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202. The PsychENCODE project

Author

Akbarian, Schahram, primary, Liu, Chunyu, additional, Knowles, James A, additional, Vaccarino, Flora M, additional, Farnham, Peggy J, additional, Crawford, Gregory E, additional, Jaffe, Andrew E, additional, Pinto, Dalila, additional, Dracheva, Stella, additional, Geschwind, Daniel H, additional, Mill, Jonathan, additional, Nairn, Angus C, additional, Abyzov, Alexej, additional, Pochareddy, Sirisha, additional, Prabhakar, Shyam, additional, Weissman, Sherman, additional, Sullivan, Patrick F, additional, State, Matthew W, additional, Weng, Zhiping, additional, Peters, Mette A, additional, White, Kevin P, additional, Gerstein, Mark B, additional, Amiri, Anahita, additional, Armoskus, Chris, additional, Ashley-Koch, Allison E, additional, Bae, Taejeong, additional, Beckel-Mitchener, Andrea, additional, Berman, Benjamin P, additional, Coetzee, Gerhard A, additional, Coppola, Gianfilippo, additional, Francoeur, Nancy, additional, Fromer, Menachem, additional, Gao, Robert, additional, Grennan, Kay, additional, Herstein, Jennifer, additional, Kavanagh, David H, additional, Ivanov, Nikolay A, additional, Jiang, Yan, additional, Kitchen, Robert R, additional, Kozlenkov, Alexey, additional, Kundakovic, Marija, additional, Li, Mingfeng, additional, Li, Zhen, additional, Liu, Shuang, additional, Mangravite, Lara M, additional, Mattei, Eugenio, additional, Markenscoff-Papadimitriou, Eirene, additional, Navarro, Fábio C P, additional, North, Nicole, additional, Omberg, Larsson, additional, Panchision, David, additional, Parikshak, Neelroop, additional, Poschmann, Jeremie, additional, Price, Amanda J, additional, Purcaro, Michael, additional, Reddy, Timothy E, additional, Roussos, Panos, additional, Schreiner, Shannon, additional, Scuderi, Soraya, additional, Sebra, Robert, additional, Shibata, Mikihito, additional, Shieh, Annie W, additional, Skarica, Mario, additional, Sun, Wenjie, additional, Swarup, Vivek, additional, Thomas, Amber, additional, Tsuji, Junko, additional, van Bakel, Harm, additional, Wang, Daifeng, additional, Wang, Yongjun, additional, Wang, Kai, additional, Werling, Donna M, additional, Willsey, A Jeremy, additional, Witt, Heather, additional, Won, Hyejung, additional, Wong, Chloe C Y, additional, Wray, Gregory A, additional, Wu, Emily Y, additional, Xu, Xuming, additional, Yao, Lijing, additional, Senthil, Geetha, additional, Lehner, Thomas, additional, Sklar, Pamela, additional, and Sestan, Nenad, additional

Published
2015
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203. The Molecular Taxonomy of Primary Prostate Cancer

