respectively. Strongly associated predictions were observed in CLM, PLM, PTLM, and WM. The highest coincidence levels of sires in the TOP10% were between CLM, PLM, and PTLM. The r of sire breeding values obtained applying CLM, PLM, PTLM, and WM were similar and higher than those obtained with LM and TLM. In terms of prediction ability, WM, PLM, TLM, and PTLM showed similar prediction performance for AFC. On the other hand, CLM, PLM, PTLM, and WM showed the similar prediction ability for DC Therefore, these models would be recommended to perform genetic evaluation of age at first calving and days to calving in this Nellore population. Department of Animal Science UNESP, Prof. Paulo Donato Castellani Road Department of Animal Science University of Wisconsin–Madison, 1675 Observatory Drive Department of Animal Science UNESP, Prof. Paulo Donato Castellani Road CAPES: 1817-12-4 FAPESP: 2009/15010-6
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- 2016
22. Genetic parameter estimates for carcass traits and visual scores including or not genomic information
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Gordo, D. G. M. [UNESP], Espigolan, R. [UNESP], Tonussi, R. L. [UNESP], Junior, G. A. F. [UNESP], Bresolin, T. [UNESP], Braga Magalhaes, A. F. [UNESP], Feitosa, F. L. [UNESP], Baldi, F. [UNESP], Carvalheiro, R. [UNESP], Tonhati, H. [UNESP], Oliveira, H. N. de [UNESP], Chardulo, L. A. L. [UNESP], Albuquerque, L. G. de [UNESP], Universidade Estadual Paulista (Unesp), and Dept Zootecnia
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beef cattle ,single nucleotide polymorphism ,fat thickness ,longissimus muscle area ,heritability ,genetic correlation - Abstract
Made available in DSpace on 2018-11-26T17:55:50Z (GMT). No. of bitstreams: 0 Previous issue date: 2016-05-01 Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) The objective of this study was to determine whether visual scores used as selection criteria in Nellore breeding programs are effective indicators of carcass traits measured after slaughter. Additionally, this study evaluated the effect of different structures of the relationship matrix (A and H) on the estimation of genetic parameters and on the prediction accuracy of breeding values. There were 13,524 animals for visual scores of conformation (CS), finishing precocity (FP), and muscling (MS) and 1,753, 1,747, and 1,564 for LM area (LMA), backfat thickness (BF), and HCW, respectively. Of these, 1,566 animals were genotyped using a high-density panel containing 777,962 SNP. Six analyses were performed using multitrait animal models, each including the 3 visual scores and 1 carcass trait. For the visual scores, the model included direct additive genetic and residual random effects and the fixed effects of contemporary group (defined by year of birth, management group at yearling, and farm) and the linear effect of age of animal at yearling. The same model was used for the carcass traits, replacing the effect of age of animal at yearling with the linear effect of age of animal at slaughter. The variance and covariance components were estimated by the REML method in analyses using the numerator relationship matrix (A) or combining the genomic and the numerator relationship matrices (H). The heritability estimates for the visual scores obtained with the 2 methods were similar and of moderate magnitude (0.23-0.34), indicating that these traits should response to direct selection. The heritabilities for LMA, BF, and HCW were 0.13, 0.07, and 0.17, respectively, using matrix A and 0.29, 0.16, and 0.23, respectively, using matrix H. The genetic correlations between the visual scores and carcass traits were positive, and higher correlations were generally obtained when matrix H was used. Considering the difficulties and cost of measuring carcass traits postmortem, visual scores of CS, FP, and MS could be used as selection criteria to improve HCW, BF, and LMA. The use of genomic information permitted the detection of greater additive genetic variability for LMA and BF. For HCW, the high magnitude of the genetic correlations with visual scores was probably sufficient to recover genetic variability. The methods provided similar breeding value accuracies, especially for the visual scores. Univ Estadual Paulista, Fac Ciencias Agr & Vet, BR-14884900 Jaboticabal, SP, Brazil Univ Estadual Paulista, Fac Med Vet & Zootecnia, BR-18618970 Botucatu, SP, Brazil Dept Zootecnia, Via Acesso Paulo Donato Castellane S-N, BR-14884900 Jaboticabal, SP, Brazil Univ Estadual Paulista, Fac Ciencias Agr & Vet, BR-14884900 Jaboticabal, SP, Brazil Univ Estadual Paulista, Fac Med Vet & Zootecnia, BR-18618970 Botucatu, SP, Brazil FAPESP: 2009/16118-5 FAPESP: 2014/11537-8
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- 2016
23. Inbreeding depression in zebu cattle traits
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PEREIRA, R. J., SANTANA JUNIOR, M. L., AYRES, D. R., BIGNARDI, A. B., MENEZES, G. R. de O., SILVA, L. O. C. da, MACHADO, C. H. C., JOSAHKIAN, L. A., ALBUQUERQUE, L. G., GMAT/UFMT, GILBERTO ROMEIRO DE OLIVEIRA MENEZE, CNPGC, LUIZ OTAVIO CAMPOS DA SILVA, CNPGC, Associalão Brasileira dos criadores de Zebu, Uberlândia, Associação Brasileira dos Criadores de Zebu, Uberlândia, and FCAV/USP.
