Network


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

Hotspot


Dive into the research topics where Imre Vastrik is active.

Publication


Featured researches published by Imre Vastrik.


Nature | 2007

Patterns of somatic mutation in human cancer genomes

Christopher Greenman; Philip Stephens; Raffaella Smith; Gillian L. Dalgliesh; Chris Hunter; Graham R. Bignell; Helen Davies; Jon Teague; Adam Butler; Claire Stevens; Sarah Edkins; Sarah O’Meara; Imre Vastrik; Esther Schmidt; Tim Avis; Syd Barthorpe; Gurpreet Bhamra; Gemma Buck; Bhudipa Choudhury; Jody Clements; Jennifer Cole; Ed Dicks; Simon A. Forbes; Kris Gray; Kelly Halliday; Rachel Harrison; Katy Hills; Jon Hinton; Andy Jenkinson; David Jones

Cancers arise owing to mutations in a subset of genes that confer growth advantage. The availability of the human genome sequence led us to propose that systematic resequencing of cancer genomes for mutations would lead to the discovery of many additional cancer genes. Here we report more than 1,000 somatic mutations found in 274 megabases (Mb) of DNA corresponding to the coding exons of 518 protein kinase genes in 210 diverse human cancers. There was substantial variation in the number and pattern of mutations in individual cancers reflecting different exposures, DNA repair defects and cellular origins. Most somatic mutations are likely to be ‘passengers’ that do not contribute to oncogenesis. However, there was evidence for ‘driver’ mutations contributing to the development of the cancers studied in approximately 120 genes. Systematic sequencing of cancer genomes therefore reveals the evolutionary diversity of cancers and implicates a larger repertoire of cancer genes than previously anticipated.


Nucleic Acids Research | 2002

The Ensembl genome database project

Tim Hubbard; Darren Barker; Ewan Birney; Graham Cameron; Yuan Chen; L. Clark; Tony Cox; James Cuff; V. Curwen; Thomas A. Down; Richard Durbin; E. Eyras; James Gilbert; Martin Hammond; L. Huminiecki; Arek Kasprzyk; Heikki Lehväslaiho; Philip Lijnzaad; Craig Melsopp; Emmanuel Mongin; R. Pettett; M. Pocock; Simon Potter; A. Rust; Esther Schmidt; Stephen M. J. Searle; Guy Slater; J. Smith; W. Spooner; A. Stabenau

The Ensembl (http://www.ensembl.org/) database project provides a bioinformatics framework to organise biology around the sequences of large genomes. It is a comprehensive source of stable automatic annotation of the human genome sequence, with confirmed gene predictions that have been integrated with external data sources, and is available as either an interactive web site or as flat files. It is also an open source software engineering project to develop a portable system able to handle very large genomes and associated requirements from sequence analysis to data storage and visualisation. The Ensembl site is one of the leading sources of human genome sequence annotation and provided much of the analysis for publication by the international human genome project of the draft genome. The Ensembl system is being installed around the world in both companies and academic sites on machines ranging from supercomputers to laptops.


Nucleic Acids Research | 2004

Reactome: a knowledgebase of biological pathways

G. Joshi-Tope; Marc Gillespie; Imre Vastrik; Peter D'Eustachio; Esther Schmidt; B. de Bono; Bijay Jassal; G.R. Gopinath; G.R. Wu; Lisa Matthews; Suzanna E. Lewis; Ewan Birney; Lincoln Stein

Reactome, located at http://www.reactome.org is a curated, peer-reviewed resource of human biological processes. Given the genetic makeup of an organism, the complete set of possible reactions constitutes its reactome. The basic unit of the Reactome database is a reaction; reactions are then grouped into causal chains to form pathways. The Reactome data model allows us to represent many diverse processes in the human system, including the pathways of intermediary metabolism, regulatory pathways, and signal transduction, and high-level processes, such as the cell cycle. Reactome provides a qualitative framework, on which quantitative data can be superimposed. Tools have been developed to facilitate custom data entry and annotation by expert biologists, and to allow visualization and exploration of the finished dataset as an interactive process map. Although our primary curational domain is pathways from Homo sapiens, we regularly create electronic projections of human pathways onto other organisms via putative orthologs, thus making Reactome relevant to model organism research communities. The database is publicly available under open source terms, which allows both its content and its software infrastructure to be freely used and redistributed.


Nucleic Acids Research | 2009

Reactome knowledgebase of human biological pathways and processes.

Lisa Matthews; Gopal Gopinath; Marc Gillespie; Michael Caudy; David Croft; Bernard de Bono; Phani Garapati; Jill Hemish; Henning Hermjakob; Bijay Jassal; Alex Kanapin; Suzanna E. Lewis; Shahana Mahajan; Bruce May; Esther Schmidt; Imre Vastrik; Guanming Wu; Ewan Birney; Lincoln Stein; Peter D’Eustachio

Reactome (http://www.reactome.org) is an expert-authored, peer-reviewed knowledgebase of human reactions and pathways that functions as a data mining resource and electronic textbook. Its current release includes 2975 human proteins, 2907 reactions and 4455 literature citations. A new entity-level pathway viewer and improved search and data mining tools facilitate searching and visualizing pathway data and the analysis of user-supplied high-throughput data sets. Reactome has increased its utility to the model organism communities with improved orthology prediction methods allowing pathway inference for 22 species and through collaborations to create manually curated Reactome pathway datasets for species including Arabidopsis, Oryza sativa (rice), Drosophila and Gallus gallus (chicken). Reactomes data content and software can all be freely used and redistributed under open source terms.


Nature Biotechnology | 2010

The BioPAX community standard for pathway data sharing

Emek Demir; Michael P. Cary; Suzanne M. Paley; Ken Fukuda; Christian Lemer; Imre Vastrik; Guanming Wu; Peter D'Eustachio; Carl F. Schaefer; Joanne S. Luciano; Frank Schacherer; Irma Martínez-Flores; Zhenjun Hu; Verónica Jiménez-Jacinto; Geeta Joshi-Tope; Kumaran Kandasamy; Alejandra López-Fuentes; Huaiyu Mi; Elgar Pichler; Igor Rodchenkov; Andrea Splendiani; Sasha Tkachev; Jeremy Zucker; Gopal Gopinath; Harsha Rajasimha; Ranjani Ramakrishnan; Imran Shah; Mustafa Syed; Nadia Anwar; Özgün Babur

Biological Pathway Exchange (BioPAX) is a standard language to represent biological pathways at the molecular and cellular level and to facilitate the exchange of pathway data. The rapid growth of the volume of pathway data has spurred the development of databases and computational tools to aid interpretation; however, use of these data is hampered by the current fragmentation of pathway information across many databases with incompatible formats. BioPAX, which was created through a community process, solves this problem by making