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Michel Schneider

Bio: Michel Schneider is an academic researcher from Swiss Institute of Bioinformatics. The author has contributed to research in topics: UniProt & Microbubbles. The author has an hindex of 34, co-authored 61 publications receiving 11674 citations. Previous affiliations of Michel Schneider include University of Geneva & University of Basel.


Papers
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Journal ArticleDOI
Alex Bateman, Maria Jesus Martin, Claire O'Donovan, Michele Magrane, Rolf Apweiler, Emanuele Alpi, Ricardo Antunes, Joanna Arganiska, Benoit Bely, Mark Bingley, Carlos Bonilla, Ramona Britto, Borisas Bursteinas, Gayatri Chavali, Elena Cibrian-Uhalte, Alan Wilter Sousa da Silva, Maurizio De Giorgi, Tunca Doğan, Francesco Fazzini, Paul Gane, Leyla Jael Garcia Castro, Penelope Garmiri, Emma Hatton-Ellis, Reija Hieta, Rachael P. Huntley, Duncan Legge, W Liu, Jie Luo, Alistair MacDougall, Prudence Mutowo, Andrew Nightingale, Sandra Orchard, Klemens Pichler, Diego Poggioli, Sangya Pundir, Luis Pureza, Guoying Qi, Steven Rosanoff, Rabie Saidi, Tony Sawford, Aleksandra Shypitsyna, Edward Turner, Vladimir Volynkin, Tony Wardell, Xavier Watkins, Hermann Zellner, Andrew Peter Cowley, Luis Figueira, Weizhong Li, Hamish McWilliam, Rodrigo Lopez, Ioannis Xenarios, Lydie Bougueleret, Alan Bridge, Sylvain Poux, Nicole Redaschi, Lucila Aimo, Ghislaine Argoud-Puy, Andrea H. Auchincloss, Kristian B. Axelsen, Parit Bansal, Delphine Baratin, Marie Claude Blatter, Brigitte Boeckmann, Jerven Bolleman, Emmanuel Boutet, Lionel Breuza, Cristina Casal-Casas, Edouard de Castro, Elisabeth Coudert, Béatrice A. Cuche, M Doche, Dolnide Dornevil, Séverine Duvaud, Anne Estreicher, L Famiglietti, Marc Feuermann, Elisabeth Gasteiger, Sebastien Gehant, Vivienne Baillie Gerritsen, Arnaud Gos, Nadine Gruaz-Gumowski, Ursula Hinz, Chantal Hulo, Florence Jungo, Guillaume Keller, Vicente Lara, P Lemercier, Damien Lieberherr, Thierry Lombardot, Xavier D. Martin, Patrick Masson, Anne Morgat, Teresa Batista Neto, Nevila Nouspikel, Salvo Paesano, Ivo Pedruzzi, Sandrine Pilbout, Monica Pozzato, Manuela Pruess, Catherine Rivoire, Bernd Roechert, Michel Schneider, Christian J. A. Sigrist, K Sonesson, S Staehli, Andre Stutz, Shyamala Sundaram, Michael Tognolli, Laure Verbregue, Anne Lise Veuthey, Cathy H. Wu, Cecilia N. Arighi, Leslie Arminski, Chuming Chen, Yongxing Chen, John S. Garavelli, Hongzhan Huang, Kati Laiho, Peter B. McGarvey, Darren A. Natale, Baris E. Suzek, C. R. Vinayaka, Qinghua Wang, Yuqi Wang, Lai-Su L. Yeh, Meher Shruti Yerramalla, Jian Zhang 
TL;DR: An annotation score for all entries in UniProt is introduced to represent the relative amount of knowledge known about each protein to help identify which proteins are the best characterized and most informative for comparative analysis.
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/.

4,050 citations

Journal ArticleDOI
TL;DR: The SWISS-PROT protein knowledgebase connects amino acid sequences with the current knowledge in the Life Sciences by providing an interdisciplinary overview of relevant information by bringing together experimental results, computed features and sometimes even contradictory conclusions.
Abstract: The SWISS-PROT protein knowledgebase (http://www.expasy.org/sprot/ and http://www.ebi.ac.uk/swissprot/) connects amino acid sequences with the current knowledge in the Life Sciences. Each protein entry provides an interdisciplinary overview of relevant information by bringing together experimental results, computed features and sometimes even contradictory conclusions. Detailed expertise that goes beyond the scope of SWISS-PROT is made available via direct links to specialised databases. SWISS-PROT provides annotated entries for all species, but concentrates on the annotation of entries from human (the HPI project) and other model organisms to ensure the presence of high quality annotation for representative members of all protein families. Part of the annotation can be transferred to other family members, as is already done for microbes by the High-quality Automated and Manual Annotation of microbial Proteomes (HAMAP) project. Protein families and groups of proteins are regularly reviewed to keep up with current scientific findings. Complementarily, TrEMBL strives to comprise all protein sequences that are not yet represented in SWISS-PROT, by incorporating a perpetually increasing level of mostly automated annotation. Researchers are welcome to contribute their knowledge to the scientific community by submitting relevant findings to SWISS-PROT at swiss-prot@expasy.org.