Author

Abeshouse, Adam, primary, Ahn, Jaeil, additional, Akbani, Rehan, additional, Ally, Adrian, additional, Amin, Samirkumar, additional, Andry, Christopher D., additional, Annala, Matti, additional, Aprikian, Armen, additional, Armenia, Joshua, additional, Arora, Arshi, additional, Auman, J. Todd, additional, Balasundaram, Miruna, additional, Balu, Saianand, additional, Barbieri, Christopher E., additional, Bauer, Thomas, additional, Benz, Christopher C., additional, Bergeron, Alain, additional, Beroukhim, Rameen, additional, Berrios, Mario, additional, Bivol, Adrian, additional, Bodenheimer, Tom, additional, Boice, Lori, additional, Bootwalla, Moiz S., additional, Borges dos Reis, Rodolfo, additional, Boutros, Paul C., additional, Bowen, Jay, additional, Bowlby, Reanne, additional, Boyd, Jeffrey, additional, Bradley, Robert K., additional, Breggia, Anne, additional, Brimo, Fadi, additional, Bristow, Christopher A., additional, Brooks, Denise, additional, Broom, Bradley M., additional, Bryce, Alan H., additional, Bubley, Glenn, additional, Burks, Eric, additional, Butterfield, Yaron S.N., additional, Button, Michael, additional, Canes, David, additional, Carlotti, Carlos G., additional, Carlsen, Rebecca, additional, Carmel, Michel, additional, Carroll, Peter R., additional, Carter, Scott L., additional, Cartun, Richard, additional, Carver, Brett S., additional, Chan, June M., additional, Chang, Matthew T., additional, Chen, Yu, additional, Cherniack, Andrew D., additional, Chevalier, Simone, additional, Chin, Lynda, additional, Cho, Juok, additional, Chu, Andy, additional, Chuah, Eric, additional, Chudamani, Sudha, additional, Cibulskis, Kristian, additional, Ciriello, Giovanni, additional, Clarke, Amanda, additional, Cooperberg, Matthew R., additional, Corcoran, Niall M., additional, Costello, Anthony J., additional, Cowan, Janet, additional, Crain, Daniel, additional, Curley, Erin, additional, David, Kerstin, additional, Demchok, John A., additional, Demichelis, Francesca, additional, Dhalla, Noreen, additional, Dhir, Rajiv, additional, Doueik, Alexandre, additional, Drake, Bettina, additional, Dvinge, Heidi, additional, Dyakova, Natalya, additional, Felau, Ina, additional, Ferguson, Martin L., additional, Frazer, Scott, additional, Freedland, Stephen, additional, Fu, Yao, additional, Gabriel, Stacey B., additional, Gao, Jianjiong, additional, Gardner, Johanna, additional, Gastier-Foster, Julie M., additional, Gehlenborg, Nils, additional, Gerken, Mark, additional, Gerstein, Mark B., additional, Getz, Gad, additional, Godwin, Andrew K., additional, Gopalan, Anuradha, additional, Graefen, Markus, additional, Graim, Kiley, additional, Gribbin, Thomas, additional, Guin, Ranabir, additional, Gupta, Manaswi, additional, Hadjipanayis, Angela, additional, Haider, Syed, additional, Hamel, Lucie, additional, Hayes, D. Neil, additional, Heiman, David I., additional, Hess, Julian, additional, Hoadley, Katherine A., additional, Holbrook, Andrea H., additional, Holt, Robert A., additional, Holway, Antonia, additional, Hovens, Christopher M., additional, Hoyle, Alan P., additional, Huang, Mei, additional, Hutter, Carolyn M., additional, Ittmann, Michael, additional, Iype, Lisa, additional, Jefferys, Stuart R., additional, Jones, Corbin D., additional, Jones, Steven J.M., additional, Juhl, Hartmut, additional, Kahles, Andre, additional, Kane, Christopher J., additional, Kasaian, Katayoon, additional, Kerger, Michael, additional, Khurana, Ekta, additional, Kim, Jaegil, additional, Klein, Robert J., additional, Kucherlapati, Raju, additional, Lacombe, Louis, additional, Ladanyi, Marc, additional, Lai, Phillip H., additional, Laird, Peter W., additional, Lander, Eric S., additional, Latour, Mathieu, additional, Lawrence, Michael S., additional, Lau, Kevin, additional, LeBien, Tucker, additional, Lee, Darlene, additional, Lee, Semin, additional, Lehmann, Kjong-Van, additional, Leraas, Kristen M., additional, Leshchiner, Ignaty, additional, Leung, Robert, additional, Libertino, John A., additional, Lichtenberg, Tara M., additional, Lin, Pei, additional, Linehan, W. Marston, additional, Ling, Shiyun, additional, Lippman, Scott M., additional, Liu, Jia, additional, Liu, Wenbin, additional, Lochovsky, Lucas, additional, Loda, Massimo, additional, Logothetis, Christopher, additional, Lolla, Laxmi, additional, Longacre, Teri, additional, Lu, Yiling, additional, Luo, Jianhua, additional, Ma, Yussanne, additional, Mahadeshwar, Harshad S., additional, Mallery, David, additional, Mariamidze, Armaz, additional, Marra, Marco A., additional, Mayo, Michael, additional, McCall, Shannon, additional, McKercher, Ginette, additional, Meng, Shaowu, additional, Mes-Masson, Anne-Marie, additional, Merino, Maria J., additional, Meyerson, Matthew, additional, Mieczkowski, Piotr A., additional, Mills, Gordon B., additional, Shaw, Kenna R. Mills, additional, Minner, Sarah, additional, Moinzadeh, Alireza, additional, Moore, Richard A., additional, Morris, Scott, additional, Morrison, Carl, additional, Mose, Lisle E., additional, Mungall, Andrew J., additional, Murray, Bradley A., additional, Myers, Jerome B., additional, Naresh, Rashi, additional, Nelson, Joel, additional, Nelson, Mark A., additional, Nelson, Peter S., additional, Newton, Yulia, additional, Noble, Michael S., additional, Noushmehr, Houtan, additional, Nykter, Matti, additional, Pantazi, Angeliki, additional, Parfenov, Michael, additional, Park, Peter J., additional, Parker, Joel S., additional, Paulauskis, Joseph, additional, Penny, Robert, additional, Perou, Charles M., additional, Piché, Alain, additional, Pihl, Todd, additional, Pinto, Peter A., additional, Prandi, Davide, additional, Protopopov, Alexei, additional, Ramirez, Nilsa C., additional, Rao, Arvind, additional, Rathmell, W. Kimryn, additional, Rätsch, Gunnar, additional, Ren, Xiaojia, additional, Reuter, Victor E., additional, Reynolds, Sheila M., additional, Rhie, Suhn K., additional, Rieger-Christ, Kimberly, additional, Roach, Jeffrey, additional, Robertson, A. Gordon, additional, Robinson, Brian, additional, Rubin, Mark A., additional, Saad, Fred, additional, Sadeghi, Sara, additional, Saksena, Gordon, additional, Saller, Charles, additional, Salner, Andrew, additional, Sanchez-Vega, Francisco, additional, Sander, Chris, additional, Sandusky, George, additional, Sauter, Guido, additional, Sboner, Andrea, additional, Scardino, Peter T., additional, Scarlata, Eleonora, additional, Schein, Jacqueline E., additional, Schlomm, Thorsten, additional, Schmidt, Laura S., additional, Schultz, Nikolaus, additional, Schumacher, Steven E., additional, Seidman, Jonathan, additional, Neder, Luciano, additional, Seth, Sahil, additional, Sharp, Alexis, additional, Shelton, Candace, additional, Shelton, Troy, additional, Shen, Hui, additional, Shen, Ronglai, additional, Sherman, Mark, additional, Sheth, Margi, additional, Shi, Yan, additional, Shih, Juliann, additional, Shmulevich, Ilya, additional, Simko, Jeffry, additional, Simon, Ronald, additional, Simons, Janae V., additional, Sipahimalani, Payal, additional, Skelly, Tara, additional, Sofia, Heidi J., additional, Soloway, Matthew G., additional, Song, Xingzhi, additional, Sorcini, Andrea, additional, Sougnez, Carrie, additional, Stepa, Serghei, additional, Stewart, Chip, additional, Stewart, John, additional, Stuart, Joshua M., additional, Sullivan, Travis B., additional, Sun, Charlie, additional, Sun, Huandong, additional, Tam, Angela, additional, Tan, Donghui, additional, Tang, Jiabin, additional, Tarnuzzer, Roy, additional, Tarvin, Katherine, additional, Taylor, Barry S., additional, Teebagy, Patrick, additional, Tenggara, Imelda, additional, Têtu, Bernard, additional, Tewari, Ashutosh, additional, Thiessen, Nina, additional, Thompson, Timothy, additional, Thorne, Leigh B., additional, Tirapelli, Daniela P., additional, Tomlins, Scott A., additional, Trevisan, Felipe Amstalden, additional, Troncoso, Patricia, additional, True, Lawrence D., additional, Tsourlakis, Maria Christina, additional, Tyekucheva, Svitlana, additional, Van Allen, Eliezer, additional, Van Den Berg, David J., additional, Veluvolu, Umadevi, additional, Verhaak, Roel, additional, Vocke, Cathy D., additional, Voet, Doug, additional, Wan, Yunhu, additional, Wang, Qingguo, additional, Wang, Wenyi, additional, Wang, Zhining, additional, Weinhold, Nils, additional, Weinstein, John N., additional, Weisenberger, Daniel J., additional, Wilkerson, Matthew D., additional, Wise, Lisa, additional, Witte, John, additional, Wu, Chia-Chin, additional, Wu, Junyuan, additional, Wu, Ye, additional, Xu, Andrew W., additional, Yadav, Shalini S., additional, Yang, Liming, additional, Yang, Lixing, additional, Yau, Christina, additional, Ye, Huihui, additional, Yena, Peggy, additional, Zeng, Thomas, additional, Zenklusen, Jean C., additional, Zhang, Hailei, additional, Zhang, Jianhua, additional, Zhang, Jiashan, additional, Zhang, Wei, additional, Zhong, Yi, additional, Zhu, Kelsey, additional, and Zmuda, Erik, additional

Published
2015
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205. An ensemble approach to accurately detect somatic mutations using SomaticSeq

Author

Fang, Li Tai, primary, Afshar, Pegah Tootoonchi, additional, Chhibber, Aparna, additional, Mohiyuddin, Marghoob, additional, Fan, Yu, additional, Mu, John C., additional, Gibeling, Greg, additional, Barr, Sharon, additional, Asadi, Narges Bani, additional, Gerstein, Mark B., additional, Koboldt, Daniel C., additional, Wang, Wenyi, additional, Wong, Wing H., additional, and Lam, Hugo Y.K., additional

Published
2015
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206. Erratum: Analysis of deletion breakpoints from 1,092 humans reveals details of mutation mechanisms

Author

Abyzov, Alexej, primary, Li, Shantao, additional, Kim, Daniel Rhee, additional, Mohiyuddin, Marghoob, additional, Stütz, Adrian M., additional, Parrish, Nicholas F., additional, Mu, Xinmeng Jasmine, additional, Clark, Wyatt, additional, Chen, Ken, additional, Hurles, Matthew, additional, Korbel, Jan O., additional, Lam, Hugo Y. K., additional, Lee, Charles, additional, and Gerstein, Mark B., additional

Published
2015
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208. Analysis of deletion breakpoints from 1,092 humans reveals details of mutation mechanisms

Author

Abyzov, Alexej, primary, Li, Shantao, additional, Kim, Daniel Rhee, additional, Mohiyuddin, Marghoob, additional, Stütz, Adrian M., additional, Parrish, Nicholas F., additional, Mu, Xinmeng Jasmine, additional, Clark, Wyatt, additional, Chen, Ken, additional, Hurles, Matthew, additional, Korbel, Jan O., additional, Lam, Hugo Y. K., additional, Lee, Charles, additional, and Gerstein, Mark B., additional

Published
2015
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211. Getting Started in Text Mining: Part Two

Author

Rzhetsky, Andrey, Seringhaus, Michael, and Gerstein, Mark B.

Abstract

We are, in a sense, drowning in information. Today, it is unusual for scientists even to read a journal cover to cover—much less to personally parse all information pertinent to even a narrow research area. Increasingly complex content, large digital supplements, and a staggering volume of publications are now threatening old-fashioned scientific reading with extinction. But by using computers to sift through and scour published articles, the nascent technology of text mining promises to automate the rote information-gathering stage—hopefully leaving to human minds the more challenging (and rewarding) activity of higher thinking.

