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22 results on '"Lydie Bougueleret"'

1. Taxon sampling unequally affects individual nodes in a phylogenetic tree: consequences for model gene tree construction in SwissTree

Author

Adrian M. Altenhoff, Evgenia V. Kriventseva, Ioannis Xenarios, Brigitte Boeckmann, Christophe Dessimoz, Lydie Bougueleret, David Dylus, Sébastien Moretti, Toni Gabaldón, C-M Train, and Eyal Privman

Subjects
0303 health sciences, Phylogenetic tree, Ecology, 0206 medical engineering, Locus (genetics), 02 engineering and technology, Phylogenetic network, Biology, 03 medical and health sciences, Tree (data structure), Phylogenetics, Evolutionary biology, Tree rearrangement, Computational phylogenetics, Gene family, 020602 bioinformatics, 030304 developmental biology
Abstract

Medium to large phylogenetic gene trees constructed from datasets of different species density and taxonomic range are rarely topologically consistent because of missing phylogenetic signal, non-phylogenetic signal and error. In this study, we first use simulations to show that taxon sampling unequally affects nodes in a gene tree, which likely contributes to controversial conclusions from taxon sampling experiments and contradicting species phylogenies such as for the boreoeutherians. Hence, because it is unlikely that a large gene tree can be reconstructed correctly based on a single optimized dataset, we take a two-step approach for the construction of model gene trees. First, stable and unstable clades are identified by comparing phylogenetic trees inferred from multiple datasets and data types (nucleotide, amino acid, codon) from the same gene family. Subsequently, data subsets are optimized for the analysis of individual uncertain clades. Results are summarized in form of a model tree that illustrates the evolutionary relationship of gene loci. A case study shows how a seemingly complex gene phylogeny becomes increasingly consistent with the reference species tree by attentive taxon sampling and subtree analysis. The procedure is progressively introduced to SwissTree (http://swisstree.vital-it.ch), a resource of high confidence model gene (locus) trees. Finally we demonstrate the usefulness of SwissTree for orthology benchmarking.

Published
2017
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2. The SwissLipids knowledgebase for lipid biology

Author

F. Gisou van der Goot, Howard Riezman, Fabrice P. A. David, Lou Götz, Anne Niknejad, Nevila Hyka-Nouspikel, Dmitry Kuznetsov, Anne Gleizes, Robin Liechti, Alan Bridge, Lydie Bougueleret, Ioannis Xenarios, and Lucila Aimo

Subjects
Statistics and Probability, 0303 health sciences, Databases, Factual, Knowledge Bases, Databases and Ontologies, Computational Biology, Lipid metabolism, Computational biology, Biology, Bioinformatics, Lipid Metabolism, Biochemistry, Lipids, Original Papers, Mass Spectrometry, Computer Science Applications, 03 medical and health sciences, Computational Mathematics, 0302 clinical medicine, Computational Theory and Mathematics, ddc:540, Humans, Molecular Biology, 030217 neurology & neurosurgery, 030304 developmental biology
Abstract

Motivation: Lipids are a large and diverse group of biological molecules with roles in membrane formation, energy storage and signaling. Cellular lipidomes may contain tens of thousands of structures, a staggering degree of complexity whose significance is not yet fully understood. High-throughput mass spectrometry-based platforms provide a means to study this complexity, but the interpretation of lipidomic data and its integration with prior knowledge of lipid biology suffers from a lack of appropriate tools to manage the data and extract knowledge from it. Results: To facilitate the description and exploration of lipidomic data and its integration with prior biological knowledge, we have developed a knowledge resource for lipids and their biology—SwissLipids. SwissLipids provides curated knowledge of lipid structures and metabolism which is used to generate an in silico library of feasible lipid structures. These are arranged in a hierarchical classification that links mass spectrometry analytical outputs to all possible lipid structures, metabolic reactions and enzymes. SwissLipids provides a reference namespace for lipidomic data publication, data exploration and hypothesis generation. The current version of SwissLipids includes over 244 000 known and theoretically possible lipid structures, over 800 proteins, and curated links to published knowledge from over 620 peer-reviewed publications. We are continually updating the SwissLipids hierarchy with new lipid categories and new expert curated knowledge. Availability: SwissLipids is freely available at http://www.swisslipids.org/. Contact: alan.bridge@isb-sib.ch Supplementary information: Supplementary data are available at Bioinformatics online.

Published
2017

3. The UniProt-GO Annotation database in 2011

Author

Rachael P. Huntley, Florence Jungo, Tony Sawford, Harminder Sehra, Shyamala Sundaram, Phillippe Lemercier, Bernd Roechert, Silvia Braconi-Quintaje, Guillaume Keller, Madelaine Moinat, Sylvain Poux, Paul Browne, Rolf Apweiler, Kristian B. Axelsen, Kati Laiho, Andre Stutz, Janet James, Catherine Rivoire, Diego Poggioli, Wei Mun Chan, Ivo Pedruzzi, Anne Estreicher, Silvia Jimenez, Paula Duek Roggli, Michael Gardner, Serenella Ferro-Rojas, Claire O'Donovan, Patrick Masson, Maria Jesus Martin, Michele Magrane, Elizabeth Coudert, Benoit Bely, Michael Tognolli, Emmanuel Boutet, Isabelle Cusin, Andrea H. Auchincloss, Yasmin Alam-Faruque, Klemens Pichler, Nadine Gruaz-Gumowski, Chantal Hulo, Ursula Hinz, Ruth Y. Eberhardt, Duncan Legge, L Famiglietti, E. Dimmer, Michael Schneider, Marc Feuermann, Lionel Breuza, Arnaud Gos, Damien Lieberherr, Ghislaine Argoud-Puy, Marie-Claude Blatter, Lydie Bougueleret, Ioannis Xenarios, and Alan Bridge

Subjects
0303 health sciences, business.industry, Databases, Protein, Molecular Sequence Annotation/standards, Vocabulary, Controlled, Molecular Sequence Annotation, Articles, Biology, File format, Bioinformatics, World Wide Web, 03 medical and health sciences, Consistency (database systems), Annotation, 0302 clinical medicine, 030220 oncology & carcinogenesis, Controlled vocabulary, Genetics, Data set (IBM mainframe), The Internet, UniProt, business, 030304 developmental biology
Abstract

The GO annotation dataset provided by the UniProt Consortium (GOA: http://www.ebi.ac.uk/GOA) is a comprehensive set of evidenced-based associations between terms from the Gene Ontology resource and UniProtKB proteins. Currently supplying over 100 million annotations to 11 million proteins in more than 360,000 taxa, this resource has increased 2-fold over the last 2 years and has benefited from a wealth of checks to improve annotation correctness and consistency as well as now supplying a greater information content enabled by GO Consortium annotation format developments. Detailed, manual GO annotations obtained from the curation of peer-reviewed papers are directly contributed by all UniProt curators and supplemented with manual and electronic annotations from 36 model organism and domain-focused scientific resources. The inclusion of high-quality, automatic annotation predictions ensures the UniProt GO annotation dataset supplies functional information to a wide range of proteins, including those from poorly characterized, non-model organism species. UniProt GO annotations are freely available in a range of formats accessible by both file downloads and web-based views. In addition, the introduction of a new, normalized file format in 2010 has made for easier handling of the complete UniProt-GOA data set.

Published
2017

4. Activities at the Universal Protein Resource (UniProt)

Author

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

Subjects
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.

