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Dive into the research topics where Claire O'Donovan is active.

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Featured researches published by Claire O'Donovan.


Nucleic Acids Research | 2003

The SWISS-PROT protein knowledgebase and its supplement TrEMBL in 2003

Brigitte Boeckmann; Amos Marc Bairoch; Rolf Apweiler; Marie-Claude Blatter; Anne Estreicher; Elisabeth Gasteiger; María Martín; Karine Michoud; Claire O'Donovan; Isabelle Phan; Sandrine Pilbout; Michel Schneider

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 [email protected].


Nucleic Acids Research | 2006

The Universal Protein Resource (UniProt): an expanding universe of protein information

Cathy H. Wu; Rolf Apweiler; Amos Marc Bairoch; Darren A. Natale; Winona C. Barker; Brigitte Boeckmann; Serenella Ferro; Elisabeth Gasteiger; Hongzhan Huang; Rodrigo Lopez; Michele Magrane; María Martín; Raja Mazumder; Claire O'Donovan; Nicole Redaschi; Baris E. Suzek

The Universal Protein Resource (UniProt) provides a central resource on protein sequences and functional annotation with three database components, each addressing a key need in protein bioinformatics. The UniProt Knowledgebase (UniProtKB), comprising the manually annotated UniProtKB/Swiss-Prot section and the automatically annotated UniProtKB/TrEMBL section, is the preeminent storehouse of protein annotation. The extensive cross-references, functional and feature annotations and literature-based evidence attribution enable scientists to analyse proteins and query across databases. The UniProt Reference Clusters (UniRef) speed similarity searches via sequence space compression by merging sequences that are 100% (UniRef100), 90% (UniRef90) or 50% (UniRef50) identical. Finally, the UniProt Archive (UniParc) stores all publicly available protein sequences, containing the history of sequence data with links to the source databases. UniProt databases continue to grow in size and in availability of information. Recent and upcoming changes to database contents, formats, controlled vocabularies and services are described. New download availability includes all major releases of UniProtKB, sequence collections by taxonomic division and complete proteomes. A bibliography mapping service has been added, and an ID mapping service will be available soon. UniProt databases can be accessed online at or downloaded at .


Nucleic Acids Research | 2009

The GOA database in 2009—an integrated Gene Ontology Annotation resource

Daniel Barrell; Emily Dimmer; Rachael P. Huntley; David Binns; Claire O'Donovan; Rolf Apweiler

The Gene Ontology Annotation (GOA) project at the EBI (http://www.ebi.ac.uk/goa) provides high-quality electronic and manual associations (annotations) of Gene Ontology (GO) terms to UniProt Knowledgebase (UniProtKB) entries. Annotations created by the project are collated with annotations from external databases to provide an extensive, publicly available GO annotation resource. Currently covering over 160 000 taxa, with greater than 32 million annotations, GOA remains the largest and most comprehensive open-source contributor to the GO Consortium (GOC) project. Over the last five years, the group has augmented the number and coverage of their electronic pipelines and a number of new manual annotation projects and collaborations now further enhance this resource. A range of files facilitate the download of annotations for particular species, and GO term information and associated annotations can also be viewed and downloaded from the newly developed GOA QuickGO tool (http://www.ebi.ac.uk/QuickGO), which allows users to precisely tailor their annotation set.


Bioinformatics | 2009

QuickGO: a web-based tool for Gene Ontology searching

David Binns; Emily Dimmer; Rachael P. Huntley; Daniel Barrell; Claire O'Donovan; Rolf Apweiler

Summary: QuickGO is a web-based tool that allows easy browsing of the Gene Ontology (GO) and all associated electronic and manual GO annotations provided by the GO Consortium annotation groups QuickGO has been a popular GO browser for many years, but after a recent redevelopment it is now able to offer a greater range of facilities including bulk downloads of GO annotation data which can be extensively filtered by a range of different parameters and GO slim set generation. Availability and Implementation: QuickGO has implemented in JavaScript, Ajax and HTML, with all major browsers supported. It can be queried online at http://www.ebi.ac.uk/QuickGO. The software for QuickGO is freely available under the Apache 2 licence and can be downloaded from http://www.ebi.ac.uk/QuickGO/installation.html Contact: [email protected]; [email protected]


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 | 2015

The GOA database: gene ontology annotation updates for 2015

Rachael P. Huntley; Tony Sawford; Prudence Mutowo-Meullenet; Aleksandra Shypitsyna; Carlos Bonilla; María Martín; Claire O'Donovan

The Gene Ontology Annotation (GOA) resource (http://www.ebi.ac.uk/GOA) provides evidence-based Gene Ontology (GO) annotations to proteins in the UniProt Knowledgebase (UniProtKB). Manual annotations provided by UniProt curators are supplemented by manual and automatic annotations from model organism databases and specialist annotation groups. GOA currently supplies 368 million GO annotations to almost 54 million proteins in more than 480 000 taxonomic groups. The resource now provides annotations to five times the number of proteins it did 4 years ago. As a member of the GO Consortium, we adhere to the most up-to-date Consortium-agreed annotation guidelines via the use of quality control checks that ensures that the GOA resource supplies high-quality functional information to proteins from a wide range of species. Annotations from GOA are freely available and are accessible through a powerful web browser as well as a variety of annotation file formats.