Published
2009

212. Comparing Classical Pathways and Modern Networks: Towards the Development of an Edge Ontology

Author

Lu, Long J., Sboner, Andrea, Huang, Yuanpeng J., Lu, Hao Xin, Gianoulis, Tara A., Yip, Kevin Y., Kim, Philip M., Montelione, Gaetano T., and Gerstein, Mark B.

Subjects
Molecular Networks (q-bio.MN), FOS: Biological sciences, Quantitative Biology - Molecular Networks
Abstract

Pathways are integral to systems biology. Their classical representation has proven useful but is inconsistent in the meaning assigned to each arrow (or edge) and inadvertently implies the isolation of one pathway from another. Conversely, modern high-throughput experiments give rise to standardized networks facilitating topological calculations. Combining these perspectives, we can embed classical pathways within large-scale networks and thus demonstrate the crosstalk between them. As more diverse types of high-throughput data become available, we can effectively merge both perspectives, embedding pathways simultaneously in multiple networks. However, the original problem still remains - the current edge representation is inadequate to accurately convey all the information in pathways. Therefore, we suggest that a standardized, well-defined, edge ontology is necessary and propose a prototype here, as a starting point for reaching this goal., Comment: 30 pages including 5 figures and supplemental material

Published
2007
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213. Copy Number Variants and Segmental Duplications Show Different Formation Signatures

Author

Kim, Philip M., Korbel, Jan O., Chen, Xueying, and Gerstein, Mark B.

Subjects
Genomics (q-bio.GN), FOS: Biological sciences, Quantitative Biology - Genomics, Quantitative Biology - Quantitative Methods, Quantitative Methods (q-bio.QM)
Abstract

In addition to variation in terms of single nucleotide polymorphisms (SNPs), whole regions ranging from several kilobases up to a megabase in length differ in copy number among individuals. These differences are referred to as Copy Number Variants (CNVs) and extensive mapping of these is underway. Recent studies have highlighted their great prevalence in the human genome. Segmental Duplications (SDs) are long (>1kb) stretches of duplicated DNA with high sequence identity. First, we analyzed the co-localization of SDs and find that SDs are significantly co-localized with each other, resulting in a power-law distribution, which suggests a preferential attachment mechanism, i.e. existing SDs are likely to be involved in creating new ones nearby. Second, we look at the relationship of CNVs/SDs with various types of repeats. We we find that the previously recognized association of SDs with Alu elements is significantly stronger for older SDs and is sharply decreasing for younger ones. While it might be expected that the patterns should be similar for SDs and CNVs, we find, surprisingly, no association of CNVs with Alu elements. This trend is consistent with the decreasing correlation between Alu elements and younger SDs, the activity of Alu elements has been decreasing and by now it they seem no longer active. Furthermore, we find a striking association of SDs with processed pseudogenes suggesting that they may also have mediated SD formation. Moreover, find strong association with microsatellites for both SDs and CNVs that suggests a role for satellites in the formation of both., 13 pages

Published
2007
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214. Gaining comprehensive biological insight into the transcriptome by performing a broad-spectrum RNA-seq analysis.

Author

Ebrahim Sahraeian, Sayed Mohammad, Mohiyuddin, Marghoob, Sebra, Robert, Tilgner, Hagen, Afshar, Pegah T., Kin Fai Au, Asadi, Narges Bani, Gerstein, Mark B., Wing Hung Wong, Snyder, Michael P., Schadt, Eric, and Lam, Hugo Y.K.

Abstract

RNA-sequencing (RNA-seq) is an essential technique for transcriptome studies, hundreds of analysis tools have been developed since it was debuted. Although recent efforts have attempted to assess the latest available tools, they have not evaluated the analysis workflows comprehensively to unleash the power within RNA-seq. Here we conduct an extensive study analysing a broad spectrum of RNA-seq workflows. Surpassing the expression analysis scope, our work also includes assessment of RNA variant-calling, RNA editing and RNA fusion detection techniques. Specifically, we examine both short- and long-read RNA-seq technologies, 39 analysis tools resulting in ~120 combinations, and ~490 analyses involving 15 samples with a variety of germline, cancer and stem cell data sets. We report the performance and propose a comprehensive RNA-seq analysis protocol, named RNACocktail, along with a computational pipeline achieving high accuracy. Validation on different samples reveals that our proposed protocol could help researchers extract more biologically relevant predictions by broad analysis of the transcriptome. [ABSTRACT FROM AUTHOR]

Published
2017
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215. Integration of extracellular RNA profiling data using metadata, biomedical ontologies and Linked Data technologies

Author

Subramanian, Sai Lakshmi, primary, Kitchen, Robert R., additional, Alexander, Roger, additional, Carter, Bob S., additional, Cheung, Kei-Hoi, additional, Laurent, Louise C., additional, Pico, Alexander, additional, Roberts, Lewis R., additional, Roth, Matthew E., additional, Rozowsky, Joel S., additional, Su, Andrew I., additional, Gerstein, Mark B., additional, and Milosavljevic, Aleksandar, additional

Published
2015
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216. Transcriptional landscape of the prenatal human brain.

Author

Miller, Jeremy A, Miller, Jeremy A, Ding, Song-Lin, Sunkin, Susan M, Smith, Kimberly A, Ng, Lydia, Szafer, Aaron, Ebbert, Amanda, Riley, Zackery L, Royall, Joshua J, Aiona, Kaylynn, Arnold, James M, Bennet, Crissa, Bertagnolli, Darren, Brouner, Krissy, Butler, Stephanie, Caldejon, Shiella, Carey, Anita, Cuhaciyan, Christine, Dalley, Rachel A, Dee, Nick, Dolbeare, Tim A, Facer, Benjamin AC, Feng, David, Fliss, Tim P, Gee, Garrett, Goldy, Jeff, Gourley, Lindsey, Gregor, Benjamin W, Gu, Guangyu, Howard, Robert E, Jochim, Jayson M, Kuan, Chihchau L, Lau, Christopher, Lee, Chang-Kyu, Lee, Felix, Lemon, Tracy A, Lesnar, Phil, McMurray, Bergen, Mastan, Naveed, Mosqueda, Nerick, Naluai-Cecchini, Theresa, Ngo, Nhan-Kiet, Nyhus, Julie, Oldre, Aaron, Olson, Eric, Parente, Jody, Parker, Patrick D, Parry, Sheana E, Stevens, Allison, Pletikos, Mihovil, Reding, Melissa, Roll, Kate, Sandman, David, Sarreal, Melaine, Shapouri, Sheila, Shapovalova, Nadiya V, Shen, Elaine H, Sjoquist, Nathan, Slaughterbeck, Clifford R, Smith, Michael, Sodt, Andy J, Williams, Derric, Zöllei, Lilla, Fischl, Bruce, Gerstein, Mark B, Geschwind, Daniel H, Glass, Ian A, Hawrylycz, Michael J, Hevner, Robert F, Huang, Hao, Jones, Allan R, Knowles, James A, Levitt, Pat, Phillips, John W, Sestan, Nenad, Wohnoutka, Paul, Dang, Chinh, Bernard, Amy, Hohmann, John G, Lein, Ed S, Miller, Jeremy A, Miller, Jeremy A, Ding, Song-Lin, Sunkin, Susan M, Smith, Kimberly A, Ng, Lydia, Szafer, Aaron, Ebbert, Amanda, Riley, Zackery L, Royall, Joshua J, Aiona, Kaylynn, Arnold, James M, Bennet, Crissa, Bertagnolli, Darren, Brouner, Krissy, Butler, Stephanie, Caldejon, Shiella, Carey, Anita, Cuhaciyan, Christine, Dalley, Rachel A, Dee, Nick, Dolbeare, Tim A, Facer, Benjamin AC, Feng, David, Fliss, Tim P, Gee, Garrett, Goldy, Jeff, Gourley, Lindsey, Gregor, Benjamin W, Gu, Guangyu, Howard, Robert E, Jochim, Jayson M, Kuan, Chihchau L, Lau, Christopher, Lee, Chang-Kyu, Lee, Felix, Lemon, Tracy A, Lesnar, Phil, McMurray, Bergen, Mastan, Naveed, Mosqueda, Nerick, Naluai-Cecchini, Theresa, Ngo, Nhan-Kiet, Nyhus, Julie, Oldre, Aaron, Olson, Eric, Parente, Jody, Parker, Patrick D, Parry, Sheana E, Stevens, Allison, Pletikos, Mihovil, Reding, Melissa, Roll, Kate, Sandman, David, Sarreal, Melaine, Shapouri, Sheila, Shapovalova, Nadiya V, Shen, Elaine H, Sjoquist, Nathan, Slaughterbeck, Clifford R, Smith, Michael, Sodt, Andy J, Williams, Derric, Zöllei, Lilla, Fischl, Bruce, Gerstein, Mark B, Geschwind, Daniel H, Glass, Ian A, Hawrylycz, Michael J, Hevner, Robert F, Huang, Hao, Jones, Allan R, Knowles, James A, Levitt, Pat, Phillips, John W, Sestan, Nenad, Wohnoutka, Paul, Dang, Chinh, Bernard, Amy, Hohmann, John G, and Lein, Ed S