Published
2013

5. New and continuing developments at PROSITE

Author

Edouard de Castro, Alan Bridge, Béatrice A. Cuche, Lorenzo Cerutti, Christian J. A. Sigrist, Lydie Bougueleret, Nicolas Hulo, and Ioannis Xenarios

Subjects
Proteome, Amino Acid Motifs, Computational biology, PROSITE, Biology, Discriminatory power, 03 medical and health sciences, Annotation, Documentation, Sequence Analysis, Protein, Genetics, Protein function prediction, Amino Acid Sequence, Databases, Protein, Conserved Sequence, 030304 developmental biology, 0303 health sciences, Internet, 030302 biochemistry & molecular biology, Proteins, Molecular Sequence Annotation, Articles, Protein Structure, Tertiary, UniProt
Abstract

PROSITE (http://prosite.expasy.org/) consists of documentation entries describing protein domains, families and functional sites, as well as associated patterns and profiles to identify them. It is complemented by ProRule a collection of rules, which increases the discriminatory power of these profiles and patterns by providing additional information about functionally and/or structurally critical amino acids. PROSITE signatures, together with ProRule, are used for the annotation of domains and features of UniProtKB/Swiss-Prot entries. Here, we describe recent developments that allow users to perform whole-proteome annotation as well as a number of filtering options that can be combined to perform powerful targeted searches for biological discovery. The latest version of PROSITE (release 20.85, of 30 August 2012) contains 1308 patterns, 1039 profiles and 1041 ProRules.

Published
2013

6. Toward interoperable bioscience data

Author

Chris T. Evelo, Susanna-Assunta Sansone, Anne Trefethen, Dawn Field, Hong Fang, Daniel J. Jacob, Caroline E. Shamu, Philippe Rocca-Serra, Julian L. Griffin, Eamonn Maguire, Oliver Hofmann, Paula de Matos, Christoph Steinbeck, Henning Hermjakob, Brad Chapman, Gully A. P. C. Burns, Steffen Neumann, Dorothy Reilly, Carole Goble, Weida Tong, Katherine Wolstencroft, Sudeshna Das, Timothy Clark, Lee Harland, Alain Laederach, Winston Hide, Scott C. Edmunds, Stephen Marshall, Lee-Ann Coleman, Shannan J. Ho Sui, Antoine de Daruvar, Bryn Williams-Jones, Ian Dix, Annette McGrath, Pascale Gaudet, Emily Merrill, Linda A. Amaral-Zettler, Catherine A. Shang, Jay Copeland, Jos C. S. Kleinjans, Chris F. Taylor, Magali Roux, Mark K. Forster, Kimberly Begley, Shaoguang Liang, Jack A. Gilbert, Kenneth Haug, Timothy F. Booth, Lydie Bougueleret, Ioannis Xenarios, Department of Laboratory Medicine, Karolinska University Hospital [Stockholm], Josephine Bay Paul Center, Marine Biological Laboratory, Computer Chimie Centrum, (CCC), Friedrich-Alexander Universität Erlangen-Nürnberg (FAU), Laboratoire Bordelais de Recherche en Informatique (LaBRI), Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB), Centre de Bioinformatique de Bordeaux (CBIB), CGFB, Northwestern University [Evanston], School of Computer Science [Manchester], University of Manchester [Manchester], Agents Cognitifs et Apprentissage Symbolique Automatique (ACASA), Laboratoire d'Informatique de Paris 6 (LIP6), Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS), Bioinformatica, GezondheidsRisico Analyse en Toxicologie, RS: NUTRIM - R4 - Gene-environment interaction, Toxicogenomics, RS: CARIM School for Cardiovascular Diseases, RS: GROW - School for Oncology and Reproduction, and Université de Bordeaux (UB)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB)-Centre National de la Recherche Scientifique (CNRS)

Subjects
0303 health sciences, Biomedical Research, DONNEE SCIENTIFIQUE, MESH: Biomedical Research, Interoperability, MEDLINE, Information Storage and Retrieval, MESH: Information Storage and Retrieval, BIOLOGIE, Biology, DONNEE BIOLOGIQUE, Data science, [SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], Article, PARTAGE DES DONNEES, 03 medical and health sciences, 0302 clinical medicine, INFORMATIQUE, Genetics, [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM], 030217 neurology & neurosurgery, 030304 developmental biology, Research data
Abstract

International audience; To make full use of research data, the bioscience community needs to adopt technologies and reward mechanisms that support interoperability and promote the growth of an open 'data commoning' culture. Here we describe the prerequisites for data commoning and present an established and growing ecosystem of solutions using the shared 'Investigation-Study-Assay' framework to support that vision.

Published
2016
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7. The UniProtKB/Swiss-Prot Tox-Prot program: A central hub of integrated venom protein data

Author

Sylvain Poux, Florence Jungo, Lydie Bougueleret, and Ioannis Xenarios

Subjects
Protein Conformation, Molecular Sequence Data, HUGO Gene Nomenclature Committee, Venom, Context (language use), Computational biology, Biology, Toxicology, Bioinformatics, Proteomics, Article, 03 medical and health sciences, Terminology as Topic, Animals, natural sciences, Databases, Protein, Animal toxin, 030304 developmental biology, 0303 health sciences, Data display, Venoms, 030302 biochemistry & molecular biology, Proteins, Venom Protein, 3. Good health, Data Display, UniProt, Sequence Alignment, Software
Abstract

Animal toxins are of interest to a wide range of scientists, due to their numerous applications in pharmacology, neurology, hematology, medicine, and drug research. This, and to a lesser extent the development of new performing tools in transcriptomics and proteomics, has led to an increase in toxin discovery. In this context, providing publicly available data on animal toxins has become essential. The UniProtKB/Swiss-Prot Tox-Prot program (http://www.uniprot.org/program/Toxins) plays a crucial role by providing such an access to venom protein sequences and functions from all venomous species. This program has up to now curated more than 5’000 venom proteins to the high-quality standards of UniProtKB/Swiss-Prot (release 2012_02). Proteins targeted by these toxins are also available in the knowledgebase. This paper describes in details the type of information provided by UniProtKB/Swiss-Prot for toxins, as well as the structured format of the knowledgebase.

Published
2012
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8. The Gene Ontology: enhancements for 2011

