33 results on '"Shypitsyna, A"'
Search Results
2. An expanded evaluation of protein function prediction methods shows an improvement in accuracy
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Jiang, Yuxiang, Oron, Tal Ronnen, Clark, Wyatt T, Bankapur, Asma R, D'Andrea, Daniel, Lepore, Rosalba, Funk, Christopher S, Kahanda, Indika, Verspoor, Karin M, Ben-Hur, Asa, Koo, Emily, Penfold-Brown, Duncan, Shasha, Dennis, Youngs, Noah, Bonneau, Richard, Lin, Alexandra, Sahraeian, Sayed ME, Martelli, Pier Luigi, Profiti, Giuseppe, Casadio, Rita, Cao, Renzhi, Zhong, Zhaolong, Cheng, Jianlin, Altenhoff, Adrian, Skunca, Nives, Dessimoz, Christophe, Dogan, Tunca, Hakala, Kai, Kaewphan, Suwisa, Mehryary, Farrokh, Salakoski, Tapio, Ginter, Filip, Fang, Hai, Smithers, Ben, Oates, Matt, Gough, Julian, Törönen, Petri, Koskinen, Patrik, Holm, Liisa, Chen, Ching-Tai, Hsu, Wen-Lian, Bryson, Kevin, Cozzetto, Domenico, Minneci, Federico, Jones, David T, Chapman, Samuel, C., Dukka B K., Khan, Ishita K, Kihara, Daisuke, Ofer, Dan, Rappoport, Nadav, Stern, Amos, Cibrian-Uhalte, Elena, Denny, Paul, Foulger, Rebecca E, Hieta, Reija, Legge, Duncan, Lovering, Ruth C, Magrane, Michele, Melidoni, Anna N, Mutowo-Meullenet, Prudence, Pichler, Klemens, Shypitsyna, Aleksandra, Li, Biao, Zakeri, Pooya, ElShal, Sarah, Tranchevent, Léon-Charles, Das, Sayoni, Dawson, Natalie L, Lee, David, Lees, Jonathan G, Sillitoe, Ian, Bhat, Prajwal, Nepusz, Tamás, Romero, Alfonso E, Sasidharan, Rajkumar, Yang, Haixuan, Paccanaro, Alberto, Gillis, Jesse, Sedeño-Cortés, Adriana E, Pavlidis, Paul, Feng, Shou, Cejuela, Juan M, Goldberg, Tatyana, Hamp, Tobias, Richter, Lothar, Salamov, Asaf, Gabaldon, Toni, Marcet-Houben, Marina, Supek, Fran, Gong, Qingtian, Ning, Wei, Zhou, Yuanpeng, Tian, Weidong, Falda, Marco, Fontana, Paolo, Lavezzo, Enrico, Toppo, Stefano, Ferrari, Carlo, Giollo, Manuel, Piovesan, Damiano, Tosatto, Silvio, del Pozo, Angela, Fernández, José M, Maietta, Paolo, Valencia, Alfonso, Tress, Michael L, Benso, Alfredo, Di Carlo, Stefano, Politano, Gianfranco, Savino, Alessandro, Rehman, Hafeez Ur, Re, Matteo, Mesiti, Marco, Valentini, Giorgio, Bargsten, Joachim W, van Dijk, Aalt DJ, Gemovic, Branislava, Glisic, Sanja, Perovic, Vladmir, Veljkovic, Veljko, Veljkovic, Nevena, Almeida-e-Silva, Danillo C, Vencio, Ricardo ZN, Sharan, Malvika, Vogel, Jörg, Kansakar, Lakesh, Zhang, Shanshan, Vucetic, Slobodan, Wang, Zheng, Sternberg, Michael JE, Wass, Mark N, Huntley, Rachael P, Martin, Maria J, O'Donovan, Claire, Robinson, Peter N, Moreau, Yves, Tramontano, Anna, Babbitt, Patricia C, Brenner, Steven E, Linial, Michal, Orengo, Christine A, Rost, Burkhard, Greene, Casey S, Mooney, Sean D, Friedberg, Iddo, and Radivojac, Predrag
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Quantitative Biology - Quantitative Methods - Abstract
Background: The increasing volume and variety of genotypic and phenotypic data is a major defining characteristic of modern biomedical sciences. At the same time, the limitations in technology for generating data and the inherently stochastic nature of biomolecular events have led to the discrepancy between the volume of data and the amount of knowledge gleaned from it. A major bottleneck in our ability to understand the molecular underpinnings of life is the assignment of function to biological macromolecules, especially proteins. While molecular experiments provide the most reliable annotation of proteins, their relatively low throughput and restricted purview have led to an increasing role for computational function prediction. However, accurately assessing methods for protein function prediction and tracking progress in the field remain challenging. Methodology: We have conducted the second Critical Assessment of Functional Annotation (CAFA), a timed challenge to assess computational methods that automatically assign protein function. One hundred twenty-six methods from 56 research groups were evaluated for their ability to predict biological functions using the Gene Ontology and gene-disease associations using the Human Phenotype Ontology on a set of 3,681 proteins from 18 species. CAFA2 featured significantly expanded analysis compared with CAFA1, with regards to data set size, variety, and assessment metrics. To review progress in the field, the analysis also compared the best methods participating in CAFA1 to those of CAFA2. Conclusions: The top performing methods in CAFA2 outperformed the best methods from CAFA1, demonstrating that computational function prediction is improving. This increased accuracy can be attributed to the combined effect of the growing number of experimental annotations and improved methods for function prediction., Comment: Submitted to Genome Biology
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- 2016
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3. Extending gene ontology in the context of extracellular RNA and vesicle communication
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Cheung, Kei-Hoi, Keerthikumar, Shivakumar, Roncaglia, Paola, Subramanian, Sai Lakshmi, Roth, Matthew E, Samuel, Monisha, Anand, Sushma, Gangoda, Lahiru, Gould, Stephen, Alexander, Roger, Galas, David, Gerstein, Mark B, Hill, Andrew F, Kitchen, Robert R, Lötvall, Jan, Patel, Tushar, Procaccini, Dena C, Quesenberry, Peter, Rozowsky, Joel, Raffai, Robert L, Shypitsyna, Aleksandra, Su, Andrew I, Théry, Clotilde, Vickers, Kasey, Wauben, Marca HM, Mathivanan, Suresh, Milosavljevic, Aleksandar, and Laurent, Louise C
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Information and Computing Sciences ,Genetics ,Databases ,Genetic ,Extracellular Vesicles ,Gene Ontology ,Humans ,Molecular Sequence Annotation ,RNA ,Web Browser ,Ontology ,Extracellular RNA ,Extracellular vesicle ,Metadata ,Faceted search ,Atlas ,Other Biological Sciences ,Artificial Intelligence and Image Processing ,Information Systems ,Information and computing sciences - Abstract
BackgroundTo 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.MethodsBy 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.ResultsWe 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.ConclusionsAs 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.
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- 2016
4. FEATURES OF THE DECENTRALIZED MODEL OF PUBLIC MANAGEMENT OF GENERAL SECONDARY EDUCATION IN EUROPEAN COUNTRIES
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SHYPITSYNA, Yevheniia, primary
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- 2023
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5. Substrate properties of zebrafish Rtn4b/Nogo and axon regeneration in the zebrafish optic nerve
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Bodrikov, Vsevolod, Welte, Cornelia, Wiechers, Marianne, Weschenfelder, Markus, Kaur, Gurjot, Shypitsyna, Aleksandra, Pinzon‐Olejua, Alejandro, Bastmeyer, Martin, and Stuermer, Claudia A. O.
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- 2017
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6. Upregulation of reggie-1/flotillin-2 promotes axon regeneration in the rat optic nerve in vivo and neurite growth in vitro
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Jan C. Koch, Gonzalo P. Solis, Vsevolod Bodrikov, Uwe Michel, Deana Haralampieva, Aleksandra Shypitsyna, Lars Tönges, Mathias Bähr, Paul Lingor, and Claudia A.O. Stuermer
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Reggie-1/flotillin-2 ,Axon regeneration ,Neurite outgrowth ,Optic nerve crush ,Neurosciences. Biological psychiatry. Neuropsychiatry ,RC321-571 - Abstract
The ability of fish retinal ganglion cells (RGCs) to regenerate their axons was shown to require the re-expression and function of the two proteins reggie-1 and -2. RGCs in mammals fail to upregulate reggie expression and to regenerate axons after lesion suggesting the possibility that induced upregulation might promote regeneration. In the present study, RGCs in adult rats were induced to express reggie-1 by intravitreal injection of adeno-associated viral vectors (AAV2/1) expressing reggie-1 (AAV.R1-EGFP) 14d prior to optic nerve crush. Four weeks later, GAP-43-positive regenerating axons had crossed the lesion and grown into the nerve at significantly higher numbers and length (up to 5 mm) than the control transduced with AAV.EGFP. Consistently, after transduction with AAV.R1-EGFP as opposed to AAV.EGFP, primary RGCs in vitro grew long axons on chondroitin sulfate proteoglycan (CSPG) and Nogo-A, both glial cell-derived inhibitors of neurite growth, suggesting that reggie-1 can provide neurons with the ability to override inhibitors of neurite growth. This reggie-1-mediated enhancement of growth was reproduced in mouse hippocampal and N2a neurons which generated axons 40–60% longer than their control counterparts. This correlates with the reggie-1-dependent activation of Src and PI3 kinase (PI3K), of the Rho family GTPase Rac1 and downstream effectors such as cofilin. This increased growth also depends on TC10, the GTPase involved in cargo delivery to the growth cone. Thus, the upregulation of reggie-1 in mammalian neurons provides nerve cells with neuron-intrinsic properties required for axon growth and successful regeneration in the adult mammalian CNS.
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- 2013
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7. UniProt-GOA: A Central Resource for Data Integration and GO Annotation.