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Gado leiteiro ,Reproduction ,Gado de corte ,Beef cattle ,Dairy cattle ,Growth ,Reprodução ,Calving performance - Abstract
The productivity of herds may be negatively affected by inbreeding depression, and it is important to know how intense is this effect on the livestock performance. We performed a comprehensive analysis involving five Zebu breeds reared in Brazil to estimate inbreeding depression in productive and reproductive traits. Inbreeding depression was estimated for 13 traits by including the individual inbreeding rate as a linear covariate in the standard genetic evaluation models. For all breeds and for almost all traits (no effect was observed on gestation length), the performance of the animals was compromised by an increase in inbreeding. The average inbreeding depression was B0.222% and B0.859% per 1% of inbreeding for linear regression coefficients scaled on the percentage of mean (bm) and standard deviation (br), respectively. The means for bm (and B) were B0.269% (B1.202%) for weight/growth traits and B0.174% (B0.546%) for reproductive traits. Hence, inbreeding depression is more pronounced in weight/growth traits than in reproductive traits. These findings highlight the need for the management of inbreeding in the respective breeding programmes of the breeds studied here.
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- 2016
24. Valores econômicos para sistemas de recria e engorda de bovinos Nelore e cruzado
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Albuquerque, L. G
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CARCAÇA - Published
- 2016
25. Genetic parameters for milk yield of Bubalus bubalis using unadjusted and adjusted milk production for days in milk
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Tonhati, H. [UNESP], Baldi, F. S. [UNESP], Laureano, M. M.M. [UNESP], Albuquerque, L. G. [UNESP], Universidade Estadual Paulista (Unesp), Universidade Estadual Paulista (UNESP), and CAPES
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Spearman correlations ,Genetic parameters, Lactation length, Milk production, Spearman correlations ,Milk production ,lcsh:Animal culture ,Genetic parameters ,Lactation length ,lcsh:SF1-1100 - Abstract
Submitted by Guilherme Lemeszenski (guilherme@nead.unesp.br) on 2014-02-26T17:18:33Z No. of bitstreams: 1 WOS000207598400042.pdf: 120641 bytes, checksum: 956b0ad7b27c7f0d2d13df6f51dba419 (MD5) Made available in DSpace on 2014-02-26T17:18:33Z (GMT). No. of bitstreams: 1 WOS000207598400042.pdf: 120641 bytes, checksum: 956b0ad7b27c7f0d2d13df6f51dba419 (MD5) Previous issue date: 2007-01-01 Submitted by Vitor Silverio Rodrigues (vitorsrodrigues@reitoria.unesp.br) on 2014-05-20T13:18:02Z No. of bitstreams: 1 WOS000207598400042.pdf: 120641 bytes, checksum: 956b0ad7b27c7f0d2d13df6f51dba419 (MD5) Made available in DSpace on 2014-05-20T13:18:02Z (GMT). No. of bitstreams: 1 WOS000207598400042.pdf: 120641 bytes, checksum: 956b0ad7b27c7f0d2d13df6f51dba419 (MD5) Previous issue date: 2007-01-01 Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) The objectives of this study were to estimate genetic parameters for unadjusted and adjusted milk production for 270 and 305 days of lactation and, subsequently, to verify the coincidence of rank of 2%, 5%, 20% and 40% best sires selected based on both models. Complete lactations from 90 or 150 days of lactation to 270 or 350 days of lactation were considered in the analyses. Milk production was adjusted for lactation length by multiplicative correction factors, or by including lactation length as a covariable in the model. Heritabilities, genetic correlations and breeding values were estimated for each trait, and variance and covariance components were estimated by restricted maximum likelihood methodology. Heritability estimates varied from 0.16 to 0.27. Genetic correlations between unadjusted and adjusted milk production for lactation length were higher than 0.64. Heritabilities for adjusted milk production were higher than heritabilities for unadjusted milk production for lactation length. In situations with high selection intensity, probably, modifications will happen in the rank of bulls and/or in the bulls chosen for mating if records are adjusted or unadjusted for 305 days. Univ São Paulo State, Dept Zootecnia, Fac Ciências Agr & Vet, UNESP, BR-14884000 Jaboticabal, SP, Brazil CNPq, FAPESP, CAPES, Campinas, SP, Brazil Univ São Paulo State, Dept Zootecnia, Fac Ciências Agr & Vet, UNESP, BR-14884000 Jaboticabal, SP, Brazil