Author

P D'Eustachio, Benjamin C. Hitz, Julie Park, Paul Browne, Douglas G. Howe, Cynthia J. Krieger, Kalpana Karra, Stan Laulederkind, Karen R. Christie, Susan Tweedie, Eurie L. Hong, Lydie Bougueleret, Michele Magrane, Cathy R. Gresham, Rolf Apweiler, Lisa Matthews, Dong Li, Philippa J. Talmud, Ioannis Xenarios, J. M. Cherry, Tanya Z. Berardini, Deborah A. Siegele, Rama Balakrishnan, D. Sitnikov, A. Auchinchloss, Selina S. Dwight, Tony Sawford, Paul J. Kersey, Ruth C. Lovering, Ruth Y. Eberhardt, Ursula Hinz, Lakshmi Pillai, Sylvain Poux, Edith D. Wong, Klemens Pichler, Kati Laiho, Malcolm J. Gardner, Stephen G. Oliver, Lionel Breuza, Kara Dolinski, P Lemercier, Kristian B. Axelsen, Midori A. Harris, Adrienne E. Zweifel, H. Drabkin, Guillaume Keller, Marek S. Skrzypek, Daniel M. Staines, Fiona M. McCarthy, Nicholas H. Brown, Mark D. McDowall, Antonia Lock, Mary Shimoyama, Maria C. Costanzo, Teresia Buza, S. Jimenez, Rex L. Chisholm, Paul W. Sternberg, Hui Wang, Nadine Gruaz-Gumowski, Chantal Hulo, Rebecca E. Foulger, Melinda R. Dwinell, Judith A. Blake, Marcus C. Chibucos, B. K. McIntosh, C. D. Amundsen, Jane Lomax, L Famiglietti, Tom Hayman, Michael Tognolli, Eva Huala, James C. Hu, Patrick Masson, Maria Jesus Martin, Benoit Bely, Shuai Weng, Heather C. Wick, E. Dimmer, L. Ni, Catherine Rivoire, Christopher J. Mungall, H. Sehra, P. Duek-Roggli, Maria Victoria Schneider, Dianna G. Fisk, Michael S. Livstone, Ivo Pedruzzi, Shyamala Sundaram, Donna K. Slonim, Isabelle Cusin, Stuart R. Miyasato, Timothy F. Lowry, Varsha K. Khodiyar, Seth Carbon, Elisabeth Coudert, Jürg Bähler, Juancarlos Chan, Evelyn Camon, Daniel P. Renfro, Anne Estreicher, M. C. Blatter, Robert S. Nash, P Gaudet, Sven Heinicke, K. Van Auken, Stacia R. Engel, Alan Bridge, Ralf Stephan, Mary E. Dolan, Shane C. Burgess, Petra Fey, Shur-Jen Wang, Damien Lieberherr, Duncan Legge, P. Porras Millán, Andre Stutz, Yasmin Alam-Faruque, Gail Binkley, Bernd Roechert, S. Branconi-Quintaje, Ghislaine Argoud-Puy, S. Basu, Kim Rutherford, M. Moinat, Monte Westerfield, Arnaud Gos, Eleanor J Stanley, Valerie Wood, Ranjana Kishore, Diego Poggioli, S. Ferro-Rojas, Victoria Petri, Florence Jungo, Suzanna E. Lewis, Emmanuel Boutet, Warren A. Kibbe, M Feuermann, Claire O'Donovan, W. M. Chan, J. James, David P. Hill, Rachael P. Huntley, M. Gwinn Giglio, Paul Thomas, Jodi E. Hirschman, Paola Roncaglia, Gene Ontology Consortium, Blake, JA., Dolan, M., Drabkin, H., Hill, DP., Ni, L., Sitnikov, D., Burgess, S., Buza, T., Gresham, C., McCarthy, F., Pillai, L., Wang, H., Carbon, S., Lewis, SE., Mungall, CJ., Gaudet, P., Chisholm, RL., Fey, P., Kibbe, WA., Basu, S., Siegele, DA., McIntosh, BK., Renfro, DP., Zweifel, AE., Hu, JC., Brown, NH., Tweedie, S., Alam-Faruque, Y., Apweiler, R., Auchinchloss, A., Axelsen, K., Argoud-Puy, G., Bely, B., Blatter, M-., Bougueleret, L., Boutet, E., Branconi, S., Breuza, L., Bridge, A., Browne, P., Chan, WM., Coudert, E., Cusin, I., Dimmer, E., Duek-Roggli, P., Eberhardt, R., Estreicher, A., Famiglietti, L., Ferro-Rojas, S., Feuermann, M., Gardner, M., Gos, A., Gruaz-Gumowski, N., Hinz, U., Hulo, C., Huntley, R., James, J., Jimenez, S., Jungo, F., Keller, G., Laiho, K., Legge, D., Lemercier, P., Lieberherr, D., Magrane, M., Martin, MJ., Masson, P., Moinat, M., O'Donovan, C., Pedruzzi, I., Pichler, K., Poggioli, D., Porras Millán, P., Poux, S., Rivoire, C., Roechert, B., Sawford, T., Schneider, M., Sehra, H., Stanley, E., Stutz, A., Sundaram, S., Tognolli, M., Xenarios, I., Foulger, R., Lomax, J., Roncaglia, P., Camon, E., Khodiyar, VK., Lovering, RC., Talmud, PJ., Chibucos, M., Gwinn Giglio, M., Dolinski, K., Heinicke, S., Livstone, MS., Stephan, R., Harris, MA., Oliver, SG., Rutherford, K., Wood, V., Bahler, J., Lock, A., Kersey, PJ., McDowall, MD., Staines, DM., Dwinell, M., Shimoyama, M., Laulederkind, S., Hayman, T., Wang, S-., Petri, V., Lowry, T., D'Eustachio, P., Matthews, L., Amundsen, CD., Balakrishnan, R., Binkley, G., Cherry, JM., Christie, KR., Costanzo, MC., Dwight, SS., Engel, SR., Fisk, DG., Hirschman, JE., Hitz, BC., Hong, EL., Karra, K., Krieger, CJ., Miyasato, SR., Nash, RS., Park, J., Skrzypek, MS., Weng, S., Wong, ED., Berardini, TZ., Li, D., Huala, E., Slonim, D., Wick, H., Thomas, P., Chan, J., Kishore, R., Sternberg, P., Van Auken, K., Howe, D., and Westerfield, M.

Subjects
Quality Control, 0303 health sciences, media_common.quotation_subject, Databases, Genetic, Molecular Sequence Annotation/standards, Vocabulary, Controlled, Inference, Molecular Sequence Annotation, Articles, Biology, Ontology (information science), World Wide Web, Open Biomedical Ontologies, 03 medical and health sciences, Annotation, 0302 clinical medicine, Resource (project management), Controlled vocabulary, Genetics, Social media, Function (engineering), 030217 neurology & neurosurgery, 030304 developmental biology, media_common
Abstract

The Gene Ontology (GO) (http://www.geneontology.org) is a community bioinformatics resource that represents gene product function through the use of structured, controlled vocabularies. The number of GO annotations of gene products has increased due to curation efforts among GO Consortium (GOC) groups, including focused literature-based annotation and ortholog-based functional inference. The GO ontologies continue to expand and improve as a result of targeted ontology development, including the introduction of computable logical definitions and development of new tools for the streamlined addition of terms to the ontology. The GOC continues to support its user community through the use of e-mail lists, social media and web-based resources.

Published
2011
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9. Animal Toxins: How is Complexity Represented in Databases?

Author

Florence Jungo, Anne Estreicher, Amos Bairoch, Lydie Bougueleret, and Ioannis Xenarios

Subjects
0303 health sciences, venom protein, ConoServer, Health, Toxicology and Mutagenesis, ArachnoServer, 030302 biochemistry & molecular biology, Proteins, Spider Venoms, animal toxin, Review, ATDB, Toxicology, Tox-Prot, 03 medical and health sciences, Animals, UniProtKB/Swiss-Prot, ddc:576, Databases, Protein, Peptides, Software, database, 030304 developmental biology
Abstract

Peptide toxins synthesized by venomous animals have been extensively studied in the last decades. To be useful to the scientific community, this knowledge has been stored, annotated and made easy to retrieve by several databases. The aim of this article is to present what type of information users can access from each database. ArachnoServer and ConoServer focus on spider toxins and cone snail toxins, respectively. UniProtKB, a generalist protein knowledgebase, has an animal toxin-dedicated annotation program that includes toxins from all venomous animals. Finally, the ATDB metadatabase compiles data and annotations from other databases and provides toxin ontology.