3,440 citations

Book ChapterDOI
TL;DR: The purpose of this chapter is to present a guided tour of a UniProtKB/Swiss-Prot entry, paying particular attention to the specificities of plant protein annotation, and some of the tools and databases that are linked to each entry.
Abstract: The Swiss Institute of Bioinformatics (SIB), the European Bioinformatics Institute (EBI), and the Protein Information Resource (PIR) form the Universal Protein Resource (UniProt) consortium. Its main goal is to provide the scientific community with a central resource for protein sequences and functional information. The UniProt consortium maintains the UniProt KnowledgeBase (UniProtKB) and several supplementary databases including the UniProt Reference Clusters (UniRef) and the UniProt Archive (UniParc). (1) UniProtKB is a comprehensive protein sequence knowledgebase that consists of two sections: UniProtKB/Swiss-Prot, which contains manually annotated entries, and UniProtKB/TrEMBL, which contains computer-annotated entries. UniProtKB/Swiss-Prot entries contain information curated by biologists and provide users with cross-links to about 100 external databases and with access to additional information or tools. (2) The UniRef databases (UniRef100, UniRef90, and UniRef50) define clusters of protein sequences that share 100, 90, or 50% identity. (3) The UniParc database stores and maps all publicly available protein sequence data, including obsolete data excluded from UniProtKB. The UniProt databases can be accessed online (http://www.uniprot.org/) or downloaded in several formats (ftp://ftp.uniprot.org/pub). New releases are published every 2 weeks. The purpose of this chapter is to present a guided tour of a UniProtKB/Swiss-Prot entry, paying particular attention to the specificities of plant protein annotation. We will also present some of the tools and databases that are linked to each entry.

615 citations

Book ChapterDOI
TL;DR: The purpose of this chapter is to present a guided tour of a UniProtKB/Swiss-Prot entry, and some of the tools and databases that are linked to each entry.
Abstract: The Universal Protein Resource (UniProt, http://www.uniprot.org ) consortium is an initiative of the SIB Swiss Institute of Bioinformatics (SIB), the European Bioinformatics Institute (EBI) and the Protein Information Resource (PIR) to provide the scientific community with a central resource for protein sequences and functional information. The UniProt consortium maintains the UniProt KnowledgeBase (UniProtKB), updated every 4 weeks, and several supplementary databases including the UniProt Reference Clusters (UniRef) and the UniProt Archive (UniParc).The Swiss-Prot section of the UniProt KnowledgeBase (UniProtKB/Swiss-Prot) contains publicly available expertly manually annotated protein sequences obtained from a broad spectrum of organisms. Plant protein entries are produced in the frame of the Plant Proteome Annotation Program (PPAP), with an emphasis on characterized proteins of Arabidopsis thaliana and Oryza sativa. High level annotations provided by UniProtKB/Swiss-Prot are widely used to predict annotation of newly available proteins through automatic pipelines.The purpose of this chapter is to present a guided tour of a UniProtKB/Swiss-Prot entry. We will also present some of the tools and databases that are linked to each entry.