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- 2010
26. 207 Genome-wide association study for beef fatty acid profile using haplotypes in Nellore cattle
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Feitosa, F. L. B., primary, Braz, C. U., additional, Lemos, M. V. A. D., additional, Berton, M. P., additional, Silva, R. M. D. O., additional, Tonussi, R. L., additional, Peripolli, E., additional, Olivieri, B. F., additional, Ferrinho, A. M., additional, Mueller, L. F., additional, Furlan, J. D. J. M., additional, Pereira, A. S. C., additional, de Albuquerque, L. G., additional, Schenkel, F. S., additional, and Baldi, F., additional
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- 2017
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27. Meat quality traits of Nellore bulls according to different degrees of backfat thickness: a multivariate approach
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Baldassini, W. A., primary, Chardulo, L. A. L., additional, Silva, J. A. V., additional, Malheiros, J. M., additional, Dias, V. A. D., additional, Espigolan, R., additional, Baldi, F. S., additional, Albuquerque, L. G., additional, Fernandes, T. T., additional, and Padilha, P. M., additional
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- 2017
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28. Principal component analysis of breeding values for growth and reproductive traits and genetic association with adult size in beef cattle1
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Boligon, A. A., primary, Vicente, I. S., additional, Vaz, R. Z., additional, Campos, G. S., additional, Souza, F. R. P., additional, Carvalheiro, R., additional, and Albuquerque, L. G., additional
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- 2016
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29. Differential expression of immune response genes associated with subclinical mastitis in dairy buffaloes.
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Tanamati, F., Stafuzza, N. B., Gimenez, D. F. J., Stella, A. A. S., Santos, D. J. A., Ferro, M. I. T., Albuquerque, L. G., Gasparino, E., and Tonhati, H.
- Abstract
Buffalo milk production has become of significant importance on the world scale, however, there are few studies involving biotechnological tools specifically for buffalo. To verify the effects caused by subclinical mastitis on the components of milk and to study the innate immune system in the udder of dairy buffaloes with subclinical mastitis, we evaluated the levels of expression of the lactoferrin (LTF), tumor necrosis factor alpha (TNF-α), interleukin-1 beta (IL-1β), interleukin-8 (IL-8), and toll-like receptors 2 (TLR-2) and 4 (TLR-4) genes in buffaloes with and without subclinical mastitis. Milk samples were collected for the determination of milk components: somatic cell score (SCS), fat, protein, lactose, total solids and solids-not-fat (SNF), as well as for RNA extraction of milk cells, complementary DNA synthesis, and expression profile quantification by quantitative real-time PCR. For gene expression, the ΔΔCt was estimated using contrasts of the target genes expression adjusted for the expression of the housekeeping genes between both groups. Linear regression analysis was performed to determine the relationship between the genes studied and the milk components. Subclinical mastitis induced changes in the fat, lactose and SNF in milk of buffaloes, and the messenger RNA abundance was upregulated for TLR-2, TLR-4, TNF-α, IL-1β and IL-8 genes in milk cells of buffaloes with subclinical mastitis, whereas the LTF gene was not differentially expressed. Results of linear regression analysis showed that TLR-2 gene expression most explains the variation in SCS, and the change in a unit of ΔCt of the TNF-α gene would result in a higher increase in SCS. The study of these immune function genes that are active in the mammary gland is important to characterize the action mechanism of the innate immunity that occurs in subclinical mastitis in dairy buffaloes and may aid the development of strategies to preserve the health of the udder. [ABSTRACT FROM AUTHOR]
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- 2019
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30. Economic values for growth and finishing production systems of Nellore and crossbred cattle
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Peripolli, E., Oliveira, M.A.L., Baldi, F., Vercesi, A., Albuquerque, L. G., Pereira, A.S.C., Peripolli, E., Oliveira, M.A.L., Baldi, F., Vercesi, A., Albuquerque, L. G., and Pereira, A.S.C.