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Mélanie Courtot, Aleksandra Shypitsyna, Elena Speretta, Alexander Holmes, Tony Sawford, Tony Wardell, Maria Jesus Martin, and Claire O'Donovan
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- 2015
8. Comparative analysis of the effects of various detoxification solutions on the structure of the kidneys in experimental burn disease in rats
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L.Ya. Fedoniuk, T.V. Lachtadyr, O.V. Shypitsyna, and V.G. Cherkasov
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Pulmonary and Respiratory Medicine ,Autophagosome ,Kidney ,Chemistry ,Renal cortex ,Nephron ,Mitochondrion ,Andrology ,medicine.anatomical_structure ,Pediatrics, Perinatology and Child Health ,Mitophagy ,Personal computer ,medicine ,Inner mitochondrial membrane - Abstract
The use of existing infusion solutions, as well as the development, scientific substantiation and implementation of the latest nephroprotective detoxification solutions, remain an urgent problem for combustiologists. The aim of this work is to compare the effects of various detoxification solutions (0.9 % NaCl solution and complex colloid-hyperosmolar solutions – lactoprotein with sorbitol and the newly developed HAES-LX-5 % solution) on the kidney structure in experimental burn disease in rats. The experimental rats were divided into seven groups (fifteen animals each): the first group was intact rats; the second, third and fourth groups were rats without reproduction of experimental burn disease, which had a separate intravenous infusion of 0.9 % NaCl solution, lactoprotein with sorbitol and HAES-LX-5 % at a dose of 10 ml/kg; the fifth, sixth and seventh groups were rats with experimental burn disease (by causing burn injury of the skin with an area of 21-23 % of the body surface), which under the same scheme had an intravenous infusion of the investigated solutions. All studies and the removal of rats from the experiment were performed under deep thiopental intraperitoneal anesthesia. Histological preparations of the renal cortex of the rat were stained with hematoxylin-eosin and examined on an Olympus BX51 microscope. Using ultramicrotome LKB-3 (Sweden) obtained semi-thin sections which were stained with toluidine blue and methylene blue – Azur II; and ultrathin sections were counterstained with uranyl acetate and lead citrate according to Reynolds and examined using a PEM-125K electron microscope. Morphometric measurements (estimation of the area of the vascular glomeruli, the area of the urinary lumen of the capsule of the renal corpuscles; the area of the renal tubules of the nephrons and the area of their lumens, the area of the renal corpuscles, the area of cytoplasm and nuclei of epithelial cells of tubules, and also their nuclear-cytoplasmic ratio) was carried out using the VideoTest-5.0, KAARA Image Base and Microsoft Excel on a personal computer. Statistical analysis of the obtained quantitative indicators was performed using the ІВМ SPSS v. 22.0. for Windows. Functionally different cells of nephrons have been found to die by necrosis, apoptosis and anoikis when infused with detoxification solutions during the development of burn disease; in epithelial cells of nephron tubules, mitophagy and mitoptosis occur. Mitoptosis in epithelial cells of rat tubules of nephrons with experimental burn skin injury is carried out in two ways related to: 1) destruction of the outer mitochondrial membrane; 2) preservation of the outer mitochondrial membrane and involvement of autophagic (mitophagic) mechanisms to release the cell from degraded mitochondrial material. In the first case, the mitochondria first condense, after which its matrix swells and the fragmentation of the cristae occurs due to the destruction of the junction of the cristae. Finally, the outer mitochondrial membrane breaks and the remnants of the cristae (in the form of vesicles) go into the cytoplasm. In the second case, the mitochondria condense, vesicular fragmentation of the cristae occurs, but the rupture of the outer mitochondrial membrane does not occur and the mitochondria are absorbed by the autophagosome (or transformed into the autophagosome). Next is the merger of autophagosomes with lysosomes and the formation of autophagolysosomes, which, under the conditions of effective digestion of the contents, are transformed into vacuoles. The latter are emptied by exocytosis and ensure the release of cells from degraded material. Only lactoprotein with sorbitol has a membrane-plastic effect on the strengthening (enhancement of structuring) of the mitochondrial membrane in part of the mitochondria of epithelial cells of nephron tubules, which is ultrastructurally manifested by an increase in the electron density and thickness of all components of the mitochondria. The maximum membrane effect of lactoprotein with sorbitol against mitochondria manifests itself fourteen days after the experimental burn skin injury and gradually (after twenty-one and thirty days) disappears, which is correlated with an improvement in the overall clinical condition and an improvement in the structural changes in the kidney of animals with burn disease. There is every reason to believe that increased structuration of mitochondria is a preventer of the spread of mitoptosis and mitophagy, the excess of which can lead to cell death.
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- 2019
9. The GOA database: Gene Ontology annotation updates for 2015
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Huntley, Rachael P., Sawford, Tony, Mutowo-Meullenet, Prudence, Shypitsyna, Aleksandra, Bonilla, Carlos, Martin, Maria J., and OʼDonovan, Claire
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- 2015
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10. CORPORATE CODES OF ETHICS: STRUCTURAL, PRAGMATIC, AND COGNITIVE ASPECTS
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Yu. V. Shypitsyna
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Engineering ethics ,Cognition ,Psychology ,Ethical code - Published
- 2020
11. Origin of Nogo-A by Domain Shuffling in an Early Jawed Vertebrate
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Shypitsyna, Aleksandra, Málaga-Trillo, Edward, Reuter, Alexander, and Stuermer, Claudia A.O.
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- 2011
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12. Substrate properties of zebrafish Rtn4b/Nogo and axon regeneration in the zebrafish optic nerve
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Alejandro Pinzon-Olejua, Aleksandra Shypitsyna, Cornelia Welte, Vsevolod Bodrikov, Gurjot Kaur, Martin Bastmeyer, Claudia A. O. Stuermer, Markus Weschenfelder, and Marianne Wiechers
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0301 basic medicine ,Retina ,animal structures ,biology ,Neurite ,Morpholino ,General Neuroscience ,biology.organism_classification ,Molecular biology ,Cell biology ,03 medical and health sciences ,Myelin ,030104 developmental biology ,0302 clinical medicine ,medicine.anatomical_structure ,Retinal ganglion cell ,embryonic structures ,Optic nerve ,medicine ,sense organs ,Axon ,Zebrafish ,030217 neurology & neurosurgery - Abstract
This study explored why lesioned retinal ganglion cell (RGC) axons regenerate successfully in the zebrafish optic nerve despite the presence of Rtn4b, the homologue of the rat neurite growth inhibitor RTN4-A/Nogo-A. Rat Nogo-A and zebrafish Rtn4b possess characteristic motifs (M1-4) in the Nogo-A-specific region, which contains delta20, the most inhibitory region of rat Nogo-A. To determine whether zebrafish M1-4 is inhibitory as rat M1-4 and Nogo-A delta20, proteins were recombinantly expressed and used as substrates for zebrafish single cell RGCs, mouse hippocampal neurons and goldfish, zebrafish and chick retinal explants. When offered as homogenous substrates, neurites of hippocampal neurons and of zebrafish single cell RGCs were inhibited by zebrafish M1-4, rat M1-4, and Nogo-A delta20. Neurite length increased when zebrafish single cell RGCs were treated with receptor-type-specific antagonists and, respectively, with morpholinos (MO) against S1PR2 and S1PR5a-which represent candidate zebrafish Nogo-A receptors. In a stripe assay, however, where M1-4 lanes alternate with polylysine-(Plys)-only lanes, RGC axons from goldfish, zebrafish, and chick retinal explants avoided rat M1-4 but freely crossed zebrafish M1-4 lanes-suggesting that zebrafish M1-4 is growth permissive and less inhibitory than rat M1-4. Moreover, immunostainings and dot blots of optic nerve and myelin showed that expression of Rtn4b is very low in tissue and myelin at 3-5 days after lesion when axons regenerate. Thus, Rtn4b seems to represent no major obstacle for axon regeneration in vivo because it is less inhibitory for RGC axons from retina explants, and because of its low abundance.
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- 2017
13. The Gene Ontology Resource: 20 years and still GOing strong