590 citations

Journal ArticleDOI
Judith A. Blake, Mary E. Dolan, H. Drabkin, David P. Hill, Li N, D. Sitnikov, Susan M. Bridges1, Shane C. Burgess1, Teresia Buza1, Fiona M. McCarthy1, Divyaswetha Peddinti1, Lakshmi Pillai1, Seth Carbon2, Heiko Dietze2, Amelia Ireland2, Suzanna E. Lewis2, Christopher J. Mungall2, Pascale Gaudet3, Chrisholm Rl3, Petra Fey3, Warren A. Kibbe3, S. Basu3, Deborah A. Siegele4, B. K. McIntosh4, Daniel P. Renfro4, Adrienne E. Zweifel4, James C. Hu4, Nicholas H. Brown5, Susan Tweedie5, Yasmin Alam-Faruque6, Rolf Apweiler6, A. Auchinchloss6, Kristian B. Axelsen6, Benoit Bely6, M. C. Blatter6, Bonilla C6, Bouguerleret L6, Emmanuel Boutet6, Lionel Breuza6, Alan Bridge6, W. M. Chan6, Gayatri Chavali6, Elisabeth Coudert6, E. Dimmer6, Anne Estreicher6, L Famiglietti6, Marc Feuermann6, Arnaud Gos6, Nadine Gruaz-Gumowski6, Hieta R6, Hinz C6, Chantal Hulo6, Rachael P. Huntley6, J. James6, Florence Jungo6, Guillaume Keller6, Kati Laiho6, Duncan Legge6, P. Lemercier6, Damien Lieberherr6, Michele Magrane6, Maria Jesus Martin6, Patrick Masson6, Mutowo-Muellenet P6, Claire O'Donovan6, Ivo Pedruzzi6, Klemens Pichler6, Diego Poggioli6, Porras Millán P6, Sylvain Poux6, Catherine Rivoire6, Bernd Roechert6, Tony Sawford6, Michel Schneider6, Andre Stutz6, Shyamala Sundaram6, Michael Tognolli6, Ioannis Xenarios6, Foulgar R, Jane Lomax, Paola Roncaglia, Varsha K. Khodiyar7, Ruth C. Lovering7, Philippa J. Talmud7, Marcus C. Chibucos8, Giglio Mg9, Hsin-Yu Chang9, Sarah Hunter9, Craig McAnulla9, Alex L. Mitchell9, Sangrador A9, Stephan R, Midori A. Harris5, Stephen G. Oliver5, Kim Rutherford5, Wood7, Jürg Bähler7, Antonia Lock7, Paul J. Kersey9, McDowall Dm9, Daniel M. Staines9, Melinda R. Dwinell10, Mary Shimoyama10, Stan Laulederkind10, Tom Hayman10, Shur-Jen Wang10, Timothy F. Lowry10, P D'Eustachio11, Lisa Matthews11, Rama Balakrishnan12, Gail Binkley12, J. M. Cherry12, Maria C. Costanzo12, Selina S. Dwight12, Engel12, Dianna G. Fisk12, Benjamin C. Hitz12, Eurie L. Hong12, Kalpana Karra12, Miyasato12, Robert S. Nash12, Julie Park12, Marek S. Skrzypek12, Shuai Weng12, Edith D. Wong12, Tanya Z. Berardini13, Eva Huala13, Huaiyu Mi14, Paul Thomas14, Juancarlos Chan15, Ranjana Kishore15, Paul W. Sternberg15, Van Auken K15, Doug Howe16, Monte Westerfield16 
TL;DR: The Gene Ontology (GO) Consortium is a community-based bioinformatics resource that classifies gene product function through the use of structured, controlled vocabularies and has been expanded not only to cover new areas of biology through focused interaction with experts, but also to capture greater specificity in all areas of the ontology.
Abstract: The Gene Ontology (GO) Consortium (GOC, http://www.geneontology.org) is a community-based bioinformatics resource that classifies gene product function through the use of structured, controlled vocabularies. Over the past year, the GOC has implemented several processes to increase the quantity, quality and specificity of GO annotations. First, the number of manual, literature-based annotations has grown at an increasing rate. Second, as a result of a new 'phylogenetic annotation' process, manually reviewed, homology-based annotations are becoming available for a broad range of species. Third, the quality of GO annotations has been improved through a streamlined process for, and automated quality checks of, GO annotations deposited by different annotation groups. Fourth, the consistency and correctness of the ontology itself has increased by using automated reasoning tools. Finally, the GO has been expanded not only to cover new areas of biology through focused interaction with experts, but also to capture greater specificity in all areas of the ontology using tools for adding new combinatorial terms. The GOC works closely with other ontology developers to support integrated use of terminologies. The GOC supports its user community through the use of e-mail lists, social media and web-based resources.

492 citations


Cited by
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Journal ArticleDOI
TL;DR: In addition to maintaining the GenBank(R) nucleic acid sequence database, the National Center for Biotechnology Information (NCBI) provides data analysis and retrieval resources for the data in GenBank and other biological data made available through NCBI’s website.
Abstract: In addition to maintaining the GenBank(R) nucleic acid sequence database, the National Center for Biotechnology Information (NCBI) provides data analysis and retrieval resources for the data in GenBank and other biological data made available through NCBI's website. NCBI resources include Entrez, PubMed, PubMed Central, LocusLink, the NCBI Taxonomy Browser, BLAST, BLAST Link (BLink), Electronic PCR, OrfFinder, Spidey, RefSeq, UniGene, HomoloGene, ProtEST, dbMHC, dbSNP, Cancer Chromosome Aberration Project (CCAP), Entrez Genomes and related tools, the Map Viewer, Model Maker, Evidence Viewer, Clusters of Orthologous Groups (COGs) database, Retroviral Genotyping Tools, SARS Coronavirus Resource, SAGEmap, Gene Expression Omnibus (GEO), Online Mendelian Inheritance in Man (OMIM), the Molecular Modeling Database (MMDB), the Conserved Domain Database (CDD) and the Conserved Domain Architecture Retrieval Tool (CDART). Augmenting many of the web applications are custom implementations of the BLAST program optimized to search specialized data sets. All of the resources can be accessed through the NCBI home page at: http://www.ncbi.nlm.nih.gov.