- Abstract
A bio-economic model called Beef Management System was developed to obtain economic values for four growth and finishing cattle production system. A total of four rearing and finishing systems, two were composed by Nellore cattle and the others by crossbred cattle (½ Taurine; ½ Zebu) were tested. For each genetic group, two production systems were developed, one with full time grazing animals and the second with animals grazing during the rearing period and subsequent feedlot finishing. The economic values were estimated by simulations in electronic tables, using the Microsoft Office Excel, considering the average daily gain (ADG), dressing percentage (DP), feed intake (FI) and maintenance energy (ME) for each production system proposed. To obtain the economic values, ADG and DP were increased in 1 %, and ME and FI were reduced in 1 %. With an increase of 1 % in the DP and ADG, the cost to obtain 33.11 pounds decreased in all studied models. A 1 % reduction in animal’s ME resulted in a decrease of 0.45 % in the cost to produce 33.11 pounds in both grazing and subsequent feedlot models and decreased 0.55 % in both full grazing models. With the 1 % reduction in animal’s CA, the cost of 33.11 pounds decreased 0.83 and 0.84 % in the grazing and subsequent feedlot models with Nellore and Crossed cattle; and 0.85 and 0.83 % in full grazing models with Nellore and Crossed cattle. These traits shown an enormous impact on growth and fattening economic systems in cattle production, and DP shown an advantage over the others, once this variable resulted in the highest economic values for all systems analyzed. Thus, through the composition of the four models and the variables included in each of them, it was possible to measure the real genetic impact and its importance related to economic values in cattle production., Foi desenvolvido o modelo bioeconômico nominado de Beef Management System para a obtenção de valores econômicos em quatro sistemas de recria e engorda de bovinos. Dos modelos analisados, dois utilizaram machos inteiros da raça Nelore e os outros dois machos inteiros cruzados (½ sangue taurino; ½ sangue zebu). Para cada grupamento genético estipulou-se dois modelos de produção, um 100 % a pasto e o outro com recria em pastagem e posterior confinamento. O estudo foi conduzido por meio de simulações em planilhas eletrônicas interligadas do programa Microsoft Office Excel. Os valores econômicos foram estimados para as características de ganho médio diário (GMD), rendimento de carcaça (RC), consumo alimentar (CA) e energia de mantença (EM), para cada um dos modelos propostos. Para obtenção dos valores econômicos, estipulou-se um aumento de 1 % no GMD e RC, e diminuiu-se 1 % da EM e CA. Com o aumento de 1 % no RC e no GMD, o custo de produção diminuiu 14,69 kg de carne (1 unidade de arroba) em todos os modelos estudados. A redução de 1 % na EM dos animais resultou em uma diminuição de 0,45 % no custo de produção de 14,69 kg de carne em ambos os modelos a pasto com confinamento e 0,55 % em ambos os modelos 100 % a pasto. Com a redução de 1 % na CA, o custo de produção de 14,69 kg de carne diminuiu 0,83 e 0,84 % nos modelos a pasto com confinamento de animais Nelores e cruzados e 0,85 e 0,83 % nos modelos 100 % a pasto de animais Nelores e cruzados. Essas características possuem um grande impacto econômico nos sistemas de recria e engorda, com grande vantagem para a característica de RC, uma vez que esta proporcionou os maiores valores econômicos para todos os sistemas estudados. Por meio das variáveis que compuseram os modelos estudados tornou-se possível mensurar a real importância do impacto genético das características e seus respectivos valores econômicos.