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Rebecca Tauber, Robert J. Dodson, Marek S. Skrzypek, Raymond Lee, Valerie Wood, Paul W. Sternberg, C. Rivoire, Nancy H. Campbell, E. Hatton-Ellis, M. Rodriguez-Lopez, Elena Speretta, D. S. Osumi, Alix J. Rey, A. Mac-Dougall, Jane E. Mendel, Christopher J. Mungall, Helen Parkinson, Maria Jesus Martin, Pascale Gaudet, A. Stutz, Nathan Dunn, Gillian Millburn, Kate Warner, K. Axelsen, C. Arighi, Mary E. Dolan, M. J. Kesling, Barbara Kramarz, Seth Carbon, Joshua L. Goodman, Rachael P. Huntley, Anjali Shrivastava, Daniela Raciti, C. Wu, Victor B. Strelets, Steven J Marygold, H. Drabkin, M. Magrane, Benjamin M. Good, A. Shrivatsav Vp, Lorna Richardson, James P. Balhoff, P. Lemercier, E. Bakker, Amaia Sangrador-Vegas, Marc Feuermann, Paul Thomas, D. Lieberherr, J. Cho, Hans-Michael Müller, Robert S. Nash, Leonore Reiser, Birgit H M Meldal, Neil D. Rawlings, N. N. Hyka, D. A. Natale, Paola Roncaglia, Paul Denny, Michelle G. Giglio, Judith A. Blake, S. Sundaram, Shankar Subramaniam, Marcus C. Chibucos, Kevin A. MacPherson, S. Poux, Karen R. Christie, Mary Shimoyama, Eva Huala, Colin Logie, Huaiyu Mi, Felix Gondwe, K. Pichler, Petra Fey, Deborah A. Siegele, Phani V. Garapati, N. Tyagi, J L De Pons, Alex Bateman, Melinda R. Dwinell, Pablo Porras, Giulia Antonazzo, Midori A. Harris, Y. Lussi, Stuart R. Miyasato, Li Ni, K. Laiho, A. Estreicher, Travis K. Sheppard, Edith D. Wong, M. C. Harrison, H. Chen, S. Basu, Sandra A. LaBonte, Margaret Duesbury, E. Hartline, Sibyl Gao, Vítor Trovisco, Jacqueline Hayles, George Georghiou, Rex L. Chisholm, Kathleen Falls, S. Poudel, James C. Hu, G. T. Hayman, Kim Rutherford, F. Jungo, Hsin-Yu Chang, E. Boutet, Robert D. Finn, Alex L. Mitchell, Stan Laulederkind, J. H. Rawson, Marek Tutaj, Vanessa Acquaah, Peter D'Eustachio, G. Keller, L. Breuza, P. Garmiri, Nicholas H. Brown, Laurent-Philippe Albou, Antonia Lock, Nomi L. Harris, U. Hinz, Matthew Berriman, R. Britto, Rossana Zaru, Suzanna E. Lewis, N. Gruaz-Gumowski, Livia Perfetto, Matt Simison, Martin Kuiper, Shuai Weng, M. Tognolli, G. Dos Santos, Elizabeth R Bolton, Xiaosong Huang, A. Gos, P. Masson, David B. Emmert, Lisa Matthews, C. Casals-Casas, Kevin L. Howe, N. T. Del, Sandra Orchard, L. Famiglietti, Doug Howe, T. Sawford, T. E.M. Jones, Stephen G. Oliver, Kalpana Karra, S. Fexova, Tremayne Mushayahama, Dustin Ebert, Jim Thurmond, Ruth C. Lovering, E. Coudert, A. Bridge, Suzi Aleksander, Suvarna Nadendla, Christian A. Grove, David P. Hill, J. M. Cherry, M. C. Blatter, K. Van Auken, H. Bye-A-Jee, B. L. Dunn, A. Lreid, Sabrina Toro, Monte Westerfield, Z. Xie, A. Auchincloss, I. Pedruzzi, Anushya Muruganujan, B. Bely, S. H. Ahmad, Stacia R. Engel, Shur-Jen Wang, Gail Binkley, Lincoln Stein, Pinglei Zhou, G. P. Argoud, Marcio Luis Acencio, C. Hulo, Jürg Bähler, Juancarlos Chan, P. C. Ng, Helen Attrill, Mélanie Courtot, A. Ignatchenko, Tanya Z. Berardini, D. Sitnikov, Eric Douglass, and A. Shypitsyna
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Quality Control ,media_common.quotation_subject ,Ontology (information science) ,Biology ,History, 21st Century ,Filter (software) ,Unique identifier ,World Wide Web ,03 medical and health sciences ,0302 clinical medicine ,Resource (project management) ,Web page ,Genetics ,Animals ,Humans ,Database Issue ,Quality (business) ,Function (engineering) ,Molecular Biology ,030304 developmental biology ,media_common ,0303 health sciences ,Focus (computing) ,Bacteria ,Eukaryota ,Molecular Sequence Annotation ,History, 20th Century ,High-Throughput Screening Assays ,Gene Ontology ,Mitogen-Activated Protein Kinases ,030217 neurology & neurosurgery - Abstract
The Gene Ontology resource (GO; http://geneontology.org) provides structured, computable knowledge regarding the functions of genes and gene products. Founded in 1998, GO has become widely adopted in the life sciences, and its contents are under continual improvement, both in quantity and in quality. Here, we report the major developments of the GO resource during the past two years. Each monthly release of the GO resource is now packaged and given a unique identifier (DOI), enabling GO-based analyses on a specific release to be reproduced in the future. The molecular function ontology has been refactored to better represent the overall activities of gene products, with a focus on transcription regulator activities. Quality assurance efforts have been ramped up to address potentially out-of-date or inaccurate annotations. New evidence codes for high-throughput experiments now enable users to filter out annotations obtained from these sources. GO-CAM, a new framework for representing gene function that is more expressive than standard GO annotations, has been released, and users can now explore the growing repository of these models. We also provide the ‘GO ribbon’ widget for visualizing GO annotations to a gene; the widget can be easily embedded in any web page. This is an open access article distributed under the terms of the Creative Commons CC BY license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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- 2018
14. Comparative analysis of the effects of various detoxification solutions on the structure of the kidneys in experimental burn disease in rats
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Cherkasov, V.G., primary, Lachtadyr, T.V., primary, Fedoniuk, L.Ya., primary, and Shypitsyna, O.V., primary
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- 2019
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15. An expanded evaluation of protein function prediction methods shows an improvement in accuracy
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Yuxiang Jiang, Tal Ronnen Oron, Wyatt T. Clark, Asma R. Bankapur, Daniel D’Andrea, Rosalba Lepore, Christopher S. Funk, Indika Kahanda, Karin M. Verspoor, Asa Ben-Hur, Da Chen Emily Koo, Duncan Penfold-Brown, Dennis Shasha, Noah Youngs, Richard Bonneau, Alexandra Lin, Sayed M. E. Sahraeian, Pier Luigi Martelli, Giuseppe Profiti, Rita Casadio, Renzhi Cao, Zhaolong Zhong, Jianlin Cheng, Adrian Altenhoff, Nives Skunca, Christophe Dessimoz, Tunca Dogan, Kai Hakala, Suwisa Kaewphan, Farrokh Mehryary, Tapio Salakoski, Filip Ginter, Hai Fang, Ben Smithers, Matt Oates, Julian Gough, Petri Törönen, Patrik Koskinen, Liisa Holm, Ching-Tai Chen, Wen-Lian Hsu, Kevin Bryson, Domenico Cozzetto, Federico Minneci, David T. Jones, Samuel Chapman, Dukka BKC, Ishita K. Khan, Daisuke Kihara, Dan Ofer, Nadav Rappoport, Amos Stern, Elena Cibrian-Uhalte, Paul Denny, Rebecca E. Foulger, Reija Hieta, Duncan Legge, Ruth C. Lovering, Michele Magrane, Anna N. Melidoni, Prudence Mutowo-Meullenet, Klemens Pichler, Aleksandra Shypitsyna, Biao Li, Pooya Zakeri, Sarah ElShal, Léon-Charles Tranchevent, Sayoni Das, Natalie L. Dawson, David Lee, Jonathan G. Lees, Ian Sillitoe, Prajwal Bhat, Tamás Nepusz, Alfonso E. Romero, Rajkumar Sasidharan, Haixuan Yang, Alberto Paccanaro, Jesse Gillis, Adriana E. Sedeño-Cortés, Paul Pavlidis, Shou Feng, Juan M. Cejuela, Tatyana Goldberg, Tobias Hamp, Lothar Richter, Asaf Salamov, Toni Gabaldon, Marina Marcet-Houben, Fran Supek, Qingtian Gong, Wei Ning, Yuanpeng Zhou, Weidong Tian, Marco Falda, Paolo Fontana, Enrico Lavezzo, Stefano Toppo, Carlo Ferrari, Manuel Giollo, Damiano Piovesan, Silvio C.E. Tosatto, Angela del Pozo, José M. Fernández, Paolo Maietta, Alfonso Valencia, Michael L. Tress, Alfredo Benso, Stefano Di Carlo, Gianfranco Politano, Alessandro Savino, Hafeez Ur Rehman, Matteo Re, Marco Mesiti, Giorgio Valentini, Joachim W. Bargsten, Aalt D. J. van Dijk, Branislava Gemovic, Sanja Glisic, Vladmir Perovic, Veljko Veljkovic, Nevena Veljkovic, Danillo C. Almeida-e-Silva, Ricardo Z. N. Vencio, Malvika Sharan, Jörg Vogel, Lakesh Kansakar, Shanshan Zhang, Slobodan Vucetic, Zheng Wang, Michael J. E. Sternberg, Mark N. Wass, Rachael P. Huntley, Maria J. Martin, Claire O’Donovan, Peter N. Robinson, Yves Moreau, Anna Tramontano, Patricia C. Babbitt, Steven E. Brenner, Michal Linial, Christine A. Orengo, Burkhard Rost, Casey S. Greene, Sean D. Mooney, Iddo Friedberg, Predrag Radivojac, Jiang, Yuxiang, Oron, Tal Ronnen, Clark, Wyatt T., Bankapur, Asma R., D’Andrea, Daniel, Lepore, Rosalba, Funk, Christopher S., Kahanda, Indika, Verspoor, Karin M., Ben-Hur, Asa, Koo, Da Chen Emily, Penfold-Brown, Duncan, Shasha, Denni, Youngs, Noah, Bonneau, Richard, Lin, Alexandra, Sahraeian, Sayed M. E., Martelli, Pier Luigi, Profiti, Giuseppe, Casadio, Rita, Cao, Renzhi, Zhong, Zhaolong, Cheng, Jianlin, Altenhoff, Adrian, Skunca, Nive, Dessimoz, Christophe, Dogan, Tunca, Hakala, Kai, Kaewphan, Suwisa, Mehryary, Farrokh, Salakoski, Tapio, Ginter, Filip, Fang, Hai, Smithers, Ben, Oates, Matt, Gough, Julian, Törönen, Petri, Koskinen, Patrik, Holm, Liisa, Chen, Ching-Tai, Hsu, Wen-Lian, Bryson, Kevin, Cozzetto, Domenico, Minneci, Federico, Jones, David T., Chapman, Samuel, Bkc, Dukka, Khan, Ishita K., Kihara, Daisuke, Ofer, Dan, Rappoport, Nadav, Stern, Amo, Cibrian-Uhalte, Elena, Denny, Paul, Foulger, Rebecca E., Hieta, Reija, Legge, Duncan, Lovering, Ruth C., Magrane, Michele, Melidoni, Anna N., Mutowo-Meullenet, Prudence, Pichler, Klemen, Shypitsyna, Aleksandra, Li, Biao, Zakeri, Pooya, Elshal, Sarah, Tranchevent, Léon-Charle, Das, Sayoni, Dawson, Natalie L., Lee, David, Lees, Jonathan G., Sillitoe, Ian, Bhat, Prajwal, Nepusz, Tamá, Romero, Alfonso E., Sasidharan, Rajkumar, Yang, Haixuan, Paccanaro, Alberto, Gillis, Jesse, Sedeño-Cortés, Adriana E., Pavlidis, Paul, Feng, Shou, Cejuela, Juan M., Goldberg, Tatyana, Hamp, Tobia, Richter, Lothar, Salamov, Asaf, Gabaldon, Toni, Marcet-Houben, Marina, Supek, Fran, Gong, Qingtian, Ning, Wei, Zhou, Yuanpeng, Tian, Weidong, Falda, Marco, Fontana, Paolo, Lavezzo, Enrico, Toppo, Stefano, Ferrari, Carlo, Giollo, Manuel, Piovesan, Damiano, Tosatto, Silvio C.E., del Pozo, Angela, Fernández, José M., Maietta, Paolo, Valencia, Alfonso, Tress, Michael L., Benso, Alfredo, Di Carlo, Stefano, Politano, Gianfranco, Savino, Alessandro, Rehman, Hafeez Ur, Re, Matteo, Mesiti, Marco, Valentini, Giorgio, Bargsten, Joachim W., van Dijk, Aalt D. J., Gemovic, Branislava, Glisic, Sanja, Perovic, Vladmir, Veljkovic, Veljko, Veljkovic, Nevena, Almeida-e-Silva, Danillo C., Vencio, Ricardo Z. N., Sharan, Malvika, Vogel, Jörg, Kansakar, Lakesh, Zhang, Shanshan, Vucetic, Slobodan, Wang, Zheng, Sternberg, Michael J. E., Wass, Mark N., Huntley, Rachael P., Martin, Maria J., O’Donovan, Claire, Robinson, Peter N., Moreau, Yve, Tramontano, Anna, Babbitt, Patricia C., Brenner, Steven E., Linial, Michal, Orengo, Christine A., Rost, Burkhard, Greene, Casey S., Mooney, Sean D., Friedberg, Iddo, Radivojac, Predrag, Friedberg, Iddo [0000-0002-1789-8000], Apollo - University of Cambridge Repository, (ukupan broj autora: 147), Biotechnology and Biological Sciences Research Council (BBSRC), National Science Foundation (Estados Unidos), United States of Department of Health & Human Services, National Natural Science Foundation of China, Natural Sciences and Engineering Research Council (Canadá), São Paulo Research Foundation, Ministerio de Economía y Competitividad (España), Biotechnology and Biological Sciences Research Council (Reino Unido), Katholieke Universiteit Leuven (Bélgica), Newton International Fellowship Scheme of the Royal Society grant, British Heart Foundation, Ministry of Education, Science and Technological Development (Serbia), Office of Biological and Environmental Research (Estados Unidos), Australian Research Council, University of Padua (Italia), Swiss National Science Foundation, Institute of Biotechnology, Computational genomics, and Bioinformatics
