Network


Latest external collaboration on country level. Dive into details by clicking on the dots.

Hotspot


Dive into the research topics where Nicola Mulder is active.

Publication


Featured researches published by Nicola Mulder.


Nucleic Acids Research | 2009

InterPro: the integrative protein signature database

Sarah Hunter; Rolf Apweiler; Teresa K. Attwood; Amos Marc Bairoch; Alex Bateman; David Binns; Peer Bork; Ujjwal Das; Louise Daugherty; Lauranne Duquenne; Robert D. Finn; Julian Gough; Daniel H. Haft; Nicolas Hulo; Daniel Kahn; Elizabeth Kelly; Aurélie Laugraud; Ivica Letunic; David M. Lonsdale; Rodrigo Lopez; John Maslen; Craig McAnulla; Jennifer McDowall; Jaina Mistry; Alex L. Mitchell; Nicola Mulder; Darren A. Natale; Christine A. Orengo; Antony F. Quinn; Jeremy D. Selengut

The InterPro database (http://www.ebi.ac.uk/interpro/) integrates together predictive models or ‘signatures’ representing protein domains, families and functional sites from multiple, diverse source databases: Gene3D, PANTHER, Pfam, PIRSF, PRINTS, ProDom, PROSITE, SMART, SUPERFAMILY and TIGRFAMs. Integration is performed manually and approximately half of the total ∼58 000 signatures available in the source databases belong to an InterPro entry. Recently, we have started to also display the remaining un-integrated signatures via our web interface. Other developments include the provision of non-signature data, such as structural data, in new XML files on our FTP site, as well as the inclusion of matchless UniProtKB proteins in the existing match XML files. The web interface has been extended and now links out to the ADAN predicted protein–protein interaction database and the SPICE and Dasty viewers. The latest public release (v18.0) covers 79.8% of UniProtKB (v14.1) and consists of 16 549 entries. InterPro data may be accessed either via the web address above, via web services, by downloading files by anonymous FTP or by using the InterProScan search software (http://www.ebi.ac.uk/Tools/InterProScan/).


Nucleic Acids Research | 2012

InterPro in 2011: new developments in the family and domain prediction database

Sarah Hunter; P. D. Jones; Alex L. Mitchell; Rolf Apweiler; Teresa K. Attwood; Alex Bateman; Thomas Bernard; David Binns; Peer Bork; Sarah W. Burge; Edouard de Castro; Penny Coggill; Matthew Corbett; Ujjwal Das; Louise Daugherty; Lauranne Duquenne; Robert D. Finn; Matthew Fraser; Julian Gough; Daniel H. Haft; Nicolas Hulo; Daniel Kahn; Elizabeth Kelly; Ivica Letunic; David M. Lonsdale; Rodrigo Lopez; John Maslen; Craig McAnulla; Jennifer McDowall; Conor McMenamin

InterPro (http://www.ebi.ac.uk/interpro/) is a database that integrates diverse information about protein families, domains and functional sites, and makes it freely available to the public via Web-based interfaces and services. Central to the database are diagnostic models, known as signatures, against which protein sequences can be searched to determine their potential function. InterPro has utility in the large-scale analysis of whole genomes and meta-genomes, as well as in characterizing individual protein sequences. Herein we give an overview of new developments in the database and its associated software since 2009, including updates to database content, curation processes and Web and programmatic interfaces.


Nucleic Acids Research | 2004

InterPro, progress and status in 2005

Nicola Mulder; Rolf Apweiler; Teresa K. Attwood; Amos Marc Bairoch; Alex Bateman; David Binns; Paul Bradley; Peer Bork; Phillip Bucher; Lorenzo Cerutti; Richard R. Copley; Emmanuel Courcelle; Ujjwal Das; Richard Durbin; Wolfgang Fleischmann; Julian Gough; Daniel H. Haft; Nicola Harte; Nicolas Hulo; Daniel Kahn; Alexander Kanapin; Maria Krestyaninova; David M. Lonsdale; Rodrigo Lopez; Ivica Letunic; John Maslen; Jennifer McDowall; Alex L. Mitchell; Anastasia N. Nikolskaya; Sandra Orchard

InterPro, an integrated documentation resource of protein families, domains and functional sites, was created to integrate the major protein signature databases. Currently, it includes PROSITE, Pfam, PRINTS, ProDom, SMART, TIGRFAMs, PIRSF and SUPERFAMILY. Signatures are manually integrated into InterPro entries that are curated to provide biological and functional information. Annotation is provided in an abstract, Gene Ontology mapping and links to specialized databases. New features of InterPro include extended protein match views, taxonomic range information and protein 3D structure data. One of the new match views is the InterPro Domain Architecture view, which shows the domain composition of protein matches. Two new entry types were introduced to better describe InterPro entries: these are active site and binding site. PIRSF and the structure-based SUPERFAMILY are the latest member databases to join InterPro, and CATH and PANTHER are soon to be integrated. InterPro release 8.0 contains 11 007 entries, representing 2573 domains, 8166 families, 201 repeats, 26 active sites, 21 binding sites and 20 post-translational modification sites. InterPro covers over 78% of all proteins in the Swiss-Prot and TrEMBL components of UniProt. The database is available for text- and sequence-based searches via a webserver (http://www.ebi.ac.uk/interpro), and for download by anonymous FTP (ftp://ftp.ebi.ac.uk/pub/databases/interpro).


Nucleic Acids Research | 2007

New developments in the InterPro database

Nicola Mulder; Rolf Apweiler; Teresa K. Attwood; Amos Marc Bairoch; Alex Bateman; David Binns; Peer Bork; Virginie Buillard; Lorenzo Cerutti; Richard R. Copley; Emmanuel Courcelle; Ujjwal Das; Louise Daugherty; Mark Dibley; Robert D. Finn; Wolfgang Fleischmann; Julian Gough; Daniel H. Haft; Nicolas Hulo; Sarah Hunter; Daniel Kahn; Alexander Kanapin; Anish Kejariwal; Alberto Labarga; Petra S. Langendijk-Genevaux; David M. Lonsdale; Rodrigo Lopez; Ivica Letunic; John Maslen; Craig McAnulla

InterPro is an integrated resource for protein families, domains and functional sites, which integrates the following protein signature databases: PROSITE, PRINTS, ProDom, Pfam, SMART, TIGRFAMs, PIRSF, SUPERFAMILY, Gene3D and PANTHER. The latter two new member databases have been integrated since the last publication in this journal. There have been several new developments in InterPro, including an additional reading field, new database links, extensions to the web interface and additional match XML files. InterPro has always provided matches to UniProtKB proteins on the website and in the match XML file on the FTP site. Additional matches to proteins in UniParc (UniProt archive) are now available for download in the new match XML files only. The latest InterPro release (13.0) contains more than 13 000 entries, covering over 78% of all proteins in UniProtKB. The database is available for text- and sequence-based searches via a webserver (), and for download by anonymous FTP (). The InterProScan search tool is now also available via a web service at .


Nucleic Acids Research | 2008

The Gene Ontology project in 2008

Midori A. Harris; Jennifer I. Deegan; Amelia Ireland; Jane Lomax; Michael Ashburner; Susan Tweedie; Seth Carbon; Suzanna E. Lewis; Christopher J. Mungall; John Richter; Karen Eilbeck; Judith A. Blake; Alexander D. Diehl; Mary E. Dolan; Harold Drabkin; Janan T. Eppig; David P. Hill; Ni Li; Martin Ringwald; Rama Balakrishnan; Gail Binkley; J. Michael Cherry; Karen R. Christie; Maria C. Costanzo; Qing Dong; Stacia R. Engel; Dianna G. Fisk; Jodi E. Hirschman; Benjamin C. Hitz; Eurie L. Hong

The Gene Ontology (GO) project (http://www.geneontology.org/) provides a set of structured, controlled vocabularies for community use in annotating genes, gene products and sequences (also see http://www.sequenceontology.org/). The ontologies have been extended and refined for several biological areas, and improvements to the structure of the ontologies have been implemented. To improve the quantity and quality of gene product annotations available from its public repository, the GO Consortium has launched a focused effort to provide comprehensive and detailed annotation of orthologous genes across a number of ‘reference’ genomes, including human and several key model organisms. Software developments include two releases of the ontology-editing tool OBO-Edit, and improvements to the AmiGO browser interface.


Nature Biotechnology | 2007

The minimum information required for reporting a molecular interaction experiment (MIMIx)

Sandra Orchard; Lukasz Salwinski; Samuel Kerrien; Luisa Montecchi-Palazzi; Matthias Oesterheld; Volker Stümpflen; Arnaud Ceol; Andrew Chatr-aryamontri; John Armstrong; Peter Woollard; John J. Salama; Susan Moore; Jérôme Wojcik; Gary D. Bader; Marc Vidal; Michael E. Cusick; Mark Gerstein; Anne-Claude Gavin; Giulio Superti-Furga; Jack Greenblatt; Joel S. Bader; Peter Uetz; Mike Tyers; Pierre Legrain; Stan Fields; Nicola Mulder; Michael K. Gilson; Michael Niepmann; Lyle D Burgoon; Javier De Las Rivas

A wealth of molecular interaction data is available in the literature, ranging from large-scale datasets to a single interaction confirmed by several different techniques. These data are all too often reported either as free text or in tables of variable format, and are often missing key pieces of information essential for a full understanding of the experiment. Here we propose MIMIx, the minimum information required for reporting a molecular interaction experiment. Adherence to these reporting guidelines will result in publications of increased clarity and usefulness to the scientific community and will support the rapid, systematic capture of molecular interaction data in public databases, thereby improving access to valuable interaction data.


Nucleic Acids Research | 2001

Proteome Analysis Database: online application of InterPro and CluSTr for the functional classification of proteins in whole genomes

Rolf Apweiler; Margaret Biswas; Wolfgang Fleischmann; Alexander Kanapin; Youla Karavidopoulou; Paul J. Kersey; Evgenia V. Kriventseva; Virginie Mittard; Nicola Mulder; Isabelle Phan; Evgeni M. Zdobnov

The SWISS-PROT group at EBI has developed the Proteome Analysis Database utilising existing resources and providing comparative analysis of the predicted protein coding sequences of the complete genomes of bacteria, archaea and eukaryotes (http://www.ebi.ac. uk/proteome/). The two main projects used, InterPro and CluSTr, give a new perspective on families, domains and sites and cover 31-67% (InterPro statistics) of the proteins from each of the complete genomes. CluSTr covers the three complete eukaryotic genomes and the incomplete human genome data. The Proteome Analysis Database is accompanied by a program that has been designed to carry out InterPro proteome comparisons for any one proteome against any other one or more of the proteomes in the database.


Nucleic Acids Research | 2003

The Proteome Analysis database: a tool for the in silico analysis of whole proteomes.

Manuela Pruess; Wolfgang Fleischmann; Alexander Kanapin; Youla Karavidopoulou; Paul J. Kersey; Evgenia V. Kriventseva; Virginie Mittard; Nicola Mulder; Isabelle Phan; Florence Servant; Rolf Apweiler

The Proteome Analysis database (http://www.ebi.ac.uk/proteome/) has been developed by the Sequence Database Group at EBI utilizing existing resources and providing comparative analysis of the predicted protein coding sequences of the complete genomes of bacteria, archeae and eukaryotes. Three main projects are used, InterPro, CluSTr and GO Slim, to give an overview on families, domains, sites, and functions of the proteins from each of the complete genomes. Complete proteome analysis is available for a total of 89 proteome sets. A specifically designed application enables InterPro proteome comparisons for any one proteome against any other one or more of the proteomes in the database.


Human Molecular Genetics | 2014

Genome-wide association study of ancestry-specific TB risk in the South African Coloured population

Emile R. Chimusa; Noah Zaitlen; Michelle Daya; Marlo Möller; Paul D. van Helden; Nicola Mulder; Alkes L. Price; Eileen G. Hoal

The worldwide burden of tuberculosis (TB) remains an enormous problem, and is particularly severe in the admixed South African Coloured (SAC) population residing in the Western Cape. Despite evidence from twin studies suggesting a strong genetic component to TB resistance, only a few loci have been identified to date. In this work, we conduct a genome-wide association study (GWAS), meta-analysis and trans-ethnic fine mapping to attempt the replication of previously identified TB susceptibility loci. Our GWAS results confirm the WT1 chr11 susceptibility locus (rs2057178: odds ratio = 0.62, P = 2.71e(-06)) previously identified by Thye et al., but fail to replicate previously identified polymorphisms in the TLR8 gene and locus 18q11.2. Our study demonstrates that the genetic contribution to TB risk varies between continental populations, and illustrates the value of including admixed populations in studies of TB risk and other complex phenotypes. Our evaluation of local ancestry based on the real and simulated data demonstrates that case-only admixture mapping is currently impractical in multi-way admixed populations, such as the SAC, due to spurious deviations in average local ancestry generated by current local ancestry inference methods. This study provides insights into identifying disease genes and ancestry-specific disease risk in multi-way admixed populations.


Current protocols in human genetics | 2008

The InterPro database and tools for protein domain analysis.

Nicola Mulder; Rolf Apweiler

InterPro provides a one‐stop shop for protein‐sequence classification, freeing the user from having to visit multiple databases separately and rationalize the different results in varying formats. This unit describes how to submit a sequence to InterProScan via a Web server. It also provides instructions for installing and running InterProScan locally. In addition, details on browsing InterPro families and domains of interest using the InterPro Web and sequence retrieval system (SRS) are provided to show users how to get the most from the resource. Curr. Protoc. Bioinform. 21:2.7.1‐2.7.18.

Collaboration


Dive into the Nicola Mulder's collaboration.

Top Co-Authors

Avatar

Rolf Apweiler

European Bioinformatics Institute

View shared research outputs
Top Co-Authors

Avatar
Top Co-Authors

Avatar

Alexander Kanapin

Wellcome Trust Centre for Human Genetics

View shared research outputs
Top Co-Authors

Avatar
Top Co-Authors

Avatar

Wolfgang Fleischmann

European Bioinformatics Institute

View shared research outputs
Top Co-Authors

Avatar
Top Co-Authors

Avatar

Margaret Biswas

European Bioinformatics Institute

View shared research outputs
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar

Sumir Panji

University of Cape Town

View shared research outputs
Researchain Logo
Decentralizing Knowledge