Abstract

The anatomical and functional architecture of the human brain is mainly determined by prenatal transcriptional processes. We describe an anatomically comprehensive atlas of the mid-gestational human brain, including de novo reference atlases, in situ hybridization, ultra-high-resolution magnetic resonance imaging (MRI) and microarray analysis on highly discrete laser-microdissected brain regions. In developing cerebral cortex, transcriptional differences are found between different proliferative and post-mitotic layers, wherein laminar signatures reflect cellular composition and developmental processes. Cytoarchitectural differences between human and mouse have molecular correlates, including species differences in gene expression in subplate, although surprisingly we find minimal differences between the inner and outer subventricular zones even though the outer zone is expanded in humans. Both germinal and post-mitotic cortical layers exhibit fronto-temporal gradients, with particular enrichment in the frontal lobe. Finally, many neurodevelopmental disorder and human-evolution-related genes show patterned expression, potentially underlying unique features of human cortical formation. These data provide a rich, freely-accessible resource for understanding human brain development.

Published
2014

217. Defining functional DNA elements in the human genome

Author

Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science, Kellis, Manolis, Kundaje, Anshul, Ward, Lucas D., Wold, Barbara, Snyder, Michael P., Bernstein, Bradley E., Marinov, Georgi K., Birney, Ewan, Crawford, Gregory E., Dekker, Job, Dunham, Ian, Elnitski, Laura L., Farnham, Peggy J., Feingold, Elise A., Gerstein, Mark B., Giddings, Morgan C., Gilbert, David M., Gingeras, Thomas R., Green, Eric D., Guigo, Roderic, Hubbard, Tim, Kent, Jim, Lieb, Jason D., Myers, Richard M., Pazin, Michael J., Ren, Bing, Stamatoyannopoulos, John A., Weng, Zhiping, White, Kevin P., Hardison, Ross C., Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science, Kellis, Manolis, Kundaje, Anshul, Ward, Lucas D., Wold, Barbara, Snyder, Michael P., Bernstein, Bradley E., Marinov, Georgi K., Birney, Ewan, Crawford, Gregory E., Dekker, Job, Dunham, Ian, Elnitski, Laura L., Farnham, Peggy J., Feingold, Elise A., Gerstein, Mark B., Giddings, Morgan C., Gilbert, David M., Gingeras, Thomas R., Green, Eric D., Guigo, Roderic, Hubbard, Tim, Kent, Jim, Lieb, Jason D., Myers, Richard M., Pazin, Michael J., Ren, Bing, Stamatoyannopoulos, John A., Weng, Zhiping, White, Kevin P., and Hardison, Ross C.

Abstract

With the completion of the human genome sequence, attention turned to identifying and annotating its functional DNA elements. As a complement to genetic and comparative genomics approaches, the Encyclopedia of DNA Elements Project was launched to contribute maps of RNA transcripts, transcriptional regulator binding sites, and chromatin states in many cell types. The resulting genome-wide data reveal sites of biochemical activity with high positional resolution and cell type specificity that facilitate studies of gene regulation and interpretation of noncoding variants associated with human disease. However, the biochemically active regions cover a much larger fraction of the genome than do evolutionarily conserved regions, raising the question of whether nonconserved but biochemically active regions are truly functional. Here, we review the strengths and limitations of biochemical, evolutionary, and genetic approaches for defining functional DNA segments, potential sources for the observed differences in estimated genomic coverage, and the biological implications of these discrepancies. We also analyze the relationship between signal intensity, genomic coverage, and evolutionary conservation. Our results reinforce the principle that each approach provides complementary information and that we need to use combinations of all three to elucidate genome function in human biology and disease.

Published
2014

222. Comparative analysis of the transcriptome across distant species

Author

Gerstein, Mark B., primary, Rozowsky, Joel, additional, Yan, Koon-Kiu, additional, Wang, Daifeng, additional, Cheng, Chao, additional, Brown, James B., additional, Davis, Carrie A., additional, Hillier, LaDeana, additional, Sisu, Cristina, additional, Li, Jingyi Jessica, additional, Pei, Baikang, additional, Harmanci, Arif O., additional, Duff, Michael O., additional, Djebali, Sarah, additional, Alexander, Roger P., additional, Alver, Burak H., additional, Auerbach, Raymond, additional, Bell, Kimberly, additional, Bickel, Peter J., additional, Boeck, Max E., additional, Boley, Nathan P., additional, Booth, Benjamin W., additional, Cherbas, Lucy, additional, Cherbas, Peter, additional, Di, Chao, additional, Dobin, Alex, additional, Drenkow, Jorg, additional, Ewing, Brent, additional, Fang, Gang, additional, Fastuca, Megan, additional, Feingold, Elise A., additional, Frankish, Adam, additional, Gao, Guanjun, additional, Good, Peter J., additional, Guigó, Roderic, additional, Hammonds, Ann, additional, Harrow, Jen, additional, Hoskins, Roger A., additional, Howald, Cédric, additional, Hu, Long, additional, Huang, Haiyan, additional, Hubbard, Tim J. P., additional, Huynh, Chau, additional, Jha, Sonali, additional, Kasper, Dionna, additional, Kato, Masaomi, additional, Kaufman, Thomas C., additional, Kitchen, Robert R., additional, Ladewig, Erik, additional, Lagarde, Julien, additional, Lai, Eric, additional, Leng, Jing, additional, Lu, Zhi, additional, MacCoss, Michael, additional, May, Gemma, additional, McWhirter, Rebecca, additional, Merrihew, Gennifer, additional, Miller, David M., additional, Mortazavi, Ali, additional, Murad, Rabi, additional, Oliver, Brian, additional, Olson, Sara, additional, Park, Peter J., additional, Pazin, Michael J., additional, Perrimon, Norbert, additional, Pervouchine, Dmitri, additional, Reinke, Valerie, additional, Reymond, Alexandre, additional, Robinson, Garrett, additional, Samsonova, Anastasia, additional, Saunders, Gary I., additional, Schlesinger, Felix, additional, Sethi, Anurag, additional, Slack, Frank J., additional, Spencer, William C., additional, Stoiber, Marcus H., additional, Strasbourger, Pnina, additional, Tanzer, Andrea, additional, Thompson, Owen A., additional, Wan, Kenneth H., additional, Wang, Guilin, additional, Wang, Huaien, additional, Watkins, Kathie L., additional, Wen, Jiayu, additional, Wen, Kejia, additional, Xue, Chenghai, additional, Yang, Li, additional, Yip, Kevin, additional, Zaleski, Chris, additional, Zhang, Yan, additional, Zheng, Henry, additional, Brenner, Steven E., additional, Graveley, Brenton R., additional, Celniker, Susan E., additional, Gingeras, Thomas R., additional, and Waterston, Robert, additional