9,604 citations

Journal ArticleDOI
TL;DR: A fully automated service for annotating bacterial and archaeal genomes that identifies protein-encoding, rRNA and tRNA genes, assigns functions to the genes, predicts which subsystems are represented in the genome, uses this information to reconstruct the metabolic network and makes the output easily downloadable for the user.
Abstract: The number of prokaryotic genome sequences becoming available is growing steadily and is growing faster than our ability to accurately annotate them. We describe a fully automated service for annotating bacterial and archaeal genomes. The service identifies protein-encoding, rRNA and tRNA genes, assigns functions to the genes, predicts which subsystems are represented in the genome, uses this information to reconstruct the metabolic network and makes the output easily downloadable for the user. In addition, the annotated genome can be browsed in an environment that supports comparative analysis with the annotated genomes maintained in the SEED environment. The service normally makes the annotated genome available within 12–24 hours of submission, but ultimately the quality of such a service will be judged in terms of accuracy, consistency, and completeness of the produced annotations. We summarize our attempts to address these issues and discuss plans for incrementally enhancing the service. By providing accurate, rapid annotation freely to the community we have created an important community resource. The service has now been utilized by over 120 external users annotating over 350 distinct genomes.

9,397 citations

Journal ArticleDOI
TL;DR: Jalview 2 is a system for interactive WYSIWYG editing, analysis and annotation of multiple sequence alignments that employs web services for sequence alignment, secondary structure prediction and the retrieval of alignments, sequences, annotation and structures from public databases and any DAS 1.53 compliant sequence or annotation server.
Abstract: Summary: Jalview Version 2 is a system for interactive WYSIWYG editing, analysis and annotation of multiple sequence alignments. Core features include keyboard and mouse-based editing, multiple views and alignment overviews, and linked structure display with Jmol. Jalview 2 is available in two forms: a lightweight Java applet for use in web applications, and a powerful desktop application that employs web services for sequence alignment, secondary structure prediction and the retrieval of alignments, sequences, annotation and structures from public databases and any DAS 1.53 compliant sequence or annotation server. Availability: The Jalview 2 Desktop application and JalviewLite applet are made freely available under the GPL, and can be downloaded from www.jalview.org Contact: g.j.barton@dundee.ac.uk

7,926 citations

Journal ArticleDOI
TL;DR: The FAIR Data Principles as mentioned in this paper are a set of data reuse principles that focus on enhancing the ability of machines to automatically find and use the data, in addition to supporting its reuse by individuals.
Abstract: There is an urgent need to improve the infrastructure supporting the reuse of scholarly data. A diverse set of stakeholders—representing academia, industry, funding agencies, and scholarly publishers—have come together to design and jointly endorse a concise and measureable set of principles that we refer to as the FAIR Data Principles. The intent is that these may act as a guideline for those wishing to enhance the reusability of their data holdings. Distinct from peer initiatives that focus on the human scholar, the FAIR Principles put specific emphasis on enhancing the ability of machines to automatically find and use the data, in addition to supporting its reuse by individuals. This Comment is the first formal publication of the FAIR Principles, and includes the rationale behind them, and some exemplar implementations in the community.

7,602 citations

Journal ArticleDOI
TL;DR: The Swiss-Prot, TrEMBL and PIR protein database activities have united to form the Universal Protein Knowledgebase (UniProt), which is to provide a comprehensive, fully classified, richly and accurately annotated protein sequence knowledgebase, with extensive cross-references and query interfaces.
Abstract: To provide the scientific community with a single, centralized, authoritative resource for protein sequences and functional information, the Swiss-Prot, TrEMBL and PIR protein database activities have united to form the Universal Protein Knowledgebase (UniProt) consortium. Our mission is to provide a comprehensive, fully classified, richly and accurately annotated protein sequence knowledgebase, with extensive cross-references and query interfaces. The central database will have two sections, corresponding to the familiar Swiss-Prot (fully manually curated entries) and TrEMBL (enriched with automated classification, annotation and extensive cross-references). For convenient sequence searches, UniProt also provides several non-redundant sequence databases. The UniProt NREF (UniRef) databases provide representative subsets of the knowledgebase suitable for efficient searching. The comprehensive UniProt Archive (UniParc) is updated daily from many public source databases. The UniProt databases can be accessed online (http://www.uniprot.org) or downloaded in several formats (ftp://ftp.uniprot.org/pub). The scientific community is encouraged to submit data for inclusion in UniProt.

7,298 citations