Published
2010
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10. HAMAP: a database of completely sequenced microbial proteome sets and manually curated microbial protein families in UniProtKB/Swiss-Prot

Author

Guillaume Keller, Andrea H. Auchincloss, Isabelle Phan, Karine Michoud, Virginie Bulliard, Edouard de Castro, Lydie Bougueleret, Delphine Baratin, Tania Lima, Corinne Lachaize, Elisabeth Coudert, Catherine Rivoire, and Amos Marc Bairoch

Subjects
Proteomics, Proteome, Protein family, Archaeal Proteins, Sequence alignment, Genomics, Biology, computer.software_genre, Genome, 03 medical and health sciences, Annotation, Bacterial Proteins, Sequence Analysis, Protein, Genetics, ddc:576, Databases, Protein, 030304 developmental biology, 0303 health sciences, Database, 030302 biochemistry & molecular biology, Articles, Bacterial Proteins/chemistry/classification/genetics, Archaeal Proteins/chemistry/classification/genetics, Proteome/chemistry, UniProt, Sequence Alignment, computer, Software
Abstract

The growth in the number of completely sequenced microbial genomes (bacterial and archaeal) has generated a need for a procedure that provides UniProtKB/Swiss-Prot-quality annotation to as many protein sequences as possible. We have devised a semi-automated system, HAMAP (High-quality Automated and Manual Annotation of microbial Proteomes), that uses manually built annotation templates for protein families to propagate annotation to all members of manually defined protein families, using very strict criteria. The HAMAP system is composed of two databases, the proteome database and the family database, and of an automatic annotation pipeline. The proteome database comprises biological and sequence information for each completely sequenced microbial proteome, and it offers several tools for CDS searches, BLAST options and retrieval of specific sets of proteins. The family database currently comprises more than 1500 manually curated protein families and their annotation templates that are used to annotate proteins that belong to one of the HAMAP families. On the HAMAP website, individual sequences as well as whole genomes can be scanned against all HAMAP families. The system provides warnings for the absence of conserved amino acid residues, unusual sequence length, etc. Thanks to the implementation of HAMAP, more than 200,000 microbial proteins have been fully annotated in UniProtKB/Swiss-Prot (HAMAP website: http://www.expasy.org/sprot/hamap).

Published
2009
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11. pfsearchV3: a code acceleration and heuristic to search PROSITE profiles

Author

Alan Bridge, Lorenzo Cerutti, Thierry Schuepbach, Marco Pagni, Ioannis Xenarios, and Lydie Bougueleret

Subjects
Statistics and Probability, Source code, Heuristic (computer science), Computer science, media_common.quotation_subject, 0206 medical engineering, Protein domain, 02 engineering and technology, PROSITE, computer.software_genre, Biochemistry, Genome, 03 medical and health sciences, Protein sequencing, Sequence Analysis, Protein, Databases, Protein, Molecular Biology, 030304 developmental biology, media_common, 0303 health sciences, Molecular Sequence Annotation, Applications Notes, Protein Structure, Tertiary, Computer Science Applications, Computational Mathematics, Computational Theory and Mathematics, Metagenomics, Data mining, Sequence Analysis, computer, Algorithms, Software, 020602 bioinformatics
Abstract

Summary: The PROSITE resource provides a rich and well annotated source of signatures in the form of generalized profiles that allow protein domain detection and functional annotation. One of the major limiting factors in the application of PROSITE in genome and metagenome annotation pipelines is the time required to search protein sequence databases for putative matches. We describe an improved and optimized implementation of the PROSITE search tool pfsearch that, combined with a newly developed heuristic, addresses this limitation. On a modern x86_64 hyper-threaded quad-core desktop computer, the new pfsearchV3 is two orders of magnitude faster than the original algorithm. Availability and implementation: Source code and binaries of pfsearchV3 are freely available for download at http://web.expasy.org/pftools/#pfsearchV3, implemented in C and supported on Linux. PROSITE generalized profiles including the heuristic cut-off scores are available at the same address. Contact: pftools@isb-sib.ch

Published
2013

12. An Integrated Ontology Resource to Explore and Study Host-Virus Relationships

Author

Patrick Masson, Rebecca E. Foulger, Chantal Hulo, Philippe Le Mercier, Edouard de Castro, Ioannis Xenarios, Alan Bridge, Lydie Bougueleret, Sylvain Poux, and Jane Lomax

Subjects
Vocabulary, ViralZone, lcsh:Medicine, Ontology (information science), Adaptive Immunity, Bioinformatics, Database and Informatics Methods, Resource (project management), lcsh:Science, media_common, 0303 health sciences, Multidisciplinary, 030302 biochemistry & molecular biology, Genomics, Genomic Databases, Bioontologies, Medical Microbiology, Virus Diseases, Viral Pathogens, Viruses, Host-Pathogen Interactions, UniProt, Databases, Nucleic Acid, Host (network), Research Article, media_common.quotation_subject, Biology, Research and Analysis Methods, Microbiology, Virus Effects on Host Gene Expression, World Wide Web, Molecular Genetics, 03 medical and health sciences, Virology, Controlled vocabulary, Web page, Genetics, Animals, Humans, Microbial Pathogens, Molecular Biology, 030304 developmental biology, lcsh:R, Organisms, Biology and Life Sciences, Computational Biology, Genome Analysis, Immunity, Innate, Biological Databases, Gene Ontology, Gene Expression Regulation, lcsh:Q, Interferons, Gene Function
Abstract

Our growing knowledge of viruses reveals how these pathogens manage to evade innate host defenses. A global scheme emerges in which many viruses usurp key cellular defense mechanisms and often inhibit the same components of antiviral signaling. To accurately describe these processes, we have generated a comprehensive dictionary for eukaryotic host-virus interactions. This controlled vocabulary has been detailed in 57 ViralZone resource web pages which contain a global description of all molecular processes. In order to annotate viral gene products with this vocabulary, an ontology has been built in a hierarchy of UniProt Knowledgebase (UniProtKB) keyword terms and corresponding Gene Ontology (GO) terms have been developed in parallel. The results are 65 UniProtKB keywords related to 57 GO terms, which have been used in 14,390 manual annotations; 908,723 automatic annotations and propagated to an estimation of 922,941 GO annotations. ViralZone pages, UniProtKB keywords and GO terms provide complementary tools to users, and the three resources have been linked to each other through host-virus vocabulary.

Published
2014

13. Activation of the human homologue of the Drosophila sina gene in apoptosis and tumor suppression

Author

G Linares-Cruz, Fabien Calvo, Marcel Tuynder, M Medhioub, H der Sarkissan, Lydie Bougueleret, D. Le Paslier, Robert Amson, Adam Telerman, Mona Nemani, Heriberto Bruzzoni-Giovanelli, F Sigaux, Veronique Alvaro, Daniel Cohen, Jean-Pierre Roperch, Patricia Pasturaud, Ilya Chumakov, Dorra Cherif, Moshe Oren, Jean Dausset, Lucien Cazes, I Le Gall, David Israeli, Service de Recherche en Hémato-Immunologie (SRHI - UMR_E 05), Université Paris Diderot - Paris 7 (UPD7)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Oxford National Institute for Health Research Biomedical Research Centre/Molecular Diagnostic Centre, National Institute biomedical research centre, Serono Genetics Institute S.A.[Evry], Serono Genetics Institute, Department of Molecular Cell Biology [Rehovot], Weizmann Institute of Science [Rehovot, Israël], Laboratoire Interdisciplinaire de Physique [Saint Martin d’Hères] (LIPhy), Université Joseph Fourier - Grenoble 1 (UJF)-Centre National de la Recherche Scientifique (CNRS), Department of Earth and Environmental Science [Socorro], New Mexico Institute of Mining and Technology [New Mexico Tech] (NMT), and Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)