Published
2014
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223. Comparative analysis of pseudogenes across three phyla

Author

Sisu, Cristina, primary, Pei, Baikang, additional, Leng, Jing, additional, Frankish, Adam, additional, Zhang, Yan, additional, Balasubramanian, Suganthi, additional, Harte, Rachel, additional, Wang, Daifeng, additional, Rutenberg-Schoenberg, Michael, additional, Clark, Wyatt, additional, Diekhans, Mark, additional, Rozowsky, Joel, additional, Hubbard, Tim, additional, Harrow, Jennifer, additional, and Gerstein, Mark B., additional

Published
2014
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224. Transcriptional landscape of the prenatal human brain

Author

Miller, Jeremy A., primary, Ding, Song-Lin, additional, Sunkin, Susan M., additional, Smith, Kimberly A., additional, Ng, Lydia, additional, Szafer, Aaron, additional, Ebbert, Amanda, additional, Riley, Zackery L., additional, Royall, Joshua J., additional, Aiona, Kaylynn, additional, Arnold, James M., additional, Bennet, Crissa, additional, Bertagnolli, Darren, additional, Brouner, Krissy, additional, Butler, Stephanie, additional, Caldejon, Shiella, additional, Carey, Anita, additional, Cuhaciyan, Christine, additional, Dalley, Rachel A., additional, Dee, Nick, additional, Dolbeare, Tim A., additional, Facer, Benjamin A. C., additional, Feng, David, additional, Fliss, Tim P., additional, Gee, Garrett, additional, Goldy, Jeff, additional, Gourley, Lindsey, additional, Gregor, Benjamin W., additional, Gu, Guangyu, additional, Howard, Robert E., additional, Jochim, Jayson M., additional, Kuan, Chihchau L., additional, Lau, Christopher, additional, Lee, Chang-Kyu, additional, Lee, Felix, additional, Lemon, Tracy A., additional, Lesnar, Phil, additional, McMurray, Bergen, additional, Mastan, Naveed, additional, Mosqueda, Nerick, additional, Naluai-Cecchini, Theresa, additional, Ngo, Nhan-Kiet, additional, Nyhus, Julie, additional, Oldre, Aaron, additional, Olson, Eric, additional, Parente, Jody, additional, Parker, Patrick D., additional, Parry, Sheana E., additional, Stevens, Allison, additional, Pletikos, Mihovil, additional, Reding, Melissa, additional, Roll, Kate, additional, Sandman, David, additional, Sarreal, Melaine, additional, Shapouri, Sheila, additional, Shapovalova, Nadiya V., additional, Shen, Elaine H., additional, Sjoquist, Nathan, additional, Slaughterbeck, Clifford R., additional, Smith, Michael, additional, Sodt, Andy J., additional, Williams, Derric, additional, Zöllei, Lilla, additional, Fischl, Bruce, additional, Gerstein, Mark B., additional, Geschwind, Daniel H., additional, Glass, Ian A., additional, Hawrylycz, Michael J., additional, Hevner, Robert F., additional, Huang, Hao, additional, Jones, Allan R., additional, Knowles, James A., additional, Levitt, Pat, additional, Phillips, John W., additional, Šestan, Nenad, additional, Wohnoutka, Paul, additional, Dang, Chinh, additional, Bernard, Amy, additional, Hohmann, John G., additional, and Lein, Ed S., additional

Published
2014
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225. The GENCODE human gene set

Author

Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science, Kellis, Manolis, Lin, M., Searle, S., Frankish, A., Bignell, A., Aken, B., Derrien, Thomas, Diekhans, M., Harte, R., Howald, C., Kokocinski, F., Tress, M., Van Baren, M., Barnes, I., Hunt, T., Carvalho-Silva, D., Davidson, C., Donaldson, S., Gilbert, J., Kay, M., Lloyd, D., Loveland, J., Mudge, J., Snow, C., Vamathevan, J., Wilming, L., Brent, M., Gerstein, Mark B., Guigo, Roderic, Reymond, A., Zadissa, A., Valencia, A., Harrow, J., Hubbard, T., Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science, Kellis, Manolis, Lin, M., Searle, S., Frankish, A., Bignell, A., Aken, B., Derrien, Thomas, Diekhans, M., Harte, R., Howald, C., Kokocinski, F., Tress, M., Van Baren, M., Barnes, I., Hunt, T., Carvalho-Silva, D., Davidson, C., Donaldson, S., Gilbert, J., Kay, M., Lloyd, D., Loveland, J., Mudge, J., Snow, C., Vamathevan, J., Wilming, L., Brent, M., Gerstein, Mark B., Guigo, Roderic, Reymond, A., Zadissa, A., Valencia, A., Harrow, J., and Hubbard, T.

Abstract

This article is part of the supplement: Beyond the Genome: The true gene count, human evolution and disease genomics, Boston, MA, USA. 11-13 October 2010., The GENCODE consortium is a sub group of the ENCODE consortium. Its aim is to provide complete annotation of genes in the human genome including protein-coding loci, non-coding loci and pseudogenes, based on experimental evidence. The final aim is for the HAVANA team to manually annotate the complete genome. This is a time-consuming process which will be completed over the course of the ENCODE project. Currently, to provide a set of annotation covering the complete genome, rather than just the regions that have been manually annotated, a merge of manual annotation from HAVANA with automatic annotation from the Ensembl automatically annotated gene set is created. This process also adds unique full-length CDS predictions from the Ensembl protein coding set into manually annotated genes, to provide the most complete up to date annotation of the genome possible. Also included in the set are short and long ncRNA genes predicted by the Ensembl prediction pipelines and a consensus set of pseudogene predictions agreed between Havana, Yale and UCSC. The CCDS set is also fully represented within the GENCODE set. The GENCODE set is the default annotation available in Ensembl and is also available in the UCSC genome browser. All the annotation is tagged as to whether it is produced by manual annotation alone, automatic annotation alone, or by both approaches. We are currently working to provide confidence levels for annotation, based on depth and type of evidence supporting it.

Published
2012

226. Unlocking the Secrets of the Genome

Author

Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science, Kellis, Manolis, Celniker, Susan E., Dillon, Laura A. L., Gerstein, Mark B., Gunsalus, Kristin C., Henikoff, Steven, Karpen, Gary H., Lai, Eric C., Lieb, Jason D., MacAlpine, David M., Micklem, Gos, Piano, Fabio, Snyder, Michael, Stein, Lincoln, White, Kevin P., Waterston, Robert H., Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science, Kellis, Manolis, Celniker, Susan E., Dillon, Laura A. L., Gerstein, Mark B., Gunsalus, Kristin C., Henikoff, Steven, Karpen, Gary H., Lai, Eric C., Lieb, Jason D., MacAlpine, David M., Micklem, Gos, Piano, Fabio, Snyder, Michael, Stein, Lincoln, White, Kevin P., and Waterston, Robert H.

Abstract

The primary objective of the Human Genome Project was to produce high-quality sequences not just for the human genome but also for those of the chief model organisms: Escherichia coli, yeast (Saccharomyces cerevisiae), worm (Caenorhabditis elegans), fly (Drosophila melanogaster) and mouse (Mus musculus). Free access to the resultant data has prompted much biological research, including development of a map of common human genetic variants (the International HapMap Project)1, expression profiling of healthy and diseased cells2 and in-depth studies of many individual genes. These genome sequences have enabled researchers to carry out genetic and functional genomic studies not previously possible, revealing new biological insights with broad relevance across the animal kingdom 3, 4.