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- 2016
31. Genome scan for postmortem carcass traits in Nellore cattle1
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Júnior, G. A. Fernandes, primary, Costa, R. B., additional, de Camargo, G. M. F., additional, Carvalheiro, R., additional, Rosa, G. J. M., additional, Baldi, F., additional, Garcia, D. A., additional, Gordo, D. G. M., additional, Espigolan, R., additional, Takada, L., additional, Magalhães, A. F. B., additional, Bresolin, T., additional, Feitosa, F. L. B., additional, Chardulo, L. A. L., additional, de Oliveira, H. N., additional, and de Albuquerque, L. G., additional
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- 2016
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32. Accuracies of genomic prediction of feed efficiency traits using different prediction and validation methods in an experimental Nelore cattle population1
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Silva, R. M. O., primary, Fragomeni, B. O., additional, Lourenco, D. A. L., additional, Magalhães, A. F. B., additional, Irano, N., additional, Carvalheiro, R., additional, Canesin, R. C., additional, Mercadante, M. E. Z., additional, Boligon, A. A., additional, Baldi, F. S., additional, Misztal, I., additional, and Albuquerque, L. G., additional
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- 2016
- Full Text
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33. Valores econômicos para sistemas de recria e engorda de bovinos Nelore e cruzado
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Peripolli, E., primary, Oliveira, M. A. L., additional, Baldi, F., additional, Pereira, A. S. C., additional, Vercesi, A. E., additional, and Albuquerque, L. G., additional
- Published
- 2016
- Full Text
- View/download PDF
34. Comparison of models for the genetic evaluation of reproductive traits with censored data in Nellore cattle1
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Garcia, D. A., primary, Rosa, G. J. M., additional, Valente, B. D., additional, Carvalheiro, R., additional, and Albuquerque, L. G., additional
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- 2016
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35. Genetic parameter estimates for carcass traits and visual scores including or not genomic information1
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Gordo, D. G. M., primary, Espigolan, R., additional, Tonussi, R. L., additional, Júnior, G.A.F., additional, Bresolin, T., additional, Magalhães, A. F. Braga, additional, Feitosa, F. L., additional, Baldi, F., additional, Carvalheiro, R., additional, Tonhati, H., additional, de Oliveira, H. N., additional, Chardulo, L. A. L., additional, and de Albuquerque, L. G., additional
- Published
- 2016
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36. Genome-wide association study for growth traits in Nelore cattle.
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Terakado, A. P. N., Costa, R. B., de Camargo, G. M. F., Irano, N., Bresolin, T., Takada, L., Carvalho, C. V. D., Oliveira, H. N., Carvalheiro, R., Baldi, F., and de Albuquerque, L. G.
- Abstract
The objective of this study was to investigate the association of single nucleotide polymorphisms (SNPs) with birth weight, weight gain from birth to weaning and from weaning to yearling, yearling height and cow weight in Nelore cattle. Data from 5064 animals participating in the DeltaGen and PAINT breeding programs were used. The animals were genotyped with a panel of 777 962 SNPs (Illumina BovineHD BeadChip) and 412 993 SNPs remained after quality control analysis of the genomic data. A genome-wide association study was performed using a single-step methodology. The analyses were processed with the BLUPF90 family of programs. When applied to a genome-wide association studies, the single-step GBLUP methodology is an iterative process that estimates weights for the SNPs. The weights of SNPs were included in all analyses by iteratively applying the single-step GBLUP methodology and repeated twice so that the effect of the SNP and the effect of the animal were recalculated in order to increase the weight of SNPs with large effects and to reduce the weight of those with small effects. The genome-wide association results are reported based on the proportion of variance explained by windows of 50 adjacent SNPs. Considering the two iterations, only windows with an additive genetic variance >1.5% were presented in the results. Associations were observed with birth weight on BTA 14, with weight gain from birth to weaning on BTA 5 and 29, with weight gain from weaning to yearling on BTA 11, and with yearling height on BTA 8, showing the genes
TMEM68 (transmembrane protein 8B) associated with birth weight and yearling height,XKR4 (XK, Kell blood group complex subunit-related family, member 4) associated with birth weight,NPR2 (natriuretic peptide receptor B) associated with yearling height, andREG3G (regenerating islet-derived 3-gamma) associated with weight gain from weaning to yearling. These genes play an important role in feed intake, weight gain and the regulation of skeletal growth. [ABSTRACT FROM AUTHOR]- Published
- 2018
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37. Method for the estimation of genetic merit of animals with uncertain paternity under Bayesian inference.
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Shiotsuki, L., Cardoso, F. F., and Albuquerque, L. G.
