Demo Data from EDBT 2026 / reviewers in the wild / expert
Rodrigo Lopez
dblp:49/5677
· DBLP profile ↗
18ranked-venue papers
2as first author
0since 2021 · last 2020
0000-0003-1256-7306ORCID · verified
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 18 · 2 first-author
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Interdisciplinary, comprehensive, and emerging computing
9 papers |
Bioinformatics and computational biology · 94% Computational science and engineering · 6% | |
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
High-performance computing · 100% |
Topics — the 15 heaviest of 16, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology
bioinformatics infrastructure |
0.4 | 1 | 2020 | The ELIXIR Core Data Resources: fundamental infrastructure for the life sciences · Bioinform. 2020 |
Bioinformatics and computational biology
functional genomics |
0.2 | 1 | 2014 | InterProScan 5: genome-scale protein function classification · Bioinform. 2014 |
Bioinformatics and computational biology › protein function prediction
protein classification |
0.2 | 1 | 2014 | InterProScan 5: genome-scale protein function classification · Bioinform. 2014 |
Bioinformatics and computational biology
protein function prediction |
0.2 | 1 | 2014 | InterProScan 5: genome-scale protein function classification · Bioinform. 2014 |
Bioinformatics and computational biology › biomedical text mining
semantic annotation |
0.2 | 1 | 2013 | EDAM: an ontology of bioinformatics operations, types of data and identifiers, topics and formats · Bioinform. 2013 |
Computational science and engineering › information retrieval
iterative search |
0.1 | 1 | 2012 | PSI-Search: iterative HOE-reduced profile SSEARCH searching · Bioinform. 2012 |
Bioinformatics and computational biology › protein function prediction › protein classification
protein family classification |
0.1 | 1 | 2012 | PSI-Search: iterative HOE-reduced profile SSEARCH searching · Bioinform. 2012 |
Bioinformatics and computational biology
sequence alignment |
0.1 | 1 | 2012 | PSI-Search: iterative HOE-reduced profile SSEARCH searching · Bioinform. 2012 |
Bioinformatics and computational biology › sequence analysis
sequence similarity search |
0.1 | 1 | 2012 | PSI-Search: iterative HOE-reduced profile SSEARCH searching · Bioinform. 2012 |
Bioinformatics and computational biology › data integration
biological database integration |
0.1 | 2 | 2002 | The EBI SRS server-new features · Bioinform. 2002 The EBI SRS server-recent developments · Bioinform. 2002 |
Bioinformatics and computational biology
data integration |
0.1 | 2 | 2002 | The EBI SRS server-new features · Bioinform. 2002 The EBI SRS server-recent developments · Bioinform. 2002 |
Bioinformatics and computational biology
multiple sequence alignment |
0.1 | 1 | 2007 | Clustal W and Clustal X version 2.0 · Bioinform. 2007 |
Bioinformatics and computational biology
sequence analysis |
0.1 | 1 | 2007 | Clustal W and Clustal X version 2.0 · Bioinform. 2007 |
High-performance computing
cluster computing |
0.1 | 1 | 2014 | InterProScan 5: genome-scale protein function classification · Bioinform. 2014 |
Bioinformatics and computational biology › biological database
protein sequence database |
0.0 | 1 | 2004 | UniProt archive · Bioinform. 2004 |
Methods — techniques the papers use, named apart from their topics
distributed data analysis · 0.4ontology engineering · 0.2smith-waterman local alignment · 0.1PSI-BLAST position-specific score matrix · 0.1progressive alignment · 0.1XML integration · 0.1virtual databases · 0.0profile · 0.0hidden markov model · 0.0fingerprint · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2020 | The ELIXIR Core Data Resources: fundamental infrastructure for the life sciencesabstractSUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Rachel Drysdale, Charles E. Cook, Robert Petryszak, Vivienne Baillie Gerritsen, Mary Barlow, Elisabeth Gasteiger, Franziska Gruhl, Jerry Lanfear, Rodrigo Lopez, Nicole Redaschi, Heinz Stockinger, Daniel Teixeira, Aravind Venkatesan, Alex Bateman, Alan J. Bridge, Guy Cochrane, Robert D. Finn, Frank Oliver Glöckner, Marc Hanauer, Thomas M. Keane, Luana Licata, Per Oksvold, Sandra E. Orchard, Christine A. Orengo, Helen E. Parkinson, Bengt Persson, Pablo Porras, Jordi Rambla De Argila, Ana Rath, Charlotte Rodwell, Ugis Sarkans, Dietmar Schomburg, Ian Sillitoe, J. Dylan Spalding, Mathias Uhlen, Sameer Velankar, Juan Antonio Vizcaíno, Kalle von Feilitzen, Christian von Mering, Andy Yates, Niklas Blomberg, Christine Durinx, Johanna R. McEntyre |
Bioinform. | 10 |
| 2014 | InterProScan 5: genome-scale protein function classificationabstractAbstract Motivation: Robust large-scale sequence analysis is a major challenge in modern genomic science, where biologists are frequently trying to characterize many millions of sequences. Here, we describe a new Java-based architecture for the widely used protein function prediction software package InterProScan. Developments include improvements and additions to the outputs of the software and the complete reimplementation of the software framework, resulting in a flexible and stable system that is able to use both multiprocessor machines and/or conventional clusters to achieve scalable distributed data analysis. InterProScan is freely available for download from the EMBl-EBI FTP site and the open source code is hosted at Google Code. Availability and implementation: InterProScan is distributed via FTP at ftp://ftp.ebi.ac.uk/pub/software/unix/iprscan/5/ and the source code is available from http://code.google.com/p/interproscan/. Contact: http://www.ebi.ac.uk/support or [email protected] or [email protected] Philip Jones, David Binns, Hsin-Yu Chang, Matthew Fraser, Weizhong Li 0001, Craig McAnulla, Hamish McWilliam, John Maslen, Alex L. Mitchell, Gift Nuka, Sebastien Pesseat, Antony F. Quinn, Amaia Sangrador-Vegas, Maxim Scheremetjew, Siew-Yit Yong, Rodrigo Lopez, Sarah Hunter |
Bioinform. | 16 |
| 2013 | EDAM: an ontology of bioinformatics operations, types of data and identifiers, topics and formatsabstractMOTIVATION: Advancing the search, publication and integration of bioinformatics tools and resources demands consistent machine-understandable descriptions. A comprehensive ontology allowing such descriptions is therefore required. RESULTS: EDAM is an ontology of bioinformatics operations (tool or workflow functions), types of data and identifiers, application domains and data formats. EDAM supports semantic annotation of diverse entities such as Web services, databases, programmatic libraries, standalone tools, interactive applications, data schemas, datasets and publications within bioinformatics. EDAM applies to organizing and finding suitable tools and data and to automating their integration into complex applications or workflows. It includes over 2200 defined concepts and has successfully been used for annotations and implementations. AVAILABILITY: The latest stable version of EDAM is available in OWL format from http://edamontology.org/EDAM.owl and in OBO format from http://edamontology.org/EDAM.obo. It can be viewed online at the NCBO BioPortal and the EBI Ontology Lookup Service. For documentation and license please refer to http://edamontology.org. This article describes version 1.2 available at http://edamontology.org/EDAM_1.2.owl. CONTACT: [email protected]. Jon C. Ison, Matús Kalas, Inge Jonassen, Dan M. Bolser, Mahmut Uludag, Hamish McWilliam, James Malone, Rodrigo Lopez, Steve Pettifer, Peter M. Rice |
Bioinform. | 8 |
| 2013 | The Enzyme Portal: A case study in applying user-centred design methods in bioinformaticsabstractUser-centred design (UCD) is a type of user interface design in which the needs and desires of users are taken into account at each stage of the design process for a service or product; often for software applications and websites. Its goal is to facilitate the design of software that is both useful and easy to use. To achieve this, you must characterise users' requirements, design suitable interactions to meet their needs, and test your designs using prototypes and real life scenarios.For bioinformatics, there is little practical information available regarding how to carry out UCD in practice. To address this we describe a complete, multi-stage UCD process used for creating a new bioinformatics resource for integrating enzyme information, called the Enzyme Portal (http://www.ebi.ac.uk/enzymeportal). This freely-available service mines and displays data about proteins with enzymatic activity from public repositories via a single search, and includes biochemical reactions, biological pathways, small molecule chemistry, disease information, 3D protein structures and relevant scientific literature.We employed several UCD techniques, including: persona development, interviews, 'canvas sort' card sorting, user workflows, usability testing and others. Our hope is that this case study will motivate the reader to apply similar UCD approaches to their own software design for bioinformatics. Indeed, we found the benefits included more effective decision-making for design ideas and technologies; enhanced team-working and communication; cost effectiveness; and ultimately a service that more closely meets the needs of our target audience. Paula de Matos, Jennifer A. Cham, Rafael Alcántara, Francis Rowland, Rodrigo Lopez, Christoph Steinbeck |
BMC Bioinform. | 6 |
| 2012 | Bioinformatics Training Network (BTN): a community resource for bioinformatics trainersabstractFunding bodies are increasingly recognizing the need to provide graduates and researchers with access to short intensive courses in a variety of disciplines, in order both to improve the general skills base and to provide solid foundations on which researchers may build their careers. In response to the development of 'high-throughput biology', the need for training in the field of bioinformatics, in particular, is seeing a resurgence: it has been defined as a key priority by many Institutions and research programmes and is now an important component of many grant proposals. Nevertheless, when it comes to planning and preparing to meet such training needs, tension arises between the reward structures that predominate in the scientific community which compel individuals to publish or perish, and the time that must be devoted to the design, delivery and maintenance of high-quality training materials. Conversely, there is much relevant teaching material and training expertise available worldwide that, were it properly organized, could be exploited by anyone who needs to provide training or needs to set up a new course. To do this, however, the materials would have to be centralized in a database and clearly tagged in relation to target audiences, learning objectives, etc. Ideally, they would also be peer reviewed, and easily and efficiently accessible for downloading. Here, we present the Bioinformatics Training Network (BTN), a new enterprise that has been initiated to address these needs and review it, respectively, to similar initiatives and collections. Maria Victoria Schneider, Peter Walter, Marie-Claude Blatter, James Watson, Michelle D. Brazas, Kristian Rother, Aidan Budd, Allegra Via, Celia W. G. van Gelder, Joachim Jacob, Pedro L. Fernandes, Tommi H. Nyrönen, Javier De Las Rivas, Thomas Blicher, Rafael C. Jiménez, Jane E. Loveland, Jennifer McDowall, Philip Jones, Brendan W. Vaughan, Rodrigo Lopez, Terri K. Attwood, Catherine Brooksbank |
Briefings Bioinform. | 20 |
| 2012 | PSI-Search: iterative HOE-reduced profile SSEARCH searchingabstractUNLABELLED: Iterative similarity searches with PSI-BLAST position-specific score matrices (PSSMs) find many more homologs than single searches, but PSSMs can be contaminated when homologous alignments are extended into unrelated protein domains-homologous over-extension (HOE). PSI-Search combines an optimal Smith-Waterman local alignment sequence search, using SSEARCH, with the PSI-BLAST profile construction strategy. An optional sequence boundary-masking procedure, which prevents alignments from being extended after they are initially included, can reduce HOE errors in the PSSM profile. Preventing HOE improves selectivity for both PSI-BLAST and PSI-Search, but PSI-Search has ~4-fold better selectivity than PSI-BLAST and similar sensitivity at 50% and 60% family coverage. PSI-Search is also produces 2- for 4-fold fewer false-positives than JackHMMER, but is ~5% less sensitive. AVAILABILITY AND IMPLEMENTATION: PSI-Search is available from the authors as a standalone implementation written in Perl for Linux-compatible platforms. It is also available through a web interface (www.ebi.ac.uk/Tools/sss/psisearch) and SOAP and REST Web Services (www.ebi.ac.uk/Tools/webservices). Weizhong Li 0001, Hamish McWilliam, Mickael Goujon, Andrew Peter Cowley, Rodrigo Lopez, William R. Pearson |
Bioinform. | 5 |
| 2010 | Fast and efficient searching of biological data resources - using EB-eyeabstractThe EB-eye is a fast and efficient search engine that provides easy and uniform access to the biological data resources hosted at the EMBL-EBI. Currently, users can access information from more than 62 distinct datasets covering some 400 million entries. The data resources represented in the EB-eye include: nucleotide and protein sequences at both the genomic and proteomic levels, structures ranging from chemicals to macro-molecular complexes, gene-expression experiments, binary level molecular interactions as well as reaction maps and pathway models, functional classifications, biological ontologies, and comprehensive literature libraries covering the biomedical sciences and related intellectual property. The EB-eye can be accessed over the web or programmatically using a SOAP Web Services interface. This allows its search and retrieval capabilities to be exploited in workflows and analytical pipe-lines. The EB-eye is a novel alternative to existing biological search and retrieval engines. In this article we describe in detail how to exploit its powerful capabilities. Franck Valentin, Silvano Squizzato, Mickael Goujon, Hamish McWilliam, Juri Pärn, Rodrigo Lopez |
Briefings Bioinform. | 6 |
| 2010 | Bioinformatics training: selecting an appropriate learning content management system - an example from the European Bioinformatics InstituteabstractToday's molecular life scientists are well educated in the emerging experimental tools of their trade, but when it comes to training on the myriad of resources and tools for dealing with biological data, a less ideal situation emerges. Often bioinformatics users receive no formal training on how to make the most of the bioinformatics resources and tools available in the public domain. The European Bioinformatics Institute, which is part of the European Molecular Biology Laboratory (EMBL-EBI), holds the world's most comprehensive collection of molecular data, and training the research community to exploit this information is embedded in the EBI's mission. We have evaluated eLearning, in parallel with face-to-face courses, as a means of training users of our data resources and tools. We anticipate that eLearning will become an increasingly important vehicle for delivering training to our growing user base, so we have undertaken an extensive review of Learning Content Management Systems (LCMSs). Here, we describe the process that we used, which considered the requirements of trainees, trainers and systems administrators, as well as taking into account our organizational values and needs. This review describes the literature survey, user discussions and scripted platform testing that we performed to narrow down our choice of platform from 36 to a single platform. We hope that it will serve as guidance for others who are seeking to incorporate eLearning into their bioinformatics training programmes. Victoria Ann Wright, Brendan W. Vaughan, Thomas Laurent 0002, Rodrigo Lopez, Catherine Brooksbank, Maria Victoria Schneider |
Briefings Bioinform. | 4 |
| 2008 | Data curation + process curation=data integration + scienceabstractIn bioinformatics, we are familiar with the idea of curated data as a prerequisite for data integration. We neglect, often to our cost, the curation and cataloguing of the processes that we use to integrate and analyse our data. Programmatic access to services, for data and processes, means that compositions of services can be made that represent the in silico experiments or processes that bioinformaticians perform. Data integration through workflows depends on being able to know what services exist and where to find those services. The large number of services and the operations they perform, their arbitrary naming and lack of documentation, however, mean that they can be difficult to use. The workflows themselves are composite processes that could be pooled and reused but only if they too can be found and understood. Thus appropriate curation, including semantic mark-up, would enable processes to be found, maintained and consequently used more easily. This broader view on semantic annotation is vital for full data integration that is necessary for the modern scientific analyses in biology. This article will brief the community on the current state of the art and the current challenges for process curation, both within and without the Life Sciences. Carole A. Goble, Robert Stevens 0001, Duncan Hull, Katy Wolstencroft, Rodrigo Lopez |
Briefings Bioinform. | 5 |
| 2008 | A tree-based conservation scoring method for short linear motifs in multiple alignments of protein sequencesabstractBACKGROUND: The structure of many eukaryotic cell regulatory proteins is highly modular. They are assembled from globular domains, segments of natively disordered polypeptides and short linear motifs. The latter are involved in protein interactions and formation of regulatory complexes. The function of such proteins, which may be difficult to define, is the aggregate of the subfunctions of the modules. It is therefore desirable to efficiently predict linear motifs with some degree of accuracy, yet sequence database searches return results that are not significant. RESULTS: We have developed a method for scoring the conservation of linear motif instances. It requires only primary sequence-derived information (e.g. multiple alignment and sequence tree) and takes into account the degenerate nature of linear motif patterns. On our benchmarking, the method accurately scores 86% of the known positive instances, while distinguishing them from random matches in 78% of the cases. The conservation score is implemented as a real time application designed to be integrated into other tools. It is currently accessible via a Web Service or through a graphical interface. CONCLUSION: The conservation score improves the prediction of linear motifs, by discarding those matches that are unlikely to be functional because they have not been conserved during the evolution of the protein sequences. It is especially useful for instances in non-structured regions of the proteins, where a domain masking filtering strategy is not applicable. Claudia Chica, Alberto Labarga, Cathryn M. Gould, Rodrigo Lopez, Toby J. Gibson |
BMC Bioinform. | 4 |
| 2007 | Clustal W and Clustal X version 2.0abstractSUMMARY: The Clustal W and Clustal X multiple sequence alignment programs have been completely rewritten in C++. This will facilitate the further development of the alignment algorithms in the future and has allowed proper porting of the programs to the latest versions of Linux, Macintosh and Windows operating systems. AVAILABILITY: The programs can be run on-line from the EBI web server: http://www.ebi.ac.uk/tools/clustalw2. The source code and executables for Windows, Linux and Macintosh computers are available from the EBI ftp site ftp://ftp.ebi.ac.uk/pub/software/clustalw2/ Mark A. Larkin, Gordon Blackshields, Nigel P. Brown, R. Chenna, Paul A. McGettigan, Hamish McWilliam, Franck Valentin, Iain M. Wallace, Andreas Wilm, Rodrigo Lopez, Julie Dawn Thompson, Toby J. Gibson, Desmond G. Higgins |
Bioinform. | 10 |
| 2004 | UniProt archiveabstractUniProt Archive (UniParc) is the most comprehensive, non-redundant protein sequence database available. Its protein sequences are retrieved from predominant, publicly accessible resources. All new and updated protein sequences are collected and loaded daily into UniParc for full coverage. To avoid redundancy, each unique sequence is stored only once with a stable protein identifier, which can be used later in UniParc to identify the same protein in all source databases. When proteins are loaded into the database, database cross-references are created to link them to the origins of the sequences. As a result, performing a sequence search against UniParc is equivalent to performing the same search against all databases cross-referenced by UniParc. UniParc contains only protein sequences and database cross-references; all other information must be retrieved from the source databases. Rasko Leinonen, Federico Garcia Diez, David Binns, Wolfgang Fleischmann, Rodrigo Lopez, Rolf Apweiler |
Bioinform. | 5 |
| 2003 | Public services from the European Bioinformatics InstituteabstractThe European Bioinformatics Institute (EBI) provides numerous free-of-charge, publicly available bioinformatics services that can be divided into the following categories: ftp downloads; data submissions processing and biological database production; access to query; analysis and retrieval systems and tools; user support; training and education and industry support through EBI's SME program. These services are all available at the website. It is imperative that EBI's data as well as the tools to analyse it efficiently are made available in a free and unambiguous way to the scientific community. An important part of the EBI's mission is to make this happen in a fast, reliable and efficient manner. This paper serves as a brief introduction to each of these services. Rodrigo Lopez, Karyn Duggan, Nicola Harte, Asif Kibria |
Briefings Bioinform. | 1 |
| 2003 | The European Bioinformatics Institute web site: a new viewabstractSUMMARY: The European Bioinformatics Institute (EBI), and outstation of the European Molecular Biology laboratory, has revamped its web site for the second time since 1997 in order to address increased user demand as well as establishing better uniformity and easier accessibility for the ever growing number of users and services it offers to the community. A GRID-like hardware infrastructure has been put in place to provide round the clock services in a redundant and reliable fashion. AVAILABILITY: http://www.ebi.ac.uk/ Rodrigo Lopez, Stephen Robinson, Asif Kibria, Nicola Harte, Gulam Patel, Rob Harper, Emmanuel Quevillon, Ville Silventoinen, Kimmo Kallio, Petteri Jokinen |
Bioinform. | 1 |
| 2002 | InterPro: An Integrated Documentation Resource for Protein Families, Domains and Functional SitesabstractThe exponential increase in the submission of nucleotide sequences to the nucleotide sequence database by genome sequencing centres has resulted in a need for rapid, automatic methods for classification of the resulting protein sequences. There are several signature and sequence cluster-based methods for protein classification, each resource having distinct areas of optimum application owing to the differences in the underlying analysis methods. In recognition of this, InterPro was developed as an integrated documentation resource for protein families, domains and functional sites, to rationalise the complementary efforts of the individual protein signature database projects. The member databases - PRINTS, PROSITE, Pfam, ProDom, SMART and TIGRFAMs - form the InterPro core. Related signatures from each member database are unified into single InterPro entries. Each InterPro entry includes a unique accession number, functional descriptions and literature references, and links are made back to the relevant member database(s). Release 4.0 of InterPro (November 2001) contains 4,691 entries, representing 3,532 families, 1,068 domains, 74 repeats and 15 sites of post-translational modification (PTMs) encoded by different regular expressions, profiles, fingerprints and hidden Markov models (HMMs). Each InterPro entry lists all the matches against SWISS-PROT and TrEMBL (2,141,621 InterPro hits from 586,124 SWISS-PROT and TrEMBL protein sequences). The database is freely accessible for text- and sequence-based searches. Nicola J. Mulder, Rolf Apweiler, Terri K. Attwood, Amos Bairoch, Alex Bateman, David Binns, Margaret Biswas, Paul Bradley, Peer Bork, Philipp Bucher, Richard R. Copley, Emmanuel Courcelle, Richard Durbin, Laurent Falquet, Wolfgang Fleischmann, Jérôme Gouzy, Sam Griffiths-Jones, Daniel H. Haft, Henning Hermjakob, Nicolas Hulo, Daniel Kahn, Alexander Kanapin, Maria Krestyaninova, Rodrigo Lopez, Ivica Letunic, Sue Orchard, Marco Pagni, David Peyruc, Chris P. Ponting, Florence Servant, Christian J. A. Sigrist |
Briefings Bioinform. | 24 |
| 2002 | The EBI SRS server-recent developmentsabstractAbstract Motivation: The current data explosion is intractable without advanced data management systems. The numerous data sets become really useful when they are interconnected under a uniform interface—representing the domain knowledge. The SRS has become an integration system for both data retrieval and applications for data analysis. It provides capabilities to search multiple databases by shared attributes and to query across databases fast and efficiently. Results: Here we present recent developments at the EBI SRS server (http://srs.ebi.ac.uk). The EBI SRS server contains today more than 130 biological databases and integrates more than 10 applications. It is a central resource for molecular biology data as well as a reference server for the latest developments in data integration. One of the latest additions to the EBI SRS server is the InterPro database—Integrated Resource of Protein Domains and Functional Sites. Distributed in XML format it became a turning point in low level XML–SRS integration. We present InterProScan as an example of data analysis applications, describe some advanced features of SRS6, and introduce the SRSQuickSearch JavaScript interfaces to SRS. Availability: SRS6 is a licensed product of LION Bioscience AG freely available for academics. The EBI SRS server (http://srs.ebi.ac.uk) is a free central resource for molecular biology data as well as a reference server for the latest developments in data integration. Contact: [email protected]; [email protected] Evgeny M. Zdobnov, Rodrigo Lopez, Rolf Apweiler, Thure Etzold |
Bioinform. | 2 |
| 2002 | The EBI SRS server-new featuresabstractMOTIVATION: Here we report on recent developments at the EBI SRS server (http://srs.ebi.ac.uk). SRS has become an integration system for both data retrieval and sequence analysis applications. The EBI SRS server is a primary gateway to major databases in the field of molecular biology produced and supported at EBI as well as European public access point to the MEDLINE database provided by US National Library of Medicine (NLM). It is a reference server for latest developments in data and application integration. The new additions include: concept of virtual databases, integration of XML databases like the Integrated Resource of Protein Domains and Functional Sites (InterPro), Gene Ontology (GO), MEDLINE, Metabolic pathways, etc., user friendly data representation in 'Nice views', SRSQuickSearch bookmarklets. AVAILABILITY: SRS6 is a licensed product of LION Bioscience AG freely available for academics. The EBI SRS server (http://srs.ebi.ac.uk) is a free central resource for molecular biology data as well as a reference server for the latest developments in data integration. Evgeny M. Zdobnov, Rodrigo Lopez, Rolf Apweiler, Thure Etzold |
Bioinform. | 2 |
| 2000 | InterPro-an integrated documentation resource for protein families, domains and functional sitesabstractMOTIVATION: InterPro is a new integrated documentation resource for protein families, domains and functional sites, developed initially as a means of rationalising the complementary efforts of the PROSITE, PRINTS, Pfam and ProDom database projects. RESULTS: Merged annotations from PRINTS, PROSITE and Pfam form the InterPro core. Each combined InterPro entry includes functional descriptions and literature references, and links are made back to the relevant parent database(s), allowing users to see at a glance whether a particular family or domain has associated patterns, profiles, fingerprints, etc. Merged and individual entries (i.e. those that have no counterpart in the companion resources) are assigned unique accession numbers. Release 1.2 of InterPro (June 2000) contains over 3000 entries, representing families, domains, repeats and sites of post-translational modification (PTMs) encoded by 6581 different regular expressions, profiles, fingerprints and Hidden Markov Models (HMMs). Each InterPro entry lists all the matches against SWISS-PROT and TrEMBL (more than 1000000 hits from 264333 different proteins out of 384572 in SWISS-PROT and TrEMBL). Rolf Apweiler, Terri K. Attwood, Amos Bairoch, Alex Bateman, Ewan Birney, Margaret Biswas, Philipp Bucher, Lorenzo Cerutti, Florence Corpet, Michael D. R. Croning, Richard Durbin, Laurent Falquet, Wolfgang Fleischmann, Jérôme Gouzy, Henning Hermjakob, Nicolas Hulo, Inge Jonassen, Daniel Kahn, Alexander Kanapin, Youla Karavidopoulou, Rodrigo Lopez, Beate Marx, Nicola J. Mulder, Thomas M. Oinn, Marco Pagni, Florence Servant, Christian J. A. Sigrist, Evgeny M. Zdobnov |
Bioinform. | 21 |