Published
2012

227. Molecular sampling of prostate cancer: a dilemma for predicting disease progression

Author

Sboner, Andrea, Demichelis, Francesca, Calza, Stefano, Pawitan, Yudi, Setlur, Sunita R, Hoshida, Yujin, Perner, Sven, Adami, Hans-Olov, Fall, Katja, A Mucci, Lorelei, Kantoff, Philip W, Stampfer, Meir, Andersson, Swen-Olof, Varenhorst, Eberhard, Johansson, Jan-Erik, Gerstein, Mark B, Golub, Todd R, Rubin, Mark A, Andren, Ove, Sboner, Andrea, Demichelis, Francesca, Calza, Stefano, Pawitan, Yudi, Setlur, Sunita R, Hoshida, Yujin, Perner, Sven, Adami, Hans-Olov, Fall, Katja, A Mucci, Lorelei, Kantoff, Philip W, Stampfer, Meir, Andersson, Swen-Olof, Varenhorst, Eberhard, Johansson, Jan-Erik, Gerstein, Mark B, Golub, Todd R, Rubin, Mark A, and Andren, Ove

Abstract

Background: Current prostate cancer prognostic models are based on pre-treatment prostate specific antigen (PSA) levels, biopsy Gleason score, and clinical staging but in practice are inadequate to accurately predict disease progression. Hence, we sought to develop a molecular panel for prostate cancer progression by reasoning that molecular profiles might further improve current clinical models. Methods: We analyzed a Swedish Watchful Waiting cohort with up to 30 years of clinical follow up using a novel method for gene expression profiling. This cDNA-mediated annealing, selection, ligation, and extension (DASL) method enabled the use of formalin-fixed paraffin-embedded transurethral resection of prostate (TURP) samples taken at the time of the initial diagnosis. We determined the expression profiles of 6100 genes for 281 men divided in two extreme groups: men who died of prostate cancer and men who survived more than 10 years without metastases (lethals and indolents, respectively). Several statistical and machine learning models using clinical and molecular features were evaluated for their ability to distinguish lethal from indolent cases. Results: Surprisingly, none of the predictive models using molecular profiles significantly improved over models using clinical variables only. Additional computational analysis confirmed that molecular heterogeneity within both the lethal and indolent classes is widespread in prostate cancer as compared to other types of tumors. Conclusions: The determination of the molecularly dominant tumor nodule may be limited by sampling at time of initial diagnosis, may not be present at time of initial diagnosis, or may occur as the disease progresses making the development of molecular biomarkers for prostate cancer progression challenging., Original Publication:Andrea Sboner, Francesca Demichelis, Stefano Calza, Yudi Pawitan, Sunita R Setlur, Yujin Hoshida, Sven Perner, Hans-Olov Adami, Katja Fall, Lorelei A Mucci, Philip W Kantoff, Meir Stampfer, Swen-Olof Andersson, Eberhard Varenhorst, Jan-Erik Johansson, Mark B Gerstein, Todd R Golub, Mark A Rubin and Ove Andren, Molecular sampling of prostate cancer: a dilemma for predicting disease progression, 2010, BMC MEDICAL GENOMICS, (3), 8.http://dx.doi.org/10.1186/1755-8794-3-8Copyright: BioMed Centralhttp://www.biomedcentral.com

Published
2010
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228. Deciphering protein kinase specificity through large-scale analysis of yeast phosphorylation site motifs

Author

Mok, Janine, Kim, Philip M., Lam, Hugo Y. K., Piccirillo, Stacy, Zhou, Xiuqiong, Jeschke, Grace R., Sheridan, Douglas L., Parker, Sirlester A., Desai, Ved, Jwa, Miri, Cameroni, Elisabetta, Niu, Hengyao, Good, Matthew, Remenyi, Attila, Ma, Jia-Lin Nianhan, Sheu, Yi-Jun, Sassi, Holly E., Sopko, Richelle, Chan, Clarence S. M., De Virgilio, Claudio, Hollingsworth, Nancy M., Lim, Wendell A., Stern, David F., Stillman, Bruce, Andrews, Brenda J., Gerstein, Mark B., Snyder, Michael, Turk, Benjamin E., Mok, Janine, Kim, Philip M., Lam, Hugo Y. K., Piccirillo, Stacy, Zhou, Xiuqiong, Jeschke, Grace R., Sheridan, Douglas L., Parker, Sirlester A., Desai, Ved, Jwa, Miri, Cameroni, Elisabetta, Niu, Hengyao, Good, Matthew, Remenyi, Attila, Ma, Jia-Lin Nianhan, Sheu, Yi-Jun, Sassi, Holly E., Sopko, Richelle, Chan, Clarence S. M., De Virgilio, Claudio, Hollingsworth, Nancy M., Lim, Wendell A., Stern, David F., Stillman, Bruce, Andrews, Brenda J., Gerstein, Mark B., Snyder, Michael, and Turk, Benjamin E.

Abstract

Phosphorylation is a universal mechanism for regulating cell behavior in eukaryotes. Although protein kinases target short linear sequence motifs on their substrates, the rules for kinase substrate recognition are not completely understood. We used a rapid peptide screening approach to determine consensus phosphorylation site motifs targeted by 61 of the 122 kinases in Saccharomyces cerevisiae. By correlating these motifs with kinase primary sequence, we uncovered previously unappreciated rules for determining specificity within the kinase family, including a residue determining P–3 arginine specificity among members of the CMGC [CDK (cyclin-dependent kinase), MAPK (mitogen-activated protein kinase), GSK (glycogen synthase kinase), and CDK-like] group of kinases. Furthermore, computational scanning of the yeast proteome enabled the prediction of thousands of new kinase-substrate relationships. We experimentally verified several candidate substrates of the Prk1 family of kinases in vitro and in vivo and identified a protein substrate of the kinase Vhs1. Together, these results elucidate how kinase catalytic domains recognize their phosphorylation targets and suggest general avenues for the identification of previously unknown kinase substrates across eukaryotes.

Published
2010

229. Quantifying environmental adaptation of metabolic pathways in metagenomics

Author

Gianoulis, Tara A, Raes, Jeroen, Patel, Prianka V, Bjornson, Robert, Korbel, Jan O, Letunic, Ivica, Yamada, Takuji, Paccanaro, Alberto, Snyder, Michael, Bork, Peer, Gerstein, Mark B, Jensen, Lars Juhl, Gianoulis, Tara A, Raes, Jeroen, Patel, Prianka V, Bjornson, Robert, Korbel, Jan O, Letunic, Ivica, Yamada, Takuji, Paccanaro, Alberto, Snyder, Michael, Bork, Peer, Gerstein, Mark B, and Jensen, Lars Juhl

Abstract

Udgivelsesdato: 2009-Feb-3, Recently, approaches have been developed to sample the genetic content of heterogeneous environments (metagenomics). However, by what means these sequences link distinct environmental conditions with specific biological processes is not well understood. Thus, a major challenge is how the usage of particular pathways and subnetworks reflects the adaptation of microbial communities across environments and habitats-i.e., how network dynamics relates to environmental features. Previous research has treated environments as discrete, somewhat simplified classes (e.g., terrestrial vs. marine), and searched for obvious metabolic differences among them (i.e., treating the analysis as a typical classification problem). However, environmental differences result from combinations of many factors, which often vary only slightly. Therefore, we introduce an approach that employs correlation and regression to relate multiple, continuously varying factors defining an environment to the extent of particular microbial pathways present in a geographic site. Moreover, rather than looking only at individual correlations (one-to-one), we adapted canonical correlation analysis and related techniques to define an ensemble of weighted pathways that maximally covaries with a combination of environmental variables (many-to-many), which we term a metabolic footprint. Applied to available aquatic datasets, we identified footprints predictive of their environment that can potentially be used as biosensors. For example, we show a strong multivariate correlation between the energy-conversion strategies of a community and multiple environmental gradients (e.g., temperature). Moreover, we identified covariation in amino acid transport and cofactor synthesis, suggesting that limiting amounts of cofactor can (partially) explain increased import of amino acids in nutrient-limited conditions.

Published
2009

230. Mapping of transcription factor binding regions in mammalian cells by ChIP : comparison of array- and sequencing-based technologies.

