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Dive into the research topics where Guillaume Keller is active.

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Featured researches published by Guillaume Keller.


Nucleic Acids Research | 2012

The UniProt-GO Annotation database in 2011

Emily Dimmer; Rachael P. Huntley; Yasmin Alam-Faruque; Tony Sawford; Claire O'Donovan; María Martín; Benoit Bely; Paul Browne; Wei Mun Chan; Ruth Eberhardt; Michael Gardner; Kati Laiho; D Legge; Michele Magrane; Klemens Pichler; Diego Poggioli; Harminder Sehra; Andrea H. Auchincloss; Kristian B. Axelsen; Marie-Claude Blatter; Emmanuel Boutet; Silvia Braconi-Quintaje; Lionel Breuza; Alan Bridge; Elizabeth Coudert; Anne Estreicher; L Famiglietti; Serenella Ferro-Rojas; Marc Feuermann; Arnaud Gos

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.


Nucleic Acids Research | 2009

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

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

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).


Nucleic Acids Research | 2012

UniPathway: a resource for the exploration and annotation of metabolic pathways

Anne Morgat; Eric Coissac; Elisabeth Coudert; Kristian B. Axelsen; Guillaume Keller; Amos Marc Bairoch; Alan Bridge; Lydie Bougueleret; Ioannis Xenarios; Alain Viari

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.


Nucleic Acids Research | 2013

HAMAP in 2013, new developments in the protein family classification and annotation system

Ivo Pedruzzi; Catherine Rivoire; Andrea H. Auchincloss; Elisabeth Coudert; Guillaume Keller; Edouard de Castro; Delphine Baratin; Béatrice A. Cuche; Lydie Bougueleret; Sylvain Poux; Nicole Redaschi; Ioannis Xenarios; Alan Bridge

HAMAP (High-quality Automated and Manual Annotation of Proteins—available at http://hamap.expasy.org/) is a system for the classification and annotation of protein sequences. It consists of a collection of manually curated family profiles for protein classification, and associated annotation rules that specify annotations that apply to family members. HAMAP was originally developed to support the manual curation of UniProtKB/Swiss-Prot records describing microbial proteins. Here we describe new developments in HAMAP, including the extension of HAMAP to eukaryotic proteins, the use of HAMAP in the automated annotation of UniProtKB/TrEMBL, providing high-quality annotation for millions of protein sequences, and the future integration of HAMAP into a unified system for UniProtKB annotation, UniRule. HAMAP is continuously updated by expert curators with new family profiles and annotation rules as new protein families are characterized. The collection of HAMAP family classification profiles and annotation rules can be browsed and viewed on the HAMAP website, which also provides an interface to scan user sequences against HAMAP profiles.


Nucleic Acids Research | 2015

HAMAP in 2015: updates to the protein family classification and annotation system

Ivo Pedruzzi; Catherine Rivoire; Andrea H. Auchincloss; Elisabeth Coudert; Guillaume Keller; Edouard de Castro; Delphine Baratin; Béatrice A. Cuche; Lydie Bougueleret; Sylvain Poux; Nicole Redaschi; Ioannis Xenarios; Alan Bridge

HAMAP (High-quality Automated and Manual Annotation of Proteins—available at http://hamap.expasy.org/) is a system for the automatic classification and annotation of protein sequences. HAMAP provides annotation of the same quality and detail as UniProtKB/Swiss-Prot, using manually curated profiles for protein sequence family classification and expert curated rules for functional annotation of family members. HAMAP data and tools are made available through our website and as part of the UniRule pipeline of UniProt, providing annotation for millions of unreviewed sequences of UniProtKB/TrEMBL. Here we report on the growth of HAMAP and updates to the HAMAP system since our last report in the NAR Database Issue of 2013. We continue to augment HAMAP with new family profiles and annotation rules as new protein families are characterized and annotated in UniProtKB/Swiss-Prot; the latest version of HAMAP (as of 3 September 2014) contains 1983 family classification profiles and 1998 annotation rules (up from 1780 and 1720). We demonstrate how the complex logic of HAMAP rules allows for precise annotation of individual functional variants within large homologous protein families. We also describe improvements to our web-based tool HAMAP-Scan which simplify the classification and annotation of sequences, and the incorporation of an improved sequence-profile search algorithm.


Database | 2009

Collaborative annotation of genes and proteins between UniProtKB/Swiss-Prot and dictyBase

Pascale Gaudet; Lydie Lane; Petra Fey; Alan Bridge; Sylvain Poux; Andrea H. Auchincloss; Kristian B. Axelsen; S. Braconi Quintaje; Emmanuel Boutet; P. Brown; Elisabeth Coudert; Ruchira S. Datta; W.C. de Lima; T. de Oliveira Lima; Séverine Duvaud; N. Farriol-Mathis; S. Ferro Rojas; Marc Feuermann; Alain Gateau; Ursula Hinz; Chantal Hulo; J. James; S. Jimenez; Florence Jungo; Guillaume Keller; P Lemercier; Damien Lieberherr; M. Moinat; A. Nikolskaya; I. Pedruzzi

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.

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Alan Bridge

Swiss Institute of Bioinformatics

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Andrea H. Auchincloss

Swiss Institute of Bioinformatics

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Elisabeth Coudert

Swiss Institute of Bioinformatics

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Lydie Bougueleret

Swiss Institute of Bioinformatics

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Catherine Rivoire

Swiss Institute of Bioinformatics

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Delphine Baratin

Swiss Institute of Bioinformatics

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Edouard de Castro

Swiss Institute of Bioinformatics

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Ioannis Xenarios

Swiss Institute of Bioinformatics

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Kristian B. Axelsen

Swiss Institute of Bioinformatics

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Sylvain Poux

Swiss Institute of Bioinformatics

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