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0301 basic medicine ,Computer science ,Disease gene prioritization ,Protein function prediction ,Ecology, Evolution, Behavior and Systematics ,Genetics ,Cell Biology ,05 Environmental Sciences ,600 Technik, Medizin, angewandte Wissenschaften::610 Medizin und Gesundheit ,computer.software_genre ,Quantitative Biology - Quantitative Methods ,Wiskundige en Statistische Methoden - Biometris ,Field (computer science) ,Laboratorium voor Plantenveredeling ,Function (engineering) ,Databases, Protein ,1183 Plant biology, microbiology, virology ,Quantitative Methods (q-bio.QM) ,media_common ,Genetics & Heredity ,Settore BIO/11 - BIOLOGIA MOLECOLARE ,Ecology ,SISTA ,1184 Genetics, developmental biology, physiology ,Life Sciences & Biomedicine ,Algorithms ,Bioinformatics ,Evolution ,media_common.quotation_subject ,BIOINFORMÁTICA ,Machine learning ,Bottleneck ,Set (abstract data type) ,BIOS Applied Bioinformatics ,03 medical and health sciences ,Annotation ,Structure-Activity Relationship ,Behavior and Systematics ,Human Phenotype Ontology ,Humans ,ddc:610 ,DISINTEGRIN ,Mathematical and Statistical Methods - Biometris ,BIOINFORMATICS ,08 Information And Computing Sciences ,Science & Technology ,business.industry ,Research ,ADAM ,Proteins ,Computational Biology ,Molecular Sequence Annotation ,06 Biological Sciences ,Data set ,ONTOLOGY ,Plant Breeding ,030104 developmental biology ,Gene Ontology ,Biotechnology & Applied Microbiology ,FOS: Biological sciences ,Artificial intelligence ,business ,computer ,Software - Abstract
BACKGROUND: A major bottleneck in our understanding of the molecular underpinnings of life is the assignment of function to proteins. While molecular experiments provide the most reliable annotation of proteins, their relatively low throughput and restricted purview have led to an increasing role for computational function prediction. However, assessing methods for protein function prediction and tracking progress in the field remain challenging. RESULTS: We conducted the second critical assessment of functional annotation (CAFA), a timed challenge to assess computational methods that automatically assign protein function. We evaluated 126 methods from 56 research groups for their ability to predict biological functions using Gene Ontology and gene-disease associations using Human Phenotype Ontology on a set of 3681 proteins from 18 species. CAFA2 featured expanded analysis compared with CAFA1, with regards to data set size, variety, and assessment metrics. To review progress in the field, the analysis compared the best methods from CAFA1 to those of CAFA2. CONCLUSIONS: The top-performing methods in CAFA2 outperformed those from CAFA1. This increased accuracy can be attributed to a combination of the growing number of experimental annotations and improved methods for function prediction. The assessment also revealed that the definition of top-performing algorithms is ontology specific, that different performance metrics can be used to probe the nature of accurate predictions, and the relative diversity of predictions in the biological process and human phenotype ontologies. While there was methodological improvement between CAFA1 and CAFA2, the interpretation of results and usefulness of individual methods remain context-dependent., We acknowledge the contributions of Maximilian Hecht, Alexander Grün, Julia Krumhoff, My Nguyen Ly, Jonathan Boidol, Rene Schoeffel, Yann Spöri, Jessika Binder, Christoph Hamm and Karolina Worf. This work was partially supported by the following grants: National Science Foundation grants DBI-1458477 (PR), DBI-1458443 (SDM), DBI-1458390 (CSG), DBI-1458359 (IF), IIS-1319551 (DK), DBI-1262189 (DK), and DBI-1149224 (JC); National Institutes of Health grants R01GM093123 (JC), R01GM097528 (DK), R01GM076990 (PP), R01GM071749 (SEB), R01LM009722 (SDM), and UL1TR000423 (SDM); the National Natural Science Foundation of China grants 3147124 (WT) and 91231116 (WT); the National Basic Research Program of China grant 2012CB316505 (WT); NSERC grant RGPIN 371348-11 (PP); FP7 infrastructure project TransPLANT Award 283496 (ADJvD); Microsoft Research/FAPESP grant 2009/53161-6 and FAPESP fellowship 2010/50491-1 (DCAeS); Biotechnology and Biological Sciences Research Council grants BB/L020505/1 (DTJ), BB/F020481/1 (MJES), BB/K004131/1 (AP), BB/F00964X/1 (AP), and BB/L018241/1 (CD); the Spanish Ministry of Economics and Competitiveness grant BIO2012-40205 (MT); KU Leuven CoE PFV/10/016 SymBioSys (YM); the Newton International Fellowship Scheme of the Royal Society grant NF080750 (TN). CSG was supported in part by the Gordon and Betty Moore Foundation’s Data-Driven Discovery Initiative grant GBMF4552. Computational resources were provided by CSC – IT Center for Science Ltd., Espoo, Finland (TS). This work was supported by the Academy of Finland (TS). RCL and ANM were supported by British Heart Foundation grant RG/13/5/30112. PD, RCL, and REF were supported by Parkinson’s UK grant G-1307, the Alexander von Humboldt Foundation through the German Federal Ministry for Education and Research, Ernst Ludwig Ehrlich Studienwerk, and the Ministry of Education, Science and Technological Development of the Republic of Serbia grant 173001. This work was a Technology Development effort for ENIGMA – Ecosystems and Networks Integrated with Genes and Molecular Assemblies (http://enigma.lbl.gov), a Scientific Focus Area Program at Lawrence Berkeley National Laboratory, which is based upon work supported by the U.S. Department of Energy, Office of Science, Office of Biological & Environmental Research grant DE-AC02-05CH11231. ENIGMA only covers the application of this work to microbial proteins. NSF DBI-0965616 and Australian Research Council grant DP150101550 (KMV). NSF DBI-0965768 (ABH). NIH T15 LM00945102 (training grant for CSF). FP7 FET grant MAESTRA ICT-2013-612944 and FP7 REGPOT grant InnoMol (FS). NIH R01 GM60595 (PCB). University of Padova grants CPDA138081/13 (ST) and GRIC13AAI9 (EL). Swiss National Science Foundation grant 150654 and UK BBSRC grant BB/M015009/1 (COD). PRB2 IPT13/0001 - ISCIII-SGEFI / FEDER (JMF)., This is the final version of the article. It first appeared from BioMed Central at http://dx.doi.org/10.1186/s13059-016-1037-6.
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- 2016
16. Substrate properties of zebrafish Rtn4b/Nogo and axon regeneration in the zebrafish optic nerve
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Vsevolod, Bodrikov, Cornelia, Welte, Marianne, Wiechers, Markus, Weschenfelder, Gurjot, Kaur, Aleksandra, Shypitsyna, Alejandro, Pinzon-Olejua, Martin, Bastmeyer, and Claudia A O, Stuermer
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Retinal Ganglion Cells ,Nogo Receptors ,animal structures ,Nogo Proteins ,Amino Acid Motifs ,Neuronal Outgrowth ,Chick Embryo ,Hippocampus ,Retina ,Tissue Culture Techniques ,Goldfish ,ddc:570 ,Animals ,Cells, Cultured ,Myelin Sheath ,Zebrafish ,Tissue Scaffolds ,Optic Nerve ,Zebrafish Proteins ,Axons ,Nerve Regeneration ,Rats ,Mice, Inbred C57BL ,Optic Nerve Injuries ,embryonic structures ,sense organs ,Myelin Proteins - Abstract
This study explored why lesioned retinal ganglion cell (RGC) axons regenerate successfully in the zebrafish optic nerve despite the presence of Rtn4b, the homologue of the rat neurite growth inhibitor RTN4-A/Nogo-A. Rat Nogo-A and zebrafish Rtn4b possess characteristic motifs (M1-4) in the Nogo-A-specific region, which contains delta20, the most inhibitory region of rat Nogo-A. To determine whether zebrafish M1-4 is inhibitory as rat M1-4 and Nogo-A delta20, proteins were recombinantly expressed and used as substrates for zebrafish single cell RGCs, mouse hippocampal neurons and goldfish, zebrafish and chick retinal explants. When offered as homogenous substrates, neurites of hippocampal neurons and of zebrafish single cell RGCs were inhibited by zebrafish M1-4, rat M1-4, and Nogo-A delta20. Neurite length increased when zebrafish single cell RGCs were treated with receptor-type-specific antagonists and, respectively, with morpholinos (MO) against S1PR2 and S1PR5a-which represent candidate zebrafish Nogo-A receptors. In a stripe assay, however, where M1-4 lanes alternate with polylysine-(Plys)-only lanes, RGC axons from goldfish, zebrafish, and chick retinal explants avoided rat M1-4 but freely crossed zebrafish M1-4 lanes-suggesting that zebrafish M1-4 is growth permissive and less inhibitory than rat M1-4. Moreover, immunostainings and dot blots of optic nerve and myelin showed that expression of Rtn4b is very low in tissue and myelin at 3-5 days after lesion when axons regenerate. Thus, Rtn4b seems to represent no major obstacle for axon regeneration in vivo because it is less inhibitory for RGC axons from retina explants, and because of its low abundance. published
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- 2017
17. The GOA database: Gene Ontology annotation updates for 2015
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Carlos Bonilla, Claire O'Donovan, Rachael P. Huntley, Prudence Mutowo-Meullenet, Tony Sawford, Maria Jesus Martin, and Aleksandra Shypitsyna
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Web browser ,Internet ,Database ,Gene ontology ,business.industry ,Proteins ,Molecular Sequence Annotation ,Biology ,File format ,computer.software_genre ,Annotation ,Gene Ontology ,Genetics ,Database Issue ,Humans ,The Internet ,UniProt ,business ,Databases, Protein ,computer ,GeneralLiterature_REFERENCE(e.g.,dictionaries,encyclopedias,glossaries) ,Software ,Gene ontology annotation - Abstract
The Gene Ontology Annotation (GOA) resource (http://www.ebi.ac.uk/GOA) provides evidence-based Gene Ontology (GO) annotations to proteins in the UniProt Knowledgebase (UniProtKB). Manual annotations provided by UniProt curators are supplemented by manual and automatic annotations from model organism databases and specialist annotation groups. GOA currently supplies 368 million GO annotations to almost 54 million proteins in more than 480,000 taxonomic groups. The resource now provides annotations to five times the number of proteins it did 4 years ago. As a member of the GO Consortium, we adhere to the most up-to-date Consortium-agreed annotation guidelines via the use of quality control checks that ensures that the GOA resource supplies high-quality functional information to proteins from a wide range of species. Annotations from GOA are freely available and are accessible through a powerful web browser as well as a variety of annotation file formats.