PLOS Biology | 2013

The COMBREX Project: Design, Methodology, and Initial Results

Brian P. Anton; Yi-Chien Chang; Peter Brown; Han-Pil Choi; Lina L. Faller; Jyotsna Guleria; Zhenjun Hu; Niels Klitgord; Ami Levy-Moonshine; Almaz Maksad; Varun Mazumdar; Mark McGettrick; Lais Osmani; Revonda Pokrzywa; John Rachlin; Rajeswari Swaminathan; Benjamin Allen; Genevieve Housman; Caitlin Monahan; Krista Rochussen; Kevin Tao; Ashok S. Bhagwat; Steven E. Brenner; Linda Columbus; Valérie de Crécy-Lagard; Donald J. Ferguson; Alexey Fomenkov; Giovanni Gadda; Richard D. Morgan; Andrei L. Osterman

Experimental data exists for only a vanishingly small fraction of sequenced microbial genes. This community page discusses the progress made by the COMBREX project to address this important issue using both computational and experimental resources.


Trends in Biotechnology | 2001

The human proteomics initiative (HPI)

Claire O'Donovan; Rolf Apweiler; Amos Marc Bairoch

The availability of the human genome sequence has enabled the exploration and exploitation of the human genome and proteome to begin. Research has now focussed on the annotation of the genome and in particular of the proteome. With expert annotation extracted from the literature by biologists as the foundation, it has been possible to expand into the areas of data mining and automatic annotation. With further development and integration of pattern recognition methods and the application of alignments clustering, proteome analysis can now be provided in a meaningful way. These various approaches have been integrated to attach, extract and combine as much relevant information as possible to the proteome. This resource should be valuable to users from both research and industry.


Nucleic Acids Research | 2017

Open Targets: a platform for therapeutic target identification and validation

Gautier Koscielny; Peter An; Denise R. Carvalho-Silva; Jennifer A. Cham; Luca Fumis; Rippa Gasparyan; Samiul Hasan; Nikiforos Karamanis; Michael Maguire; Eliseo Papa; Andrea Pierleoni; Miguel Pignatelli; Theo Platt; Francis Rowland; Priyanka Wankar; A. Patrícia Bento; Tony Burdett; Antonio Fabregat; Simon A. Forbes; Anna Gaulton; Cristina Yenyxe Gonzalez; Henning Hermjakob; Anne Hersey; Steven Jupe; Şenay Kafkas; Maria Keays; Catherine Leroy; Francisco-Javier Lopez; María Paula Magariños; James Malone

We have designed and developed a data integration and visualization platform that provides evidence about the association of known and potential drug targets with diseases. The platform is designed to support identification and prioritization of biological targets for follow-up. Each drug target is linked to a disease using integrated genome-wide data from a broad range of data sources. The platform provides either a target-centric workflow to identify diseases that may be associated with a specific target, or a disease-centric workflow to identify targets that may be associated with a specific disease. Users can easily transition between these target- and disease-centric workflows. The Open Targets Validation Platform is accessible at https://www.targetvalidation.org.


Current protocols in human genetics | 2015

Searching and Navigating UniProt Databases

Sangya Pundir; Michele Magrane; María Martín; Claire O'Donovan

The Universal Protein Resource (UniProt) is a comprehensive resource for protein sequence and annotation data. The UniProt Web site receives ∼400,000 unique visitors per month and is the primary means to access UniProt. It provides ten searchable datasets and three main tools. The key UniProt datasets are the UniProt Knowledgebase (UniProtKB), the UniProt Reference Clusters (UniRef), the UniProt Archive (UniParc), and protein sets for completely sequenced genomes (Proteomes). Other supporting datasets include information about proteins that is present in UniProtKB protein entries such as literature citations, taxonomy, and subcellular locations, among others. This paper focuses on how to use UniProt datasets. The basic protocol describes navigation and searching mechanisms for the UniProt datasets, while two alternative protocols build on the basic protocol to describe advanced search and query building.

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María Martín

European Bioinformatics Institute

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Rolf Apweiler

European Bioinformatics Institute

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Amos Marc Bairoch

Swiss Institute of Bioinformatics

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Michele Magrane

European Bioinformatics Institute

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Rachael P. Huntley

European Bioinformatics Institute

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Emily Dimmer

European Bioinformatics Institute

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Alex Bateman

European Bioinformatics Institute

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Fiona Lang

European Bioinformatics Institute

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Tony Sawford

European Bioinformatics Institute

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Elisabeth Gasteiger

Swiss Institute of Bioinformatics

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