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ANIMAL genetics ,BAYESIAN analysis ,ANIMAL paternity ,ARTIFICIAL insemination of cattle ,CATTLE breeding - Abstract
Summary: The use of controlled mating or artificial insemination is impracticable in the case of large herds, mainly because of labour costs and the need to delimit areas during the breeding period. However, the exclusion of information from animals with uncertain paternity reduces genetic progress. The objectives of this study were as follows: (i) propose an iterative empirical Bayesian procedure to implement the hierarchical animal model (ITER); (ii) calculate the posterior probabilities of paternity by the maximum likelihood method following the concepts; (iii) compare an average numerator relationship matrix (ANRM), Bayesian hierarchical (HIER) models and ITER. Records of Nellore animals born between 1984 and 2006 from the zootechnical archive of Agropecuária Jacarezinho Ltda were used. For data consistency, records of contemporary groups (CGs) with fewer than three animals and animals whose records were 3.5 standard deviations above or below the mean of their CG were eliminated. After editing the data, 62,212 animals in the file and 12,876 animals in pedigree file were maintained, respectively. Spearman and Pearson correlations between the posterior mean of the genetic effects of animals were calculated to compare the ranking of animals for selection. Simulated data were used to confirm the veracity of the model. The correlations between ITER and HIER and between ITER and ANRM were similar evaluating different files, which decreased at the same proportion when only high‐ranked animals were evaluated. In conclusion, the model proposed herein is a suitable computational alternative to improve the prediction of breeding values of animals in genetic evaluations using large databases, including animals with uncertain paternity. [ABSTRACT FROM AUTHOR]
- Published
- 2018
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38. Evaluation of longevity modeling censored records in Nellore.
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Garcia, D. A., Rosa, G. J. M., Valente, B. D., Carvalheiro, R., Fernandes Júnior, G. A., and Albuquerque, L. G.
- Abstract
The aim of the present study was to evaluate the prediction ability of models that cope with longevity phenotypic expression as uncensored and censored in Nellore cattle. Longevity was defined as the difference between the dates of last weaned calf and cow birth. There were information of 77 353 females, being 61 097 cows with uncensored phenotypic information and 16 256 cows with censored records. These data were analyzed considering three different models: (1) Gaussian linear model (LM), in which only uncensored records were considered; and two models that consider both uncensored and censored records: (2) Censored Gaussian linear model (CLM); and (3) Weibull frailty hazard model (WM). For the model prediction ability comparisons, the data set was randomly divided into training and validation sets, containing 80% and 20% of the records, respectively. There were considered 10 repetitions applying the following restrictions: (a) at least three animals per contemporary group in the training set; and (b) sires with more than 10 progenies with uncensored records (352 sires) should have daughters in the training and validation sets. The variance components estimated using the whole data set in each model were used as true values in the prediction of breeding values of the animals in the training set. The WM model showed the best prediction ability, providing the lowest χ2 average and the highest number of sets in which a model had the smallest value of χ2 statistics. The CLM and LM models showed prediction abilities 2.6% and 3.7% less efficient than WM, respectively. In addition, the accuracies of sire breeding values for LM and CLM were lower than those obtained for WM. The percentages of bulls in common, considering only 10% of sires with the highest breeding values, were around 75% and 54%, respectively, between LM–CLM and LM–WM models, considering all sires, and 75% between LM–CLM and LM–WM, when only sires with more than 10 progenies with uncensored records were taken into account. These results are indicative of reranking of animals in terms of genetic merit between LM, CLM and WM. The model in which censored records of longevity were excluded from the analysis showed the lowest prediction ability. The WM provides the best predictive performance, therefore this model would be recommended to perform genetic evaluation of longevity in this population. [ABSTRACT FROM PUBLISHER]
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- 2017
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39. Parámetros genéticos de las características andrológicas en la especie bovina
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Silva, M. R., Pedrosa, V. B., Silva, J. B.C., Herrera, L. G.G., Eler, J. P., and Albuquerque, L. G.
- Abstract
The sexual precocity and fertility of bovines have great impact on the economic success of commercial cattle herds, where some reproductive traits have been adopted as selection criteria. However, the majority of these traits depend on reproductive events of the females and, with exception of the scrotal circumference, few studies approach others andrological traits. The estimation of heritabilities and genetic correlations of testicular and seminal traits and also sexual behaviour, will allow to provide alternatives for the design of more appropriate selection strategies for fertility, together with other economic traits.  , La precocidad sexual y fertilidad tienen gran impacto en el éxito económico de los rebaños bovinos comerciales, en que las características reproductivas han sido adoptadas como criterios de selección. Sin embargo, la mayoría de estas características dependen de eventos reproductivos de las hembras y, con excepción del perímetro escrotal, pocos estudios abordan las características andrológicas. Las estimaciones de las heredabilidades y correlaciones genéticas de las características testiculares y seminales, además del comportamiento sexual, podrán proveer alternativas para la elaboración de estrategias más adecuadas de selección para fertilidad, en conjunto con las demás características de interés económico.  