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- 2014
18. Activities at the Universal Protein Resource (UniProt)
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Borisas Bursteinas, L-S Yeh, Klemens Pichler, Guillaume Keller, C Casal-Casas, Gerritsen, A Da Silva, Prudence Mutowo, Xavier D. Martin, Peter B. McGarvey, Volynkin, J Lew, K Sonesson, M. C. Blatter, L Pureza, Rodrigo Lopez, Anne Estreicher, Alex Bateman, Ramona Britto, A-L Veuthey, Penelope Garmiri, Patrick Masson, Baris E. Suzek, Cathy H. Wu, Paul Gane, Maria Jesus Martin, Shyamala Sundaram, Yasmin Alam-Faruque, Ioannis Xenarios, Alan Bridge, WM Chan, Guoying Qi, L Famiglietti, Christian J. A. Sigrist, Nadine Gruaz-Gumowski, Chantal Hulo, Hermann Zellner, Matthew Corbett, Monica Pozzato, Thierry Lombardot, S Staehli, Jerven Bolleman, Sylvain Poux, Séverine Duvaud, Tony Sawford, Chuming Chen, Xavier Watkins, Yuqi Wang, Elisabeth Gasteiger, Kati Laiho, Qinghua Wang, M Bingley, Lydie Bougueleret, Kristian B. Axelsen, Yongxing Chen, Salvo Paesano, Andrew Nightingale, Nicole Redaschi, Emma Hatton-Ellis, John S. Garavelli, Delphine Baratin, Darren A. Natale, Gayatri Chavali, E de Castro, Leslie Arminski, Damien Lieberherr, Elena Cibrian-Uhalte, Catherine Rivoire, Bernd Roechert, Yerramalla, Hongzhan Huang, Alistair MacDougall, Edd Turner, Maria Victoria Schneider, Aleksandra Shypitsyna, Jie Zhang, Michele Magrane, Dolnide Dornevil, Lara, M Donnelly, F. Fazzini, Andrea H. Auchincloss, Emanuele Alpi, Benoit Bely, Brigitte Boeckmann, Rolf Apweiler, Rachael P. Huntley, Lionel Breuza, Sangya Pundir, Lorenzo Cerutti, Tunca Doğan, EB Casanova, P van Rensburg, Rabie Saidi, Jie Luo, Mickael Goujon, Laure Verbregue, Tony Wardell, W Liu, Andre Stutz, P Lemercier, Hamish McWilliam, Ivo Pedruzzi, P-A Binz, Sebastien Gehant, Béatrice A. Cuche, Carlos Bonilla, Duncan Legge, C. R. Vinayaka, Anne Morgat, Diego Poggioli, J Arganiska, Teresa Batista Neto, Emmanuel Boutet, Florence Jungo, Ursula Hinz, Parit Bansal, Sandra Orchard, Ricardo Antunes, Manuela Pruess, M Feuermann, S. Rosanoff, Claire O'Donovan, Cecilia N. Arighi, J. James, M Doche, Elisabeth Coudert, M De Giorgi, Reija Hieta, Sandrine Pilbout, Arnaud Gos, Michael Tognolli, Leyla Jael Garcia Castro, and Lucila Aimo
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Proteomics ,0303 health sciences ,Internet ,Representation (systemics) ,Genome database ,Proteins ,Molecular Sequence Annotation ,Computational biology ,Genomics ,Biology ,Ontology (information science) ,Universal Protein Resource ,II. Protein sequence and structure, motifs and domains ,03 medical and health sciences ,Annotation ,0302 clinical medicine ,Gene Ontology ,Sequence Analysis, Protein ,030220 oncology & carcinogenesis ,Genetics ,UniProt ,Databases, Protein ,030304 developmental biology - Abstract
The mission of the Universal Protein Resource (UniProt) (http://www.uniprot.org) is to provide the scientific community with a comprehensive, high-quality and freely accessible resource of protein sequences and functional annotation. It integrates, interprets and standardizes data from literature and numerous resources to achieve the most comprehensive catalog possible of protein information. The central activities are the biocuration of the UniProt Knowledgebase and the dissemination of these data through our Web site and web services. UniProt is produced by the UniProt Consortium, which consists of groups from the European Bioinformatics Institute (EBI), the SIB Swiss Institute of Bioinformatics (SIB) and the Protein Information Resource (PIR). UniProt is updated and distributed every 4 weeks and can be accessed online for searches or downloads.
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- 2013
19. Upregulation of reggie-1/flotillin-2 promotes axon regeneration in the rat optic nerve in vivo and neurite growth in vitro
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Deana Haralampieva, Jan C. Koch, Vsevolod Bodrikov, Uwe Michel, Claudia A. O. Stuermer, Aleksandra Shypitsyna, Gonzalo P. Solis, Mathias Bähr, Lars Tönges, and Paul Lingor
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Optic nerve crush ,Neurite ,Blotting, Western ,Biology ,Retinal ganglion ,lcsh:RC321-571 ,Mice ,chemistry.chemical_compound ,Downregulation and upregulation ,Transduction, Genetic ,ddc:570 ,Neurites ,medicine ,Animals ,Rats, Wistar ,Axon ,Growth cone ,Axon regeneration ,lcsh:Neurosciences. Biological psychiatry. Neuropsychiatry ,Reggie-1/flotillin-2 ,Regeneration (biology) ,Neurite outgrowth ,Membrane Proteins ,Optic Nerve ,Axons ,Nerve Regeneration ,Rats ,Up-Regulation ,Cell biology ,medicine.anatomical_structure ,Neurology ,chemistry ,Chondroitin sulfate proteoglycan ,Optic nerve ,Neuroscience ,Signal Transduction - Abstract
The ability of fish retinal ganglion cells (RGCs) to regenerate their axons was shown to require the re-expression and function of the two proteins reggie-1 and -2. RGCs in mammals fail to upregulate reggie expression and to regenerate axons after lesion suggesting the possibility that induced upregulation might promote regeneration. In the present study, RGCs in adult rats were induced to express reggie-1 by intravitreal injection of adeno-associated viral vectors (AAV2/1) expressing reggie-1 (AAV.R1-EGFP) 14d prior to optic nerve crush. Four weeks later, GAP-43-positive regenerating axons had crossed the lesion and grown into the nerve at significantly higher numbers and length (up to 5 mm) than the control transduced with AAV.EGFP. Consistently, after transduction with AAV.R1-EGFP as opposed to AAV.EGFP, primary RGCs in vitro grew long axons on chondroitin sulfate proteoglycan (CSPG) and Nogo-A, both glial cell-derived inhibitors of neurite growth, suggesting that reggie-1 can provide neurons with the ability to override inhibitors of neurite growth. This reggie-1-mediated enhancement of growth was reproduced in mouse hippocampal and N2a neurons which generated axons 40–60% longer than their control counterparts. This correlates with the reggie-1-dependent activation of Src and PI3 kinase (PI3K), of the Rho family GTPase Rac1 and downstream effectors such as cofilin. This increased growth also depends on TC10, the GTPase involved in cargo delivery to the growth cone. Thus, the upregulation of reggie-1 in mammalian neurons provides nerve cells with neuron-intrinsic properties required for axon growth and successful regeneration in the adult mammalian CNS.