Subjects
Programmed cell death, DNA, Complementary, Ubiquitin-Protein Ligases, [SDV]Life Sciences [q-bio], Molecular Sequence Data, Apoptosis, [SDV.CAN]Life Sciences [q-bio]/Cancer, RNA-binding protein, SIAH1, Biology, 03 medical and health sciences, 0302 clinical medicine, Animals, Humans, Genes, Tumor Suppressor, [SDV.BBM]Life Sciences [q-bio]/Biochemistry, Molecular Biology, Amino Acid Sequence, Nuclear protein, Gene, In Situ Hybridization, Fluorescence, Gene Library, 030304 developmental biology, Regulation of gene expression, Zinc finger, [SDV.GEN]Life Sciences [q-bio]/Genetics, 0303 health sciences, Multidisciplinary, Sequence Homology, Amino Acid, Nuclear Proteins, Proteins, Zinc Fingers, Cell cycle, Molecular biology, Gene Expression Regulation, 030220 oncology & carcinogenesis, Chromosomes, Human, Pair 16, Research Article
Abstract

International audience; Developmentally regulated genes in Drosophila, which are conserved through evolution, are potential candidates for key functions in biological processes such as cell cycle, programmed cell death, and cancer. We report cloning and characterization of the human homologue of the Drosophila seven in absentia gene (HUMSIAH), which codes for a 282 amino acids putative zinc finger protein. HUMSIAH is localized on human chromosome 16q12-q13. This gene is activated during the physiological program of cell death in the intestinal epithelium. Moreover, human cancer-derived cells selected for suppression of their tumorigenic phenotype exhibit constitutively elevated levels of HUMSIAH mRNA. A similar pattern of expression is also displayed by the p21waf1. These results suggest that mammalian seven in absentia gene, which is a target for activation by p53, may play a role in apoptosis and tumor suppression.

Published
1996
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14. Application of text-mining for updating protein post-translational modification annotation in UniProtKB

Author

Johanna McEntyre, Lydie Bougueleret, Patrick Ruch, Alan Bridge, Ioannis Xenarios, Julien Gobeill, and Anne-Lise Veuthey

Subjects
Proteomics, Computer science, Process (engineering), Knowledge Bases, 0206 medical engineering, 02 engineering and technology, Scientific literature, computer.software_genre, Biochemistry, Manual curation, 03 medical and health sciences, Annotation, Structural Biology, Data Mining, Humans, Databases, Protein, Molecular Biology, 030304 developmental biology, 0303 health sciences, Information retrieval, Applied Mathematics, Methodology Article, Data Mining/methods, Molecular Sequence Annotation, Protein Processing, Post-Translational, Computer Science Applications, Task (computing), Information extraction, Protein processing, Posttranslational modification, Data mining, UniProt, DNA microarray, computer, 020602 bioinformatics
Abstract

The annotation of protein post-translational modifications (PTMs) is an important task of UniProtKB curators and, with continuing improvements in experimental methodology, an ever greater number of articles are being published on this topic. To help curators cope with this growing body of information we have developed a system which extracts information from the scientific literature for the most frequently annotated PTMs in UniProtKB. The procedure uses a pattern-matching and rule-based approach to extract sentences with information on the type and site of modification. A ranked list of protein candidates for the modification is also provided. For PTM extraction, precision varies from 57% to 94%, and recall from 75% to 95%, according to the type of modification. The procedure was used to track new publications on PTMs and to recover potential supporting evidence for phosphorylation sites annotated based on the results of large scale proteomics experiments. The information retrieval and extraction method we have developed in this study forms the basis of a simple tool for the manual curation of protein post-translational modifications in UniProtKB/Swiss-Prot. Our work demonstrates that even simple text-mining tools can be effectively adapted for database curation tasks, providing that a thorough understanding of the working process and requirements are first obtained. This system can be accessed at http://eagl.unige.ch/PTM/ .

Published
2013

15. Updates in Rhea – an expert curated resource of biochemical reactions

Author

Thierry Lombardot, Lydie Bougueleret, Ioannis Xenarios, Monica Pozzato, Nicole Redaschi, Joseph Onwubiko, Anne Morgat, Alan Bridge, Marco Pagni, Nevila Hyka-Nouspikel, Kristian B. Axelsen, Lucila Aimo, Anne Niknejad, Sébastien Moretti, Steven Rosanoff, and Elisabeth Coudert

Subjects
0301 basic medicine, 0303 health sciences, Enzyme Commission number, Computational biology, Ontology (information science), Biology, Astrobiology, 03 medical and health sciences, 030104 developmental biology, Resource (project management), 0302 clinical medicine, Functional annotation, Genetics, Biochemical reactions, Database Issue, Erratum, 030217 neurology & neurosurgery, 030304 developmental biology
Abstract

Rhea (http://www.rhea-db.org) is a comprehensive and non-redundant resource of expert-curated biochemical reactions designed for the functional annotation of enzymes and the description of metabolic networks. Rhea describes enzyme-catalyzed reactions covering the IUBMB Enzyme Nomenclature list as well as additional reactions, including spontaneously occurring reactions, using entities from the ChEBI (Chemical Entities of Biological Interest) ontology of small molecules. Here we describe developments in Rhea since our last report in the database issue of Nucleic Acids Research. These include the first implementation of a simple hierarchical classification of reactions, improved coverage of the IUBMB Enzyme Nomenclature list and additional reactions through continuing expert curation, and the development of a new website to serve this improved dataset.

Published
2016
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16. UniPathway: a resource for the exploration and annotation of metabolic pathways

Author

Alain Viari, Kristian B. Axelsen, Anne Morgat, Lydie Bougueleret, Guillaume Keller, Ioannis Xenarios, Amos Marc Bairoch, Alan Bridge, Eric Coissac, Elisabeth Coudert, An algorithmic view on genomes, cells, and environments (BAMBOO), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire de Biométrie et Biologie Evolutive - UMR 5558 (LBBE), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS), Swiss-Prot Group, Swiss Institute of Bioinformatics [Genève] (SIB), Laboratoire d'Ecologie Alpine (LECA), Université Joseph Fourier - Grenoble 1 (UJF)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS), Vital-IT, European Project: 247073,EC:FP7:ERC,ERC-2009-AdG,SISYPHE(2010), Laboratoire de Biométrie et Biologie Evolutive - UMR 5558 (LBBE), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS)-Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria), and Université Joseph Fourier - Grenoble 1 (UJF)-Centre National de la Recherche Scientifique (CNRS)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])

Subjects
Databases, Factual, Computational biology, Biology, Bioinformatics, 03 medical and health sciences, Annotation, Resource (project management), Controlled vocabulary, Databases, Protein, Enzymes/metabolism, Lysine/biosynthesis, Metabolic Networks and Pathways, Molecular Sequence Annotation, Genetics, ddc:576, KEGG, 030304 developmental biology, 0303 health sciences, Lysine, 030302 biochemistry & molecular biology, MetaCyc, Articles, [SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], Enzymes, Metabolic pathway, UniProt, [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM]
Abstract

International audience; UniPathway (http://www.unipathway.org) is a fully manually curated resource for the representation and annotation of metabolic pathways. UniPathway provides explicit representations of enzyme-catalyzed and spontaneous chemical reactions, as well as a hierarchical representation of metabolic pathways. This hierarchy uses linear subpathways as the basic building block for the assembly of larger and more complex pathways, including species-specific pathway variants. All of the pathway data in UniPathway has been extensively cross-linked to existing pathway resources such as KEGG and MetaCyc, as well as sequence resources such as the UniProt KnowledgeBase (UniProtKB), for which UniPathway provides a controlled vocabulary for pathway annotation. We introduce here the basic concepts underlying the UniPathway resource, with the aim of allowing users to fully exploit the information provided by UniPathway.