- Published
- 2012
40. Características reprodutivas e suas associações com outras características de importância econômica na raça Nelore
- Author
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YOKOO, M. J. I., MAGNABOSCO, C. de U., LÔBO, R. B., ALBUQUERQUE, L. G., MARCOS JUN ITI YOKOO, CPPSUL, CLAUDIO DE ULHOA MAGNABOSCO, CPAC, R. B. Lôbo, Associação Nacional de Criadores e Pesquisadores, and L. G. Albuquerque, UNESP.
- Subjects
Gado de Corte - Published
- 2012
41. Bayesian analysis of random regression models using B-splines to model test-day milk yield of Holstein cattle in Brazil
- Author
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Albuquerque, L G
- Subjects
INFERÊNCIA BAYESIANA - Published
- 2012
42. Genetic association between body composition measured by ultrasound and visual scores in brazilian nelore cattle
- Author
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Albuquerque, L. G.
- Subjects
HERDABILIDADE - Published
- 2012
43. Random regression models using different functions to model test-day milk yield of Brazilian Holstein cows
- Author
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Albuquerque, L. G
- Subjects
BOVINOS LEITEIROS - Published
- 2011
44. Modeling of average growth curve in Santa Ines sheep using random regression models
- Author
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SAMENTO, J. L. R., TORRES, R. de A., SOUSA, W. H. de, ALBUQUERQUE, L. G. de, LOBO, R. N. B., SOUSA, J. E. R. de, José Lindenberg Rocha Sarmento, Universidade Federal do Piauí (UFPI), Bom Jesus, PI, Brasil., Robledo de Almeida Torres, UFV, Viçosa, MG, Brasil., Wandrick Hauss de Sousa, EMEPA, João Pessoa, PB, Brasil., Lucia Galvão de Albuquerque, UNESP, Jaboticabal, SP, Brasil., RAIMUNDO NONATO BRAGA LOBO, CNPC, and José Ernandes Rufino de Sousa, Universidade Federal do Piauí (UFPI), Bom Jesus, PI, Brasil.
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Modelo matemático ,Sheep ,Regressão fixa ,Ovino ,Modelo animal ,Herdabilidade ,Melhoramento genético animal ,Heritability ,Funções polinomiais ,Modelo de regressão ,Raça Santa Inês ,Growth models ,Genética animal ,Valor genético ,Curva de crescimento ,Animal genetics ,Breeding value ,Brazil ,Animal breeding - Abstract
Polynomial functions of age of different orders were evaluated in the modeling of the average growth trajectory in Santa Ines sheep in random regression models. Initially, the analyses were performed not considering the animal effect. Subsequently, the random regression analyses were performed including the random effects of the animal and its mother (genetic and permanent environment). The linear fit was lower, and the other orders were similar until near 100 days of age. The cubic function provided the closest fit of the observed averages, mainly at the end of the curve. Orders superior to this one tended to present incoherent behavior with the observed weights. The estimated direct heritabilities, considering the linear fit, were higher to those estimated by considering other functions. The changes in animal ranking based on predicted breeding values using linear fit and superior orders were small; however, the difference in magnitude of the predicted breeding values was higher, reaching values 77% higher than those obtained with the cubic function. The cubic polynomial function is efficient in describing the average growth curve. [Modelagem da curva média de crescimento de ovinos Santa Inês em modelos de regressão aleatória]. Resumo: Funções polinomiais da idade de diferentes ordens foram avaliadas na modelagem da trajetória média de crescimento de ovinos Santa Inês em modelos de regressão aleatória. As análises foram executadas inicialmente desconsiderando o efeito de animal. Posteriormente, as análises de regressão aleatória foram realizadas incluindo-se os efeitos aleatórios de animal e da mãe (genético e de ambiente permanente). O ajuste linear foi inferior, e as demais ordens foram semelhantes até próximo dos 100 dias de idade. A função cúbica proporcionou o ajuste mais próximo das médias observadas, principalmente ao final da curva. Ordens superiores a esta tenderam a apresentar comportamento incoerente com os pesos observados. As herdabilidades diretas estimadas considerando ajuste linear foram superiores às estimadas considerando as demais funções. As mudanças no ordenamento dos animais, com base nos valores genéticos preditos empregando ajuste linear e de ordens superiores, foram pequenas, porém, a diferença na magnitude dos valores genéticos preditos foi maior, chegando a valores 77% maiores que os obtidos com a função cúbica. A função polinomial cúbica é eficiente para descrever a curva média de crescimento.