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- 2013
20. Additional file 1 of An expanded evaluation of protein function prediction methods shows an improvement in accuracy
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Yuxiang Jiang, Oron, Tal Ronnen, Clark, Wyatt T., Bankapur, Asma R., D’Andrea, Daniel, Lepore, Rosalba, Funk, Christopher S., Indika Kahanda, Verspoor, Karin M., Ben-Hur, Asa, Koo, Da Chen Emily, Penfold-Brown, Duncan, Shasha, Dennis, Youngs, Noah, Bonneau, Richard, Lin, Alexandra, Sahraeian, Sayed M. E., Martelli, Pier Luigi, Profiti, Giuseppe, Casadio, Rita, Renzhi Cao, Zhaolong Zhong, Jianlin Cheng, Altenhoff, Adrian, Skunca, Nives, Dessimoz, Christophe, Tunca Dogan, Hakala, Kai, Suwisa Kaewphan, Mehryary, Farrokh, Salakoski, Tapio, Ginter, Filip, Fang, Hai, Smithers, Ben, Oates, Matt, Gough, Julian, Törönen, Petri, Koskinen, Patrik, Holm, Liisa, Ching-Tai Chen, Hsu, Wen-Lian, Bryson, Kevin, Cozzetto, Domenico, Minneci, Federico, Jones, David T., Chapman, Samuel, Dukka BKC, Ishita K. Khan, Kihara, Daisuke, Ofer, Dan, Rappoport, Nadav, Stern, Amos, Cibrian-Uhalte, Elena, Denny, Paul, Foulger, Rebecca E., Hieta, Reija, Legge, Duncan, Lovering, Ruth C., Magrane, Michele, Melidoni, Anna N., Mutowo-Meullenet, Prudence, Pichler, Klemens, Shypitsyna, Aleksandra, Li, Biao, Pooya Zakeri, ElShal, Sarah, Léon-Charles Tranchevent, Sayoni Das, Dawson, Natalie L., Lee, David, Lees, Jonathan G., Sillitoe, Ian, Prajwal Bhat, Nepusz, Tamás, Romero, Alfonso E., Sasidharan, Rajkumar, Haixuan Yang, Paccanaro, Alberto, Gillis, Jesse, Sedeño-Cortés, Adriana E., Pavlidis, Paul, Feng, Shou, Cejuela, Juan M., Goldberg, Tatyana, Hamp, Tobias, Richter, Lothar, Salamov, Asaf, Gabaldon, Toni, Marcet-Houben, Marina, Supek, Fran, Qingtian Gong, Ning, Wei, Yuanpeng Zhou, Weidong Tian, Falda, Marco, Fontana, Paolo, Lavezzo, Enrico, Toppo, Stefano, Ferrari, Carlo, Giollo, Manuel, Piovesan, Damiano, Tosatto, Silvio C.E., Pozo, Angela Del, Fernández, José M., Maietta, Paolo, Valencia, Alfonso, Tress, Michael L., Benso, Alfredo, Carlo, Stefano Di, Politano, Gianfranco, Savino, Alessandro, Hafeez Ur Rehman, Re, Matteo, Mesiti, Marco, Valentini, Giorgio, Bargsten, Joachim W., Dijk, Aalt D. J. Van, Gemovic, Branislava, Glisic, Sanja, Vladmir Perovic, Veljkovic, Veljko, Veljkovic, Nevena, Danillo C. Almeida-E-Silva, Vencio, Ricardo Z. N., Malvika Sharan, Vogel, Jörg, Lakesh Kansakar, Shanshan Zhang, Vucetic, Slobodan, Wang, Zheng, Sternberg, Michael J. E., Wass, Mark N., Huntley, Rachael P., Martin, Maria J., O’Donovan, Claire, Robinson, Peter N., Moreau, Yves, Tramontano, Anna, Babbitt, Patricia C., Brenner, Steven E., Linial, Michal, Orengo, Christine A., Rost, Burkhard, Greene, Casey S., Mooney, Sean D., Friedberg, Iddo, and Radivojac, Predrag
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A document containing a subset of CAFA2 analyses that are equivalent to those provided about the CAFA1 experiment in the CAFA1 supplement. (PDF 11100 kb)
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- 2016
- Full Text
- View/download PDF
21. Extending gene ontology in the context of extracellular RNA and vesicle communication
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LS Celbiologie-Algemeen, dB&C I&I, Cheung, Kei-Hoi, Keerthikumar, Shivakumar, Roncaglia, Paola, Subramanian, Sai Lakshmi, Roth, Matthew E, Samuel, Monisha, Anand, Sushma, Gangoda, Lahiru, Gould, Stephen, Alexander, Roger, Galas, David, Gerstein, Mark B, Hill, Andrew F, Kitchen, Robert R, Lötvall, Jan, Patel, Tushar, Procaccini, Dena C, Quesenberry, Peter, Rozowsky, Joel, Raffai, Robert L, Shypitsyna, Aleksandra, Su, Andrew I, Théry, Clotilde, Vickers, Kasey, Wauben, Marca H M, Mathivanan, Suresh, Milosavljevic, Aleksandar, Laurent, Louise C, LS Celbiologie-Algemeen, dB&C I&I, Cheung, Kei-Hoi, Keerthikumar, Shivakumar, Roncaglia, Paola, Subramanian, Sai Lakshmi, Roth, Matthew E, Samuel, Monisha, Anand, Sushma, Gangoda, Lahiru, Gould, Stephen, Alexander, Roger, Galas, David, Gerstein, Mark B, Hill, Andrew F, Kitchen, Robert R, Lötvall, Jan, Patel, Tushar, Procaccini, Dena C, Quesenberry, Peter, Rozowsky, Joel, Raffai, Robert L, Shypitsyna, Aleksandra, Su, Andrew I, Théry, Clotilde, Vickers, Kasey, Wauben, Marca H M, Mathivanan, Suresh, Milosavljevic, Aleksandar, and Laurent, Louise C
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- 2016
22. An expanded evaluation of protein function prediction methods shows an improvement in accuracy
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Jiang, Y, Oron, TR, Clark, WT, Bankapur, AR, D'Andrea, D, Lepore, R, Funk, CS, Kahanda, I, Verspoor, KM, Ben-Hur, A, Koo, DCE, Penfold-Brown, D, Shasha, D, Youngs, N, Bonneau, R, Lin, A, Sahraeian, SME, Martelli, PL, Profiti, G, Casadio, R, Cao, R, Zhong, Z, Cheng, J, Altenhoff, A, Skunca, N, Dessimoz, C, Dogan, T, Hakala, K, Kaewphan, S, Mehryary, F, Salakoski, T, Ginter, F, Fang, H, Smithers, B, Oates, M, Gough, J, Toronen, P, Koskinen, P, Holm, L, Chen, C-T, Hsu, W-L, Bryson, K, Cozzetto, D, Minneci, F, Jones, DT, Chapman, S, Dukka, BKC, Khan, IK, Kihara, D, Ofer, D, Rappoport, N, Stern, A, Cibrian-Uhalte, E, Denny, P, Foulger, RE, Hieta, R, Legge, D, Lovering, RC, Magrane, M, Melidoni, AN, Mutowo-Meullenet, P, Pichler, K, Shypitsyna, A, Li, B, Zakeri, P, ElShal, S, Tranchevent, L-C, Das, S, Dawson, NL, Lee, D, Lees, JG, Sillitoe, I, Bhat, P, Nepusz, T, Romero, AE, Sasidharan, R, Yang, H, Paccanaro, A, Gillis, J, Sedeno-Cortes, AE, Pavlidis, P, Feng, S, Cejuela, JM, Goldberg, T, Hamp, T, Richter, L, Salamov, A, Gabaldon, T, Marcet-Houben, M, Supek, F, Gong, Q, Ning, W, Zhou, Y, Tian, W, Falda, M, Fontana, P, Lavezzo, E, Toppo, S, Ferrari, C, Giollo, M, Piovesan, D, Tosatto, SCE, del Pozo, A, Fernandez, JM, Maietta, P, Valencia, A, Tress, ML, Benso, A, Di Carlo, S, Politano, G, Savino, A, Rehman, HU, Re, M, Mesiti, M, Valentini, G, Bargsten, JW, van Dijk, ADJ, Gemovic, B, Glisic, S, Perovic, V, Veljkovic, V, Veljkovic, N, Almeida-e-Silva, DC, Vencio, RZN, Sharan, M, Vogel, J, Kansakar, L, Zhang, S, Vucetic, S, Wang, Z, Sternberg, MJE, Wass, MN, Huntley, RP, Martin, MJ, O'Donovan, C, Robinson, PN, Moreau, Y, Tramontano, A, Babbitt, PC, Brenner, SE, Linial, M, Orengo, CA, Rost, B, Greene, CS, Mooney, SD, Friedberg, I, Radivojac, P, Jiang, Y, Oron, TR, Clark, WT, Bankapur, AR, D'Andrea, D, Lepore, R, Funk, CS, Kahanda, I, Verspoor, KM, Ben-Hur, A, Koo, DCE, Penfold-Brown, D, Shasha, D, Youngs, N, Bonneau, R, Lin, A, Sahraeian, SME, Martelli, PL, Profiti, G, Casadio, R, Cao, R, Zhong, Z, Cheng, J, Altenhoff, A, Skunca, N, Dessimoz, C, Dogan, T, Hakala, K, Kaewphan, S, Mehryary, F, Salakoski, T, Ginter, F, Fang, H, Smithers, B, Oates, M, Gough, J, Toronen, P, Koskinen, P, Holm, L, Chen, C-T, Hsu, W-L, Bryson, K, Cozzetto, D, Minneci, F, Jones, DT, Chapman, S, Dukka, BKC, Khan, IK, Kihara, D, Ofer, D, Rappoport, N, Stern, A, Cibrian-Uhalte, E, Denny, P, Foulger, RE, Hieta, R, Legge, D, Lovering, RC, Magrane, M, Melidoni, AN, Mutowo-Meullenet, P, Pichler, K, Shypitsyna, A, Li, B, Zakeri, P, ElShal, S, Tranchevent, L-C, Das, S, Dawson, NL, Lee, D, Lees, JG, Sillitoe, I, Bhat, P, Nepusz, T, Romero, AE, Sasidharan, R, Yang, H, Paccanaro, A, Gillis, J, Sedeno-Cortes, AE, Pavlidis, P, Feng, S, Cejuela, JM, Goldberg, T, Hamp, T, Richter, L, Salamov, A, Gabaldon, T, Marcet-Houben, M, Supek, F, Gong, Q, Ning, W, Zhou, Y, Tian, W, Falda, M, Fontana, P, Lavezzo, E, Toppo, S, Ferrari, C, Giollo, M, Piovesan, D, Tosatto, SCE, del Pozo, A, Fernandez, JM, Maietta, P, Valencia, A, Tress, ML, Benso, A, Di Carlo, S, Politano, G, Savino, A, Rehman, HU, Re, M, Mesiti, M, Valentini, G, Bargsten, JW, van Dijk, ADJ, Gemovic, B, Glisic, S, Perovic, V, Veljkovic, V, Veljkovic, N, Almeida-e-Silva, DC, Vencio, RZN, Sharan, M, Vogel, J, Kansakar, L, Zhang, S, Vucetic, S, Wang, Z, Sternberg, MJE, Wass, MN, Huntley, RP, Martin, MJ, O'Donovan, C, Robinson, PN, Moreau, Y, Tramontano, A, Babbitt, PC, Brenner, SE, Linial, M, Orengo, CA, Rost, B, Greene, CS, Mooney, SD, Friedberg, I, and Radivojac, P
- Abstract
BACKGROUND: A major bottleneck in our understanding of the molecular underpinnings of life is the assignment of function to proteins. While molecular experiments provide the most reliable annotation of proteins, their relatively low throughput and restricted purview have led to an increasing role for computational function prediction. However, assessing methods for protein function prediction and tracking progress in the field remain challenging. RESULTS: We conducted the second critical assessment of functional annotation (CAFA), a timed challenge to assess computational methods that automatically assign protein function. We evaluated 126 methods from 56 research groups for their ability to predict biological functions using Gene Ontology and gene-disease associations using Human Phenotype Ontology on a set of 3681 proteins from 18 species. CAFA2 featured expanded analysis compared with CAFA1, with regards to data set size, variety, and assessment metrics. To review progress in the field, the analysis compared the best methods from CAFA1 to those of CAFA2. CONCLUSIONS: The top-performing methods in CAFA2 outperformed those from CAFA1. This increased accuracy can be attributed to a combination of the growing number of experimental annotations and improved methods for function prediction. The assessment also revealed that the definition of top-performing algorithms is ontology specific, that different performance metrics can be used to probe the nature of accurate predictions, and the relative diversity of predictions in the biological process and human phenotype ontologies. While there was methodological improvement between CAFA1 and CAFA2, the interpretation of results and usefulness of individual methods remain context-dependent.