Author

Euskirchen, Ghia M, Rozowsky, Joel S, Wei, Chia-Lin, Lee, Wah Heng, Zhang, Zhengdong D, Hartman, Stephen, Emanuelsson, Olof, Stolc, Viktor, Weissman, Sherman, Gerstein, Mark B, Ruan, Yijun, Snyder, Michael, Euskirchen, Ghia M, Rozowsky, Joel S, Wei, Chia-Lin, Lee, Wah Heng, Zhang, Zhengdong D, Hartman, Stephen, Emanuelsson, Olof, Stolc, Viktor, Weissman, Sherman, Gerstein, Mark B, Ruan, Yijun, and Snyder, Michael

Abstract

Recent progress in mapping transcription factor (TF) binding regions can largely be credited to chromatin immunoprecipitation (ChIP) technologies. We compared strategies for mapping TF binding regions in mammalian cells using two different ChIP schemes: ChIP with DNA microarray analysis (ChIP-chip) and ChIP with DNA sequencing (ChIP-PET). We first investigated parameters central to obtaining robust ChIP-chip data sets by analyzing STAT1 targets in the ENCODE regions of the human genome, and then compared ChIP-chip to ChIP-PET. We devised methods for scoring and comparing results among various tiling arrays and examined parameters such as DNA microarray format, oligonucleotide length, hybridization conditions, and the use of competitor Cot-1 DNA. The best performance was achieved with high-density oligonucleotide arrays, oligonucleotides >/=50 bases (b), the presence of competitor Cot-1 DNA and hybridizations conducted in microfluidics stations. When target identification was evaluated as a function of array number, 80%-86% of targets were identified with three or more arrays. Comparison of ChIP-chip with ChIP-PET revealed strong agreement for the highest ranked targets with less overlap for the low ranked targets. With advantages and disadvantages unique to each approach, we found that ChIP-chip and ChIP-PET are frequently complementary in their relative abilities to detect STAT1 targets for the lower ranked targets; each method detected validated targets that were missed by the other method. The most comprehensive list of STAT1 binding regions is obtained by merging results from ChIP-chip and ChIP-sequencing. Overall, this study provides information for robust identification, scoring, and validation of TF targets using ChIP-based technologies.

Published
2007
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231. What is a gene, post-ENCODE? : History and updated definition

Author

Gerstein, Mark B, Bruce, Can, Rozowsky, Joel S, Zheng, Deyou, Du, Jiang, Korbel, Jan O, Emanuelsson, Olof, Zhang, Zhengdong D, Weissman, Sherman, Snyder, Michael, Gerstein, Mark B, Bruce, Can, Rozowsky, Joel S, Zheng, Deyou, Du, Jiang, Korbel, Jan O, Emanuelsson, Olof, Zhang, Zhengdong D, Weissman, Sherman, and Snyder, Michael

Abstract

While sequencing of the human genome surprised us with how many protein-coding genes there are, it did not fundamentally change our perspective on what a gene is. In contrast, the complex patterns of dispersed regulation and pervasive transcription uncovered by the ENCODE project, together with non-genic conservation and the abundance of noncoding RNA genes, have challenged the notion of the gene. To illustrate this, we review the evolution of operational definitions of a gene over the past century--from the abstract elements of heredity of Mendel and Morgan to the present-day ORFs enumerated in the sequence databanks. We then summarize the current ENCODE findings and provide a computational metaphor for the complexity. Finally, we propose a tentative update to the definition of a gene: A gene is a union of genomic sequences encoding a coherent set of potentially overlapping functional products. Our definition side-steps the complexities of regulation and transcription by removing the former altogether from the definition and arguing that final, functional gene products (rather than intermediate transcripts) should be used to group together entities associated with a single gene. It also manifests how integral the concept of biological function is in defining genes., QC 20111206

Published
2007
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232. Extending gene ontology in the context of extracellular RNA and vesicle communication.

Author

Kei-Hoi Cheung, Alexander, Roger, Galas, David, Gerstein, Mark B., Rozowsky, Joel, Kitchen, Robert R., Lötvall, Jan, Patel, Tushar, Procaccini, Dena C., Quesenberry, Peter, Raffai, Robert L., Su, Andrew I., Théry, Clotilde, Vickers, Kasey, Wauben, Marca H. M., Laurent, Louise C., Samuel, Monisha, Anand, Sushma, Gangoda, Lahiru, and Hill, Andrew F.

Subjects
METADATA, GENE ontology, APOPTOTIC bodies
Abstract

Background: To address the lack of standard terminology to describe extracellular RNA (exRNA) data/metadata, we have launched an inter-community effort to extend the Gene Ontology (GO) with subcellular structure concepts relevant to the exRNA domain. By extending GO in this manner, the exRNA data/metadata will be more easily annotated and queried because it will be based on a shared set of terms and relationships relevant to extracellular research. Methods: By following a consensus-building process, we have worked with several academic societies/consortia, including ERCC, ISEV, and ASEMV, to identify and approve a set of exRNA and extracellular vesicle-related terms and relationships that have been incorporated into GO. In addition, we have initiated an ongoing process of extractions of gene product annotations associated with these terms from Vesiclepedia and ExoCarta, conversion of the extracted annotations to Gene Association File (GAF) format for batch submission to GO, and curation of the submitted annotations by the GO Consortium. As a use case, we have incorporated some of the GO terms into annotations of samples from the exRNA Atlas and implemented a faceted search interface based on such annotations. Results: We have added 7 new terms and modified 9 existing terms (along with their synonyms and relationships) to GO. Additionally, 18,695 unique coding gene products (mRNAs and proteins) and 963 unique non-coding gene products (ncRNAs) which are associated with the terms: "extracellular vesicle", "extracellular exosome", "apoptotic body", and "microvesicle" were extracted from ExoCarta and Vesiclepedia. These annotations are currently being processed for submission to GO. Conclusions: As an inter-community effort, we have made a substantial update to GO in the exRNA context. We have also demonstrated the utility of some of the new GO terms for sample annotation and metadata search. [ABSTRACT FROM AUTHOR]

Published
2016
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233. Extrapolating traditional DNA microarray statistics to tiling and protein microarray technologies

Author

Royce, Thomas E., Rozowsky, Joel S., Luscombe, Nicholas M., Emanuelsson, Olof, Yu, Haiyuan, Zhu, Xiaowei, Snyder, Michael, Gerstein, Mark B., Royce, Thomas E., Rozowsky, Joel S., Luscombe, Nicholas M., Emanuelsson, Olof, Yu, Haiyuan, Zhu, Xiaowei, Snyder, Michael, and Gerstein, Mark B.

Abstract

A credit to microarray technology is its broad application. Two experiments--the tiling microarray experiment and the protein microarray experiment--are exemplars of the versatility of the microarrays. With the technology's expanding list of uses, the corresponding bioinformatics must evolve in step. There currently exists a rich literature developing statistical techniques for analyzing traditional gene-centric DNA microarrays, so the first challenge in analyzing the advanced technologies is to identify which of the existing statistical protocols are relevant and where and when revised methods are needed. A second challenge is making these often very technical ideas accessible to the broader microarray community. The aim of this chapter is to present some of the most widely used statistical techniques for normalizing and scoring traditional microarray data and indicate their potential utility for analyzing the newer protein and tiling microarray experiments. In so doing, we will assume little or no prior training in statistics of the reader. Areas covered include background correction, intensity normalization, spatial normalization, and the testing of statistical significance., QC 20111207

Published
2006
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234. Epigenetic Repression of miR-31 Disrupts Androgen Receptor Homeostasis and Contributes to Prostate Cancer Progression

Author

Lin, Pei-Chun, primary, Chiu, Ya-Lin, additional, Banerjee, Samprit, additional, Park, Kyung, additional, Mosquera, Juan Miguel, additional, Giannopoulou, Eugenia, additional, Alves, Pedro, additional, Tewari, Ashutosh K., additional, Gerstein, Mark B., additional, Beltran, Himisha, additional, Melnick, Ari M., additional, Elemento, Olivier, additional, Demichelis, Francesca, additional, and Rubin, Mark A., additional