- Published
- 2011
45. Random regression models on Legendre polynomials to estimate genetic parameters for weights from birth to adult age in Canchim cattle
- Author
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Baldi, Fernando, Albuquerque, L. G., Alencar, M. M., Universidade de São Paulo (USP), and Empresa Brasileira de Pesquisa Agropecuária (EMBRAPA)
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Growth curve ,Covariance functions ,Legendre polynomials ,Beef cattle - Abstract
Made available in DSpace on 2022-04-29T08:44:18Z (GMT). No. of bitstreams: 0 Previous issue date: 2010-08-01 The objective of this work was to estimate covariance functions for direct and maternal genetic effects, animal and maternal permanent environmental effects, and subsequently, to derive relevant genetic parameters for growth traits in Canchim cattle. Data comprised 49 011 weight records on 2435 females from birth to adult age. The model of analysis included fixed effects of contemporary groups (year and month of birth and at weighing) and age of dam as quadratic covariable. Mean trends were taken into account by a cubic regression on orthogonal polynomials of animal age. Residual variances were allowed to vary and were modelled by a step function with 1, 4 or 11 classes based on animal's age. The model fitting four classes of residual variances was the best. A total of 12 random regression models from second to seventh order were used to model direct and maternal genetic effects, animal and maternal permanent environmental effects. The model with direct and maternal genetic effects, animal and maternal permanent environmental effects fitted by quadric, cubic, quintic and linear Legendre polynomials, respectively, was the most adequate to describe the covariance structure of the data. Estimates of direct and maternal heritability obtained by multi-trait (seven traits) and random regression models were very similar. Selection for higher weight at any age, especially after weaning, will produce an increase in mature cow weight. The possibility to modify the growth curve in Canchim cattle to obtain animals with rapid growth at early ages and moderate to low mature cow weight is limited. © 2010 Blackwell Verlag GmbH. Animal Science Departament FCAV, University of São Paulo State, Jaboticabal (SP) 14884 000 Southeast Embrapa Cattle, 13560 970, São Carlos (SP)
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- 2010
46. Genetic associations between scrotal circumference and female reproductive traits in Nelore cattle1
- Author
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Terakado, A. P. N., primary, Boligon, A. A., additional, Baldi, F., additional, Silva, J. A. II V., additional, and Albuquerque, L. G., additional
- Published
- 2015
- Full Text
- View/download PDF
47. Genotype × environment interaction for age at first calving, scrotal circumference, and yearling weight in Nellore cattle using reaction norms in multitrait random regression models
- Author
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Chiaia, H. L. J., primary, de Lemos, M. V. A., additional, Venturini, G. C., additional, Aboujaoude, C., additional, Berton, M. P., additional, Feitosa, F. B., additional, Carvalheiro, R., additional, Albuquerque, L. G., additional, de Oliveira, H. N., additional, and Baldi, F., additional
- Published
- 2015
- Full Text
- View/download PDF
48. Assessment of DGAT1 and LEP gene polymorphisms in three Nelore (Bos indicus) lines selected for growth and their relationship with growth and carcass traits
- Author
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Albuquerque, L G
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GADO NELORE - Published
- 2010
49. Caracterizacao do polimorfismo no gene MUC1 em tres linhas de selecao para crescimento em bovinos Nelore
- Author
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de Souza, F. R. P., Sartore, Stefano, Zerlotti Mercadante, M. E., Sacchi, Paola, Rasero, Roberto, and de Albuquerque, L. G.
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QTL ,MUC1 ,polymorphism ,zebu - Published
- 2010
50. Associacoes entre o polimorfismo no gene MUC1 e caracteristicas de crescimento e carcaca em bovinos Nelore
- Author
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de Souza, F. R. P., Maione, Sandra, Zerlotti Mercadante, M. E., Sacchi, Paola, Rasero, Roberto, and de Albuquerque, L. G.
- Subjects
QTL ,MUC1 ,polymorphism ,zebu - Published
- 2010
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