- Published
- 2016
23. Extending gene ontology in the context of extracellular RNA and vesicle communication
- Author
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Cheung, K-H, Keerthikumar, S, Roncaglia, P, Subramanian, SL, Roth, ME, Samuel, M, Anand, S, Gangoda, L, Gould, S, Alexander, R, Galas, D, Gerstein, MB, Hill, AF, Kitchen, RR, Lotvall, J, Patel, T, Procaccini, DC, Quesenberry, P, Rozowsky, J, Raffai, RL, Shypitsyna, A, Su, AI, Thery, C, Vickers, K, Wauben, MHM, Mathivanan, S, Milosavljevic, A, Laurent, LC, Cheung, K-H, Keerthikumar, S, Roncaglia, P, Subramanian, SL, Roth, ME, Samuel, M, Anand, S, Gangoda, L, Gould, S, Alexander, R, Galas, D, Gerstein, MB, Hill, AF, Kitchen, RR, Lotvall, J, Patel, T, Procaccini, DC, Quesenberry, P, Rozowsky, J, Raffai, RL, Shypitsyna, A, Su, AI, Thery, C, Vickers, K, Wauben, MHM, Mathivanan, S, Milosavljevic, A, and Laurent, LC
- 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.
- Published
- 2016
24. UniProt: a hub for protein information
- Author
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Ursula Hinz, Prudence Mutowo, Laure Verbregue, Weizhong Li, Nadine Gruaz-Gumowski, Chantal Hulo, Hermann Zellner, Shyamala Sundaram, P Lemercier, Guoying Qi, Parit Bansal, Tony Sawford, Sebastien Gehant, Delphine Baratin, Francesco Fazzini, Monica Pozzato, Séverine Duvaud, Lai-Su L. Yeh, Nicole Redaschi, Emma Hatton-Ellis, Darren A. Natale, Damien Lieberherr, Luis Figueira, Bernd Roechert, Borisas Bursteinas, Gayatri Chavali, Brigitte Boeckmann, Cristina Casal-Casas, Baris E. Suzek, Cathy H. Wu, Paul Gane, Ghislaine Argoud-Puy, Klemens Pichler, Rachael P. Huntley, Sangya Pundir, Alan Bridge, Edouard de Castro, Benoit Bely, Kristian B. Axelsen, Emmanuel Boutet, Andre Stutz, Penelope Garmiri, Christian J. A. Sigrist, John S. Garavelli, Rolf Apweiler, Peter B. McGarvey, Patrick Masson, Maria Jesus Martin, K Sonesson, Xavier Watkins, Ioannis Xenarios, Vladimir Volynkin, Hamish McWilliam, Mark Bingley, Guillaume Keller, Hongzhan Huang, Rabie Saidi, Sylvain Poux, Tunca Doğan, Yuqi Wang, Diego Poggioli, Rodrigo Lopez, Alistair MacDougall, Kati Laiho, Qinghua Wang, W Liu, Carlos Bonilla, Duncan Legge, C. R. Vinayaka, Anne Morgat, Thierry Lombardot, Jerven Bolleman, Nevila Nouspikel, Aleksandra Shypitsyna, Emanuele Alpi, Yongxing Chen, Anne Lise Veuthey, Andrew Nightingale, Béatrice A. Cuche, Alex Bateman, Ramona Britto, Alan Wilter Sousa da Silva, Jie Luo, Lionel Breuza, Marie Claude Blatter, Elena Cibrian-Uhalte, Michel Schneider, Chuming Chen, Michele Magrane, L Famiglietti, Meher Shruti Yerramalla, Lydie Bougueleret, Vivienne Baillie Gerritsen, Anne Estreicher, Dolnide Dornevil, Catherine Rivoire, Jian Zhang, S Staehli, Andrew Peter Cowley, Tony Wardell, Ivo Pedruzzi, Andrea H. Auchincloss, Salvo Paesano, Elisabeth Gasteiger, Luis Pureza, Marc Feuermann, Leslie Arminski, Xavier D. Martin, Teresa Batista Neto, Steven Rosanoff, Florence Jungo, Sandra Orchard, Claire O'Donovan, Elisabeth Coudert, Ricardo Antunes, Sandrine Pilbout, Vicente Lara, Arnaud Gos, Reija Hieta, Manuela Pruess, Joanna Arganiska, Edward Turner, Maurizio De Giorgi, M Doche, Cecilia N. Arighi, Michael Tognolli, Leyla Jael Garcia Castro, and Lucila Aimo
- Subjects
Proteome ,Computer science ,Molecular Sequence Annotation ,Computational biology ,Accession number (bioinformatics) ,DNA sequencing ,World Wide Web ,Identifier ,Annotation ,Sequence Analysis, Protein ,Genetics ,Database Issue ,natural sciences ,UniProt ,Databases, Protein - Abstract
UniProt is an important collection of protein sequences and their annotations, which has doubled in size to 80 million sequences during the past year. This growth in sequences has prompted an extension of UniProt accession number space from 6 to 10 characters. An increasing fraction of new sequences are identical to a sequence that already exists in the database with the majority of sequences coming from genome sequencing projects. We have created a new proteome identifier that uniquely identifies a particular assembly of a species and strain or subspecies to help users track the provenance of sequences. We present a new website that has been designed using a user-experience design process. We have introduced an annotation score for all entries in UniProt to represent the relative amount of knowledge known about each protein. These scores will be helpful in identifying which proteins are the best characterized and most informative for comparative analysis. All UniProt data is provided freely and is available on the web at http://www.uniprot.org/.
- Published
- 2014
25. An expanded evaluation of protein function prediction methods shows an improvement in accuracy
- Author
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Jiang, Yuxiang, primary, Oron, Tal Ronnen, additional, Clark, Wyatt T., additional, Bankapur, Asma R., additional, D’Andrea, Daniel, additional, Lepore, Rosalba, additional, Funk, Christopher S., additional, Kahanda, Indika, additional, Verspoor, Karin M., additional, Ben-Hur, Asa, additional, Koo, Da Chen Emily, additional, Penfold-Brown, Duncan, additional, Shasha, Dennis, additional, Youngs, Noah, additional, Bonneau, Richard, additional, Lin, Alexandra, additional, Sahraeian, Sayed M. E., additional, Martelli, Pier Luigi, additional, Profiti, Giuseppe, additional, Casadio, Rita, additional, Cao, Renzhi, additional, Zhong, Zhaolong, additional, Cheng, Jianlin, additional, Altenhoff, Adrian, additional, Skunca, Nives, additional, Dessimoz, Christophe, additional, Dogan, Tunca, additional, Hakala, Kai, additional, Kaewphan, Suwisa, additional, Mehryary, Farrokh, additional, Salakoski, Tapio, additional, Ginter, Filip, additional, Fang, Hai, additional, Smithers, Ben, additional, Oates, Matt, additional, Gough, Julian, additional, Törönen, Petri, additional, Koskinen, Patrik, additional, Holm, Liisa, additional, Chen, Ching-Tai, additional, Hsu, Wen-Lian, additional, Bryson, Kevin, additional, Cozzetto, Domenico, additional, Minneci, Federico, additional, Jones, David T., additional, Chapman, Samuel, additional, BKC, Dukka, additional, Khan, Ishita K., additional, Kihara, Daisuke, additional, Ofer, Dan, additional, Rappoport, Nadav, additional, Stern, Amos, additional, Cibrian-Uhalte, Elena, additional, Denny, Paul, additional, Foulger, Rebecca E., additional, Hieta, Reija, additional, Legge, Duncan, additional, Lovering, Ruth C., additional, Magrane, Michele, additional, Melidoni, Anna N., additional, Mutowo-Meullenet, Prudence, additional, Pichler, Klemens, additional, Shypitsyna, Aleksandra, additional, Li, Biao, additional, Zakeri, Pooya, additional, ElShal, Sarah, additional, Tranchevent, Léon-Charles, additional, Das, Sayoni, additional, Dawson, Natalie L., additional, Lee, David, additional, Lees, Jonathan G., additional, Sillitoe, Ian, additional, Bhat, Prajwal, additional, Nepusz, Tamás, additional, Romero, Alfonso E., additional, Sasidharan, Rajkumar, additional, Yang, Haixuan, additional, Paccanaro, Alberto, additional, Gillis, Jesse, additional, Sedeño-Cortés, Adriana E., additional, Pavlidis, Paul, additional, Feng, Shou, additional, Cejuela, Juan M., additional, Goldberg, Tatyana, additional, Hamp, Tobias, additional, Richter, Lothar, additional, Salamov, Asaf, additional, Gabaldon, Toni, additional, Marcet-Houben, Marina, additional, Supek, Fran, additional, Gong, Qingtian, additional, Ning, Wei, additional, Zhou, Yuanpeng, additional, Tian, Weidong, additional, Falda, Marco, additional, Fontana, Paolo, additional, Lavezzo, Enrico, additional, Toppo, Stefano, additional, Ferrari, Carlo, additional, Giollo, Manuel, additional, Piovesan, Damiano, additional, Tosatto, Silvio C.E., additional, del Pozo, Angela, additional, Fernández, José M., additional, Maietta, Paolo, additional, Valencia, Alfonso, additional, Tress, Michael L., additional, Benso, Alfredo, additional, Di Carlo, Stefano, additional, Politano, Gianfranco, additional, Savino, Alessandro, additional, Rehman, Hafeez Ur, additional, Re, Matteo, additional, Mesiti, Marco, additional, Valentini, Giorgio, additional, Bargsten, Joachim W., additional, van Dijk, Aalt D. J., additional, Gemovic, Branislava, additional, Glisic, Sanja, additional, Perovic, Vladmir, additional, Veljkovic, Veljko, additional, Veljkovic, Nevena, additional, Almeida-e-Silva, Danillo C., additional, Vencio, Ricardo Z. N., additional, Sharan, Malvika, additional, Vogel, Jörg, additional, Kansakar, Lakesh, additional, Zhang, Shanshan, additional, Vucetic, Slobodan, additional, Wang, Zheng, additional, Sternberg, Michael J. E., additional, Wass, Mark N., additional, Huntley, Rachael P., additional, Martin, Maria J., additional, O’Donovan, Claire, additional, Robinson, Peter N., additional, Moreau, Yves, additional, Tramontano, Anna, additional, Babbitt, Patricia C., additional, Brenner, Steven E., additional, Linial, Michal, additional, Orengo, Christine A., additional, Rost, Burkhard, additional, Greene, Casey S., additional, Mooney, Sean D., additional, Friedberg, Iddo, additional, and Radivojac, Predrag, additional
- Published
- 2016
- Full Text
- View/download PDF
26. Origin of Nogo-A by Domain Shuffling in an Early Jawed Vertebrate
- Author
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Edward Málaga-Trillo, Aleksandra Shypitsyna, Claudia A. O. Stuermer, and Alexander Reuter
- Subjects
Gene isoform ,Nogo Proteins ,Molecular Sequence Data ,Neurocan ,Branchiostoma floridae ,biology.animal ,ddc:570 ,Gene duplication ,Genetics ,Animals ,Humans ,Protein Isoforms ,Amino Acid Sequence ,Molecular Biology ,Gene ,Phylogeny ,Ecology, Evolution, Behavior and Systematics ,Cephalochordate ,biology ,reticulon ,Fishes ,axon regeneration ,Vertebrate ,Anatomy ,biology.organism_classification ,Biological Evolution ,Axons ,Divergent evolution ,neurite outgrowth inhibitors ,Jaw ,Evolutionary biology ,Vertebrates ,neurocan ,Nogo-A ,Sequence Alignment ,Myelin Proteins - Abstract
Unlike mammals, fish are able to regenerate axons in their central nervous system. This difference has been partly attributed to the loss/acquisition of inhibitory proteins during evolution. Nogo-A--the longest isoform of the reticulon4 (rtn4) gene product--is commonly found in mammalian myelin where it acts as a potent inhibitor of axonal regeneration. Interestingly, fish RTN4 isoforms were previously reported to lack the most inhibitory Nogo-A-specific region (NSR). Nevertheless, fish axons collapse on contact with mammalian NSR, suggesting that fish possess a functional Nogo-A receptor but not its ligand. To reconcile these findings, we revisited the early evolution of rtn4. Mining of current genome databases established the unequivocal presence of NSR-coding sequences in fish rtn4 paralogues. Further comparative analyses indicate that the common ancestor of fish and tetrapods had an NSR-coding rtn4 gene, which underwent duplication and divergent evolution in bony fish. Our genomic survey also revealed that the cephalochordate Branchiostoma floridae contains a single rtn gene lacking the NSR. Hence, Nogo-A most probably arose independently in the rtn4 gene of a gnathostome ancestor before the split of the fish and tetrapod lineages. Close examination of the NSR uncovered clusters of structural and sequential similarities with neurocan (NCAN), an inhibitory proteoglycan of the glial scar. Notably, the shared presence of transposable elements in ncan and rtn4 genes suggests that Nogo-A originated via insertion of an ncan-like sequence into the rtn4 gene of an early jawed vertebrate with myelinated axons.
- Published
- 2011
27. Exploring the evolution and the functional role of nogo/rtn4 gene during axonal regeneration in zebrafish
- Author
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Shypitsyna, Aleksandra
- Subjects
fish ,Evolution [gnd] ,Fisch [gnd] ,Sehsystem ,ddc:570 ,regeneration ,evolution ,Visuelles System [gnd] ,visual system ,+[gnd]%22">Regeneration ,[gnd] Nogo-66 ,Nogo-A ,Neurobiologie [gnd] - Abstract
In contrast to fish, mammals are unable to regenerate lesioned fiber tracts in the central nervous system (CNS). Two major factors are postulated to be responsible: intrinsic neuronal properties and the glial cell environment. Upon injury several types of molecules produced by glial cells elicit inhibitory effect on neurite outgrowth. One of these, oligodendrocyte-derived RTN4/Nogo was demonstrated to act as a potent inhibitor of axon regeneration and to block neurite extension via two domains: the Nogo-A-specific region and Nogo-66 located in N- and C-terminal parts of the protein, respectively.The present work focuses on the evolution of RTN4/Nogo and its inhibitory domains in chordates as well as their functional characterization in fish. In order to comprehend the origin of the Nogo-A-specific region (NSR) all available genomes of chordates were analyzed. Our data indicate that the common ancestor of fish and tetrapods had an NSR-coding rtn4 gene, which underwent duplication and divergent evolution in bony fish. Thus, in the zebrafish, the NSR was lost in rtn4 but retained in its duplicate rtn6, whereas in the pufferfish, the NSR was retained in rtn4 and the entire rtn6 gene was deleted. Distant homology screening in combination with protein architecture analysis reveals the relation of this region to CSPG neurocan on the levels of domain organization and sequence similarity, such as shared presence of the putative integrin-binding motifs. Therefore, Nogo-A most likely originated from the insertion of a neurocan DNA sequence into an ancestral rtn4 gene. Notably, the proposed timing of this event coincides with the acquisition of jaws and myelin by vertebrates. These results not only shed light on the evolution of Nogo-A, but may facilitate the identification of its molecular receptor(s).Although the NSRs in fish and mammals share only 18% identity on the primary structure level, zebrafish Nogo-66 is 66% identical and more than 80% similar to its rat homologue. This notion raises the question whether the fish peptide is able to exert neurite outgrowth inhibition. Surprisingly, in the outgrowth, collapse and contact assays zebrafish Nogo-66 appeared to be growth-permissive for fish and mammalian neurons, quite in contrast to its rat Nogo-66 homologue which inhibits growth. Upon binding to their common receptor NgR1, the rat peptide in contrast to zebrafish Nogo-66 elicits phosphorylation of the downstream effector cofilin which leads to actin filament disassembly. These data are in agreement with the apparent absence of neurite outgrowth inhibitors in fish CNS. However, it is not clear how so similar peptides can exert different responses. Thus, we have analyzed Nogo-66/NgR1 interaction combining coevolutionary and structure modeling approaches. Our results demonstrate that both proteins are already present in cephalochordates but began to coevolve only after fish-tetrapod split. Based on conservation analysis of primary and tertiary structures of these molecules and on published functional data we were able to reconstruct the receptor-ligand complex and model Nogo-66/NgR1 interactions in mammals and fish. The obtained results are in agreement with the previous notion that Nogo-66/NgR1-induced signal transduction becomes inhibitory during/after the fish-tetrapod transition.These extensive analyses of evolution of both inhibitory domains of RTN4/Nogo may help to understand why the ability to regenerate lesioned axons in the CNS became restricted during vertebrate evolution. Moreover, the combination of structural and functional approaches can provide the necessary information which molecular changes during RTN4 evolution are responsible for the acquisition of its inhibitory properties.
- Published
- 2010
28. No Nogo66- and NgR-Mediated Inhibition of Regenerating Axons in the Zebrafish Optic Nerve
- Author
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Houari Abdesselem, Aleksandra Shypitsyna, Gonzalo P. Solis, Claudia A. O. Stuermer, and Vsevolod Bodrikov
- Subjects
Retinal Ganglion Cells ,Glycosylphosphatidylinositols ,Nogo Proteins ,Growth Cones ,Receptors, Cell Surface ,In Vitro Techniques ,Inhibitory postsynaptic potential ,Hippocampus ,Retina ,Mice ,Species Specificity ,ddc:570 ,Neurites ,medicine ,Animals ,Humans ,Binding site ,Axon ,Receptor ,Zebrafish ,Neurons ,biology ,General Neuroscience ,Optic Nerve ,Articles ,Zebrafish Proteins ,Cofilin ,biology.organism_classification ,Axons ,Nerve Regeneration ,Rats ,Cell biology ,medicine.anatomical_structure ,Actin Depolymerizing Factors ,Phosphorylation ,Signal transduction ,Neuroscience ,Myelin Proteins ,HeLa Cells ,Signal Transduction - Abstract
In contrast to mammals, lesioned axons in the zebrafish (ZF) optic nerve regenerate and restore vision. This correlates with the absence of the NogoA-specific N-terminal domains from the ZFnogo/rtn-4(reticulon-4) gene that inhibits regeneration in mammals. However, mammaliannogo/rtn-4carries a second inhibitory C-terminal domain, Nogo-66, being 70% identical with ZF-Nogo66. The present study examines, (1) whether ZF-Nogo66 is inhibitory and effecting similar signaling pathways upon Nogo66-binding to the Nogo66 receptor NgR and its coreceptors, and (2) whether Rat-Nogo66 on fish, and ZF-Nogo66 on mouse neurons, cause inhibition via NgR. Our results from “outgrowth, collapse and contact assays” suggest, surprisingly, that ZF-Nogo66 is growth-permissive for ZF and mouse neurons, quite in contrast to its Rat-Nogo66 homolog which inhibits growth. The opposite effects of ZF- and Rat-Nogo66 are, in both fish and mouse, transmitted by GPI (glycosylphosphatidylinositol)-anchored receptors, including NgR. The high degree of sequence homology in the predicted binding site is consistent with the ability of ZF- and mammalian-Nogo66 to bind to NgRs of both species. Yet, Rat-Nogo66 elicits phosphorylation of the downstream effector cofilin whereas ZF-Nogo66 has no influence on cofilin phosphorylation—probably because of significantly different Rat- versus ZF-Nogo66 sequences outside of the receptor-binding region effecting, by speculation, recruitment of a different set of coreceptors or microdomain association of NgR. Thus, not only was the NogoA-specific domain lost in fish, but Nogo66, the second inhibitory domain in mammals, and its signaling upon binding to NgR, was modified so that ZF-Nogo/RTN-4 does not impair axon regeneration.
- Published
- 2009
29. The GOA database: Gene Ontology annotation updates for 2015
- Author
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Huntley, Rachael P., primary, Sawford, Tony, additional, Mutowo-Meullenet, Prudence, additional, Shypitsyna, Aleksandra, additional, Bonilla, Carlos, additional, Martin, Maria J., additional, and O'Donovan, Claire, additional
- Published
- 2014
- Full Text
- View/download PDF
30. Upregulation of reggie-1/flotillin-2 promotes axon regeneration in the rat optic nerve in vivo and neurite growth in vitro
- Author
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Koch, Jan C., primary, Solis, Gonzalo P., additional, Bodrikov, Vsevolod, additional, Michel, Uwe, additional, Haralampieva, Deana, additional, Shypitsyna, Aleksandra, additional, Tönges, Lars, additional, Bähr, Mathias, additional, Lingor, Paul, additional, and Stuermer, Claudia A.O., additional
- Published
- 2013
- Full Text
- View/download PDF
31. Origin of Nogo-A by Domain Shuffling in an Early Jawed Vertebrate
- Author
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Shypitsyna, A., primary, Malaga-Trillo, E., additional, Reuter, A., additional, and Stuermer, C. A. O., additional
- Published
- 2010
- Full Text
- View/download PDF
32. No Nogo66- and NgR-Mediated Inhibition of Regenerating Axons in the Zebrafish Optic Nerve
- Author
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Abdesselem, Houari, primary, Shypitsyna, Aleksandra, additional, Solis, Gonzalo P., additional, Bodrikov, Vsevolod, additional, and Stuermer, Claudia A. O., additional
- Published
- 2009
- Full Text
- View/download PDF
33. [Role of adenoviruses in the etiology of respiratory tract diseases]
- Author
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S V, Pervachenko, S A, Bereznyts'ka, V G, Shypitsyna, and E I, Zolotarevs'ka
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Adenoviridae Infections ,Pneumonia, Viral ,Infant, Newborn ,Humans ,Infant ,Otitis ,Respiratory Tract Infections ,Infant, Newborn, Diseases - Published
- 1965
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