Published
2013
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235. Sixty years of genome biology

Author

Doolittle, W, primary, Fraser, Peter, additional, Gerstein, Mark B, additional, Graveley, Brenton R, additional, Henikoff, Steven, additional, Huttenhower, Curtis, additional, Oshlack, Alicia, additional, Ponting, Chris P, additional, Rinn, John L, additional, Schatz, Michael C, additional, Ule, Jernej, additional, Weigel, Detlef, additional, and Weinstock, George M, additional

Published
2013
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237. Erratum: Corrigendum: Performance comparison of whole-genome sequencing platforms

Author

Lam, Hugo Y K, primary, Clark, Michael J, additional, Chen, Rui, additional, Chen, Rong, additional, Natsoulis, Georges, additional, O'Huallachain, Maeve, additional, Dewey, Frederick E, additional, Habegger, Lukas, additional, Ashley, Euan A, additional, Gerstein, Mark B, additional, Butte, Atul J, additional, Ji, Hanlee P, additional, and Snyder, Michael, additional

Published
2012
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239. Detecting and annotating genetic variations using the HugeSeq pipeline

Author

Lam, Hugo Y K, primary, Pan, Cuiping, additional, Clark, Michael J, additional, Lacroute, Phil, additional, Chen, Rui, additional, Haraksingh, Rajini, additional, O'Huallachain, Maeve, additional, Gerstein, Mark B, additional, Kidd, Jeffrey M, additional, Bustamante, Carlos D, additional, and Snyder, Michael, additional

Published
2012
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240. Genomic Analysis of the Hydrocarbon-Producing, Cellulolytic, Endophytic Fungus Ascocoryne sarcoides

Author

Gianoulis, Tara A., primary, Griffin, Meghan A., additional, Spakowicz, Daniel J., additional, Dunican, Brian F., additional, Alpha, Cambria J., additional, Sboner, Andrea, additional, Sismour, A. Michael, additional, Kodira, Chinnappa, additional, Egholm, Michael, additional, Church, George M., additional, Gerstein, Mark B., additional, and Strobel, Scott A., additional

Published
2012
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241. The GENCODE pseudogene resource

Author

Pei, Baikang, primary, Sisu, Cristina, additional, Frankish, Adam, additional, Howald, Cédric, additional, Habegger, Lukas, additional, Mu, Xinmeng, additional, Harte, Rachel, additional, Balasubramanian, Suganthi, additional, Tanzer, Andrea, additional, Diekhans, Mark, additional, Reymond, Alexandre, additional, Hubbard, Tim J, additional, Harrow, Jennifer, additional, and Gerstein, Mark B, additional

Published
2012
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242. Performance comparison of whole-genome sequencing platforms

Author

Lam, Hugo Y K, primary, Clark, Michael J, additional, Chen, Rui, additional, Chen, Rong, additional, Natsoulis, Georges, additional, O'Huallachain, Maeve, additional, Dewey, Frederick E, additional, Habegger, Lukas, additional, Ashley, Euan A, additional, Gerstein, Mark B, additional, Butte, Atul J, additional, Ji, Hanlee P, additional, and Snyder, Michael, additional

Published
2011
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243. Molecular Characterization of Neuroendocrine Prostate Cancer and Identification of New Drug Targets

Author

Beltran, Himisha, primary, Rickman, David S., additional, Park, Kyung, additional, Chae, Sung Suk, additional, Sboner, Andrea, additional, MacDonald, Theresa Y., additional, Wang, Yuwei, additional, Sheikh, Karen L., additional, Terry, Stéphane, additional, Tagawa, Scott T., additional, Dhir, Rajiv, additional, Nelson, Joel B., additional, de la Taille, Alexandre, additional, Allory, Yves, additional, Gerstein, Mark B., additional, Perner, Sven, additional, Pienta, Kenneth J., additional, Chinnaiyan, Arul M., additional, Wang, Yuzhuo, additional, Collins, Colin C., additional, Gleave, Martin E., additional, Demichelis, Francesca, additional, Nanus, David M., additional, and Rubin, Mark A., additional

Published
2011
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244. Identification of a Disease-Defining Gene Fusion in Epithelioid Hemangioendothelioma

Author

Tanas, Munir R., primary, Sboner, Andrea, additional, Oliveira, Andre M., additional, Erickson-Johnson, Michele R., additional, Hespelt, Jessica, additional, Hanwright, Philip J., additional, Flanagan, John, additional, Luo, Yuling, additional, Fenwick, Kerry, additional, Natrajan, Rachael, additional, Mitsopoulos, Costas, additional, Zvelebil, Marketa, additional, Hoch, Benjamin L., additional, Weiss, Sharon W., additional, Debiec-Rychter, Maria, additional, Sciot, Raf, additional, West, Rob B., additional, Lazar, Alexander J., additional, Ashworth, Alan, additional, Reis-Filho, Jorge S., additional, Lord, Christopher J., additional, Gerstein, Mark B., additional, Rubin, Mark A., additional, and Rubin, Brian P., additional

Published
2011
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245. The Reality of Pervasive Transcription

Author

Clark, Michael B., primary, Amaral, Paulo P., additional, Schlesinger, Felix J., additional, Dinger, Marcel E., additional, Taft, Ryan J., additional, Rinn, John L., additional, Ponting, Chris P., additional, Stadler, Peter F., additional, Morris, Kevin V., additional, Morillon, Antonin, additional, Rozowsky, Joel S., additional, Gerstein, Mark B., additional, Wahlestedt, Claes, additional, Hayashizaki, Yoshihide, additional, Carninci, Piero, additional, Gingeras, Thomas R., additional, and Mattick, John S., additional

Published
2011
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246. Abstract 3925: Characterization of complex chromosomal aberrations in prostate cancer from whole genome sequencing

Author

Berger, Michael F., primary, Lawrence, Michael S., additional, Demichelis, Francesca, additional, Drier, Yotam, additional, Cibulskis, Kristian, additional, Sivachenko, Andrey Y., additional, Sboner, Andrea, additional, Esgueva, Raquel, additional, Pflueger, Dorothee, additional, Sougnez, Carrie, additional, Onofrio, Robert, additional, Carter, Scott L., additional, Park, Kyung, additional, Habegger, Lukas, additional, Ambrogio, Lauren, additional, Fennell, Timothy, additional, Parkin, Melissa, additional, Saksena, Gordon, additional, Voet, Douglas, additional, Ramos, Alex H., additional, Pugh, Trevor J., additional, Wilkinson, Jane, additional, Fisher, Sheila, additional, Winckler, Wendy, additional, Mahan, Scott, additional, Ardlie, Kristin, additional, Baldwin, Jennifer, additional, Simons, Jonathan W., additional, Kitabayashi, Naoki, additional, MacDonald, Theresa Y., additional, Kantoff, Philip W., additional, Chin, Lynda, additional, Gabriel, Stacey B., additional, Gerstein, Mark B., additional, Golub, Todd R., additional, Meyerson, Matthew, additional, Tewari, Ashutosh, additional, Lander, Eric S., additional, Getz, Gad, additional, Rubin, Mark A., additional, and Garraway, Levi A., additional

Published
2011
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247. Abstract 957: Aurora kinase and N-myc are involved in neuroendocrine differentiation of prostate cancer and are new drug targets

Author

Beltran, Himisha, primary, Rickman, David, additional, Park, Kyung, additional, Sboner, Andrea, additional, Macdonald, Theresa, additional, Terry, Stephane, additional, Tagawa, Scott T., additional, Gerstein, Mark B., additional, Demichelis, Francesca, additional, Nanus, David M., additional, and Rubin, Mark A., additional

Published
2011
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