Published
2012
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17. Rhea--a manually curated resource of biochemical reactions

Author

Lydie Bougueleret, Alan Bridge, Ioannis Xenarios, Eugeni Belda, Gareth Owen, Christoph Steinbeck, Steve Turner, Hong Cao, Elisabeth Coudert, Rafael Alcántara, Paula de Matos, Kristian B. Axelsen, Anne Morgat, Marcus Ennis, Swiss-Prot Group, Swiss Institute of Bioinformatics [Genève] (SIB), An algorithmic view on genomes, cells, and environments (BAMBOO), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire de Biométrie et Biologie Evolutive - UMR 5558 (LBBE), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS), Department of Clinical Biochemistry, Royal Victoria Infirmary, and European Project: 247073,EC:FP7:ERC,ERC-2009-AdG,SISYPHE(2010)

Subjects
Internet, 0303 health sciences, Databases, Factual, Biochemical Phenomena, Biochemical Processes, Enzymes/metabolism, Metabolic Networks and Pathways, Software, 030302 biochemistry & molecular biology, Genome scale, Metabolic network, Enzyme Commission number, Articles, Computational biology, Ontology (information science), Biology, Bioinformatics, [SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], Enzymes, 03 medical and health sciences, Broad spectrum, Genetics, Biochemical reactions, [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM], 030304 developmental biology
Abstract

International audience; Rhea (http://www.ebi.ac.uk/rhea) is a comprehensive resource of expert-curated biochemical reactions. Rhea provides a non-redundant set of chemical transformations for use in a broad spectrum of applications, including metabolic network reconstruction and pathway inference. Rhea includes enzyme-catalyzed reactions (covering the IUBMB Enzyme Nomenclature list), transport reactions and spontaneously occurring reactions. Rhea reactions are described using chemical species from the Chemical Entities of Biological Interest ontology (ChEBI) and are stoichiometrically balanced for mass and charge. They are extensively manually curated with links to source literature and other public resources on metabolism including enzyme and pathway databases. This cross-referencing facilitates the mapping and reconciliation of common reactions and compounds between distinct resources, which is a common first step in the reconstruction of genome scale metabolic networks and models.

Published
2012
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18. Ongoing and future developments at the Universal Protein Resource

Author

Vicente Lara, Arnaud Gos, Nikolas Pontikos, L. Bollondi, L Famiglietti, Barker Wc, Chuming Chen, Michael Tognolli, Patrick Masson, Salvo Paesano, Tony Sawford, Sandrine Pilbout, Jerven Bolleman, Jian Zhang, S Staehli, Elisabeth Gasteiger, David Binns, Ursula Hinz, Nadine Gruaz-Gumowski, Chantal Hulo, Maria Jesus Martin, M. Corbett, Veuthey Al, Paul Browne, Guillaume Keller, S. Jimenez, Roberts Nv, Brigitte Boeckmann, Natale Da, Suzek Be, Edward Turner, T. Kappler, Steven Rosanoff, Leslie Arminski, Florence Jungo, M Donnelly, P. Dubey, Ruth Y. Eberhardt, Lydie Bougueleret, Vivienne Baillie Gerritsen, Maria Victoria Schneider, Lionel Breuza, Isabelle Cusin, Delphine Baratin, E. Dimmer, Rachael P. Huntley, Julius O.B. Jacobsen, Arighi Cn, Quintaje Sb, Alan Bridge, Nicole Redaschi, Shyamala Sundaram, Peter B. McGarvey, Rebecca E. Foulger, Duncan Legge, Andre Stutz, Monica Pozzato, Raja Mazumder, Anne Morgat, M Doche, K Sonesson, Anne Estreicher, Blatter Mc, Manuela Pruess, Serenella Ferro, Séverine Duvaud, F. Fazzini, Rolf Apweiler, Natarajan Tg, E. Stanley, M Feuermann, Claire O'Donovan, J. James, Ivo Pedruzzi, Castro Lg, Wu Ch, M Bingley, W Liu, He Huang, Bernd Roechert, Laure Verbregue, Elisabeth Coudert, Ioannis Xenarios, M. Moinat, Sandra Orchard, P Lemercier, Damien Lieberherr, Ricardo Antunes, Ghislaine Argoud-Puy, Sebastien Gehant, Qiang Wang, Klemens Pichler, S. Patient, Nicolas Hulo, Diego Poggioli, J. Nchoutmboube, Emmanuel Boutet, H. Sehra, Chan Wm, Yasmin Alam-Faruque, M. Kleen, Van Rensburg P, Kati Laiho, Kristian B. Axelsen, John S. Garavelli, Christian J. A. Sigrist, Amos Marc Bairoch, Yongxing Chen, A. Fedotov, Yeh Ls, Sylvain Poux, Lynette Bower, Quan Lin, Daniel Barrell, Benoit Bely, U. Ugochukwu, Xavier D. Martin, Catherine Rivoire, E. Decastro, Jie Luo, Alain Gateau, Michele Magrane, Dolnide Dornevil, Vinayaka Cr, Andrea H. Auchincloss, Yuqi Wang, An algorithmic view on genomes, cells, and environments (BAMBOO), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire de Biométrie et Biologie Evolutive - UMR 5558 (LBBE), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS), Swiss Institute of Bioinformatics [Lausanne] (SIB), Université de Lausanne = University of Lausanne (UNIL), Institut de Microélectronique, Electromagnétisme et Photonique - Laboratoire d'Hyperfréquences et Caractérisation (IMEP-LAHC), Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut National Polytechnique de Grenoble (INPG)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS), Institut de minéralogie et de physique des milieux condensés (IMPMC), Université Pierre et Marie Curie - Paris 6 (UPMC)-Université Paris Diderot - Paris 7 (UPD7)-Institut de Physique du Globe de Paris (IPG Paris)-Centre National de la Recherche Scientifique (CNRS), Laboratoire de Biométrie et Biologie Evolutive - UMR 5558 (LBBE), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS)-Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria), Université de Lausanne (UNIL), Université Pierre et Marie Curie - Paris 6 (UPMC)-IPG PARIS-Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS), UniProt Consortium, Apweiler, R., Martin, MJ., O'Donovan, C., Magrane, M., Alam-Faruque, Y., Antunes, R., Barrell, D., Bely, B., Bingley, M., Binns, D., Bower, L., Browne, P., Chan, WM., Dimmer, E., Eberhardt, R., Fazzini, F., Fedotov, A., Foulger, R., Garavelli, J., Castro, LG., Huntley, R., Jacobsen, J., Kleen, M., Laiho, K., Legge, D., Lin, Q., Liu, W., Luo, J., Orchard, S., Patient, S., Pichler, K., Poggioli, D., Pontikos, N., Pruess, M., Rosanoff, S., Sawford, T., Sehra, H., Turner, E., Corbett, M., Donnelly, M., van Rensburg, P., Xenarios, I., Bougueleret, L., Auchincloss, A., Argoud-Puy, G., Axelsen, K., Bairoch, A., Baratin, D., Blatter, MC., Boeckmann, B., Bolleman, J., Bollondi, L., Boutet, E., Quintaje, SB., Breuza, L., Bridge, A., deCastro, E., Coudert, E., Cusin, I., Doche, M., Dornevil, D., Duvaud, S., Estreicher, A., Famiglietti, L., Feuermann, M., Gehant, S., Ferro, S., Gasteiger, E., Gateau, A., Gerritsen, V., Gos, A., Gruaz-Gumowski, N., Hinz, U., Hulo, C., Hulo, N., James, J., Jimenez, S., Jungo, F., Kappler, T., Keller, G., Lara, V., Lemercier, P., Lieberherr, D., Martin, X., Masson, P., Moinat, M., Morgat, A., Paesano, S., Pedruzzi, I., Pilbout, S., Poux, S., Pozzato, M., Redaschi, N., Rivoire, C., Roechert, B., Schneider, M., Sigrist, C., Sonesson, K., Staehli, S., Stanley, E., Stutz, A., Sundaram, S., Tognolli, M., Verbregue, L., Veuthey, AL., Wu, CH., Arighi, CN., Arminski, L., Barker, WC., Chen, C., Chen, Y., Dubey, P., Huang, H., Mazumder, R., McGarvey, P., Natale, DA., Natarajan, TG., Nchoutmboube, J., Roberts, NV., Suzek, BE., Ugochukwu, U., Vinayaka, CR., Wang, Q., Wang, Y., Yeh, LS., and Zhang, J.

Subjects
Proteomics, 0303 health sciences, Sequence database, 030302 biochemistry & molecular biology, Proteins, Articles, Computational biology, Biology, Bioinformatics, [SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], Systems Integration, Universal Protein Resource, 03 medical and health sciences, Information resource, Protein sequencing, Sequence Analysis, Protein, Metagenomics, UniProt Knowledgebase, Genetics, Databases, Protein/trends, Proteins/chemistry, Proteins/genetics, UniProt, [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM], Databases, Protein, 030304 developmental biology
Abstract

International audience; The primary mission of Universal Protein Resource (UniProt) is to support biological research by maintaining a stable, comprehensive, fully classified, richly and accurately annotated protein sequence knowledgebase, with extensive cross-references and querying interfaces freely accessible to the scientific community. UniProt is produced by the UniProt Consortium which consists of groups from the European Bioinformatics Institute (EBI), the Swiss Institute of Bioinformatics (SIB) and the Protein Information Resource (PIR). UniProt is comprised of four major components, each optimized for different uses: the UniProt Archive, the UniProt Knowledgebase, the UniProt Reference Clusters and the UniProt Metagenomic and Environmental Sequence Database. UniProt is updated and distributed every 4 weeks and can be accessed online for searches or download at http://www.uniprot.org.

Published
2011
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19. CAG/CTG and CGG/GCC repeats in human brain reference cDNAs: Outcome in searching for new dynamic mutations

Author

Howard M. Cann, Veronique Albanese, Hans Lehrach, Jean Weissenbach, Sebastian Meier-Ewert, Greg Lennon, Lydie Bougueleret, Isabelle Le Gall, Daniel Cohen, Stephanie Moriniere, Sébastien Holbert, Christian Neri, Claudine Saada, Anne-Sophie Lebre, Fondation Jean Dausset - Centre d’Étude du Polymorphisme Humain, Max Planck Institute for Molecular Genetics (MPIMG), Max-Planck-Gesellschaft, Centre National de la Recherche Scientifique (CNRS), and Lawrence Livermore National Laboratory (LLNL)

Subjects
DISORDER, EXPRESSION, Candidate gene, congenital, hereditary, and neonatal diseases and abnormalities, DNA, Complementary, GENES, PROTEIN, Biology, medicine.disease_cause, DISEASE, CLONING, Chromosome Walking, 03 medical and health sciences, Fetus, 0302 clinical medicine, Gene Frequency, Polymorphism (computer science), Complementary DNA, mental disorders, SCHIZOPHRENIA, Genetics, medicine, Humans, Genetic Testing, Gene, Gene Library, 030304 developmental biology, 0303 health sciences, Mutation, Genome, Human, Brain, Infant, Nucleic Acid Hybridization, TRINUCLEOTIDE REPEATS, Human brain, EXPANSION, EXPANDED CAG REPEATS, nervous system diseases, medicine.anatomical_structure, Microsatellite, Trinucleotide repeat expansion, 030217 neurology & neurosurgery, [SDV.MHEP]Life Sciences [q-bio]/Human health and pathology
Abstract

CAG and CGG expansion is associated with 10 inherited neurological diseases and is thought to be involved in other human genetic diseases. To identify new candidate genes, we have undertaken a large-scale screening project for CAG/CTG ([CAG] n ) and CGG/GCC ([CGG] n ) repeats in human brain reference cDNAs. Here, we present the final classification for 597 cDNAs selected by CAG and CGG hybridization from two libraries (100,128 clones) and the updated characterization of [CAG] n - and [CGG] n -positive cDNAs (repeat polymorphism and cDNA localization). We have selected 124 CAG and 83 CGG hybridization-positive clones representing new genes, from which 49 CAG and 7 CGG repeats could be identified. New [CAG] n and [CGG] n with more than seven to nine units were rare (1/2000), and perfect [CAG] n 9 were more likely polymorphic. Overall, highly polymorphic to monomorphic new [CAG] n > 9 and [CGG] n > 7 were characterized. The comparison of our data with other [CAG] n and [CGG] n resources suggests that the screening of reference cDNAs leads to unique sources of new [CAG] n and [CGG] n and will enhance the study of enlarged triplet repeats in human genetic diseases.

Published
1998
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20. Survey of CAG/CTG repeats in human cDNAs representing new genes: Candidates for inherited neurological disorders

Author

Veronique Albanese, Anne-Sophie Lebre, Sophie Guillou, Howard M. Cann, Eric Poullier, Catherine Massart, Hung Bui, Claudine Saada, Jean Weissenbach, Lydie Bougueleret, Sebastian Meier-Ewert, Philippe Rigault, Catherine Giudicelli, Greg Lennon, Sébastien Holbert, Isabelle Le Gall, P Millasseau, Ilya Chumakov, Daniel Cohen, Patricia Gervy, Christian Neri, Hans Lehrach, Jean Dausset, Fondation Jean Dausset - Centre d’Étude du Polymorphisme Humain, Max Planck Institute for Molecular Genetics (MPIMG), Max-Planck-Gesellschaft, Centre National de la Recherche Scientifique (CNRS), and Lawrence Livermore National Laboratory (LLNL)

Subjects
EXPRESSION, Candidate gene, congenital, hereditary, and neonatal diseases and abnormalities, DNA, Complementary, Molecular Sequence Data, Gene Expression, Biology, ATAXIA, SEQUENCE, 03 medical and health sciences, 0302 clinical medicine, Gene mapping, SEARCH, SCHIZOPHRENIA, MAPS, Genetics, Chromosomes, Human, Humans, Cloning, Molecular, Molecular Biology, Gene, Genetics (clinical), 030304 developmental biology, Gene Library, Brain Chemistry, 0303 health sciences, Expressed sequence tag, Polymorphism, Genetic, Infant, Newborn, Chromosome, Brain, Chromosome Mapping, TRINUCLEOTIDE REPEATS, General Medicine, Sequence Analysis, DNA, EXPANSION, EXPANDED CAG REPEATS, nervous system diseases, SUSCEPTIBILITY GENE, Genes, Genetic marker, GenBank, [SDV.MHEP.PSM]Life Sciences [q-bio]/Human health and pathology/Psychiatrics and mental health, Microsatellite, Nervous System Diseases, 030217 neurology & neurosurgery, [SDV.MHEP]Life Sciences [q-bio]/Human health and pathology
Abstract

International audience; Expansion of polymorphic CAG and CTG repeats in transcripts is the cause of six inherited origin. neurodegenerative or neuromuscular diseases and may be involved in several other genetic disorders of the central nervous system. To identify new candidate genes, we have undertaken a large-scale screening project for CAG and CTG repeats in human reference cDNAs. We screened 100 128 brain cDNAs by hybridization. We also scanned GenBank expressed sequence tags for the presence of long CAG/CTG repeats in the extremities of cDNAs from several human tissues, Of the selected clones, 286 were found to represent new genes, and 72 have thus far been shown to contain CAG/CTG repeats, Our data indicate that CAG/CTG repeated 10 or more times are more likely to be polymorphic, and that new 3'-directed cDNAs with such repeats are very rare (1/2862). Nine new cDNAs containing polymorphic (observed heterozygote frequency: 0.05-0.90) CAG/CTG repeats have been currently identified in cDNAs, Ail of the cDNAs have been assigned to chromosomes, and six of them could be mapped with YACs to 1q32-q41, 3p14, 4q28, 3p21 and 12q13.3, 13q13.1-q13.2, and 19q13.43, Three of these clones are highly polymorphic and represent the most likely candidate genes for inherited neurodegenerative diseases and, perhaps, neuropsychiatric disorders of multifactorial origin.

Published
1996
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21. Collaborative annotation of genes and proteins between UniProtKB/Swiss-Prot and dictyBase

Author

Ruchira S. Datta, Rex L. Chisholm, Michel Schneider, Alan Bridge, Catherine Rivoire, Sylvain Poux, Séverine Duvaud, Alain Gateau, P. Lemercier, W.C. de Lima, Elisabeth Coudert, Chantal Hulo, Emmanuel Boutet, Petra Fey, Ursula Hinz, Michael Tognolli, E. Stanley, Kristian B. Axelsen, Bernd Roechert, Amos Marc Bairoch, M. Moinat, Lydie Lane, A. Nikolskaya, Florence Jungo, Ivo Pedruzzi, P. Brown, Kimmen Sjölander, T. de Oliveira Lima, J. James, S. Jimenez, S. Braconi Quintaje, Guillaume Keller, Damien Lieberherr, Pascale Gaudet, S. Ferro Rojas, Andrea H. Auchincloss, N. Farriol-Mathis, Marc Feuermann, Lydie Bougueleret, Gaudet, Pascale, Lane, Lydie, Bridge, Alan James, Poux, Sylvain, Auchincloss Damay, Andréa, Axelsen, Kristian Buhl, Braconi Quintaje, Silvia, Boutet, Emmanuel, Coudert, Elisabeth, Lima, Wanessa Cristina, De Oliveira Lima, Tania, Duvaud, Séverine, Farriol-Mathis, Nathalie, Ferro Rojas, Serenella, Feuermann, Marc, Gateau, Alain, Hinz, Ursula, Hulo, Chantal, James, Janet, Jimenez, Silvia, Jungo, Florence, Keller, Guillaume Bertrand, Le Mercier, Philippe, Lieberherr, Damien, Moinat-Stuenkel, Ann Madelaine, Pedruzzi, Ivo, Rivoire, Catherine, Roechert, Bernd, Schneider, Michel, Tognolli, Michael, Bougueleret, Lydie, and Bairoch, Amos Marc

Subjects
0303 health sciences, Model organism database, biology, Protein database, Computational biology, DictyBase, biology.organism_classification, General Biochemistry, Genetics and Molecular Biology, Dictyostelium discoideum, World Wide Web, 03 medical and health sciences, Annotation, 0302 clinical medicine, 030220 oncology & carcinogenesis, Original Article, ddc:576, UniProt, General Agricultural and Biological Sciences, Gene, 030304 developmental biology, Information Systems
Abstract

UniProtKB/Swiss-Prot, a curated protein database, and dictyBase, the Model Organism Database for Dictyostelium discoideum, have established a collaboration to improve data sharing. One of the major steps in this effort was the 'Dicty annotation marathon', a week-long exercise with 30 annotators aimed at achieving a major increase in the number of D. discoideum proteins represented in UniProtKB/Swiss-Prot. The marathon led to the annotation of over 1000 D. discoideum proteins in UniProtKB/Swiss-Prot. Concomitantly, there were a large number of updates in dictyBase concerning gene symbols, protein names and gene models. This exercise demonstrates how UniProtKB/Swiss-Prot can work in very close cooperation with model organism databases and how the annotation of proteins can be accelerated through those collaborations.

Published
2009
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22. Hepatitis B virus DNA integration in a sequence homologous to v-erb-A and steroid receptor genes in a hepatocellular carcinoma

Author

Anne Dejean, Pierre Tiollais, Karl-Heinz Grzeschik, Lydie Bougueleret, Recombinaison et expression génétique, Institut Pasteur [Paris] (IP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Institut Pasteur [Paris] (IP), Westfälische Wilhelms-Universität Münster = University of Münster (WWU), This work was supported by NIH grant CA97300-02, the Economic European Community and the Faculte de Medecine Lariboisiere Saint-Louis (University of Paris VII)., Institut Pasteur [Paris]-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Institut Pasteur [Paris], Westfälische Wilhelms-Universität Münster (WWU), and Cheriet Rauline, Samia

Subjects
Male, Hepatitis B virus, Carcinoma, Hepatocellular, Hepatitis B virus DNA polymerase, [SDV]Life Sciences [q-bio], Receptors, Cell Surface, Viral transformation, MESH: Amino Acid Sequence, MESH: DNA Restriction Enzymes, Biology, MESH: Base Sequence, medicine.disease_cause, Cell Line, 03 medical and health sciences, 0302 clinical medicine, MESH: Liver Neoplasms, medicine, Humans, Amino Acid Sequence, MESH: Carcinoma, Hepatocellular, 030304 developmental biology, MESH: Receptors, Cell Surface, 0303 health sciences, Multidisciplinary, MESH: Humans, Base Sequence, Liver cell, Liver Neoplasms, Hepatobiliary disease, DNA Restriction Enzymes, Oncogene Proteins, Viral, HCCS, medicine.disease, Virology, digestive system diseases, MESH: Male, 3. Good health, MESH: Cell Line, MESH: DNA, Viral, [SDV] Life Sciences [q-bio], MESH: Hepatitis B virus, 030220 oncology & carcinogenesis, Hepatocellular carcinoma, DNA, Viral, MESH: Oncogene Proteins, Viral, Female, Carcinogenesis, MESH: Female
Abstract

International audience; Hepatitis B virus (HBV) is clearly involved in the aetiology of human hepatocellular carcinoma (HCC) and the finding of HBV DNA integration into human liver DNA in almost all HCCs studied suggested that these integrated viral sequences may be involved in liver oncogenesis. Several HBV integrations in different HCCs and HCC-derived cell lines have been analysed after molecular cloning without revealing any obvious role for HBV. From a comparison of a HBV integration site present in a particular HCC with the corresponding unoccupied site in the non-tumorous tissue of the same liver, we now report that HBV integration places the viral sequence next to a liver cell sequence which bears a striking resemblance to both an oncogene (v-erb-A) and the supposed DNA-binding domain of the human glucocorticoid receptor and human oestrogen receptor genes. We suggest that this gene, usually silent or transcribed at a very low level in normal hepatocytes, becomes inappropriately expressed as a consequence of HBV integration, thus contributing to the cell transformation.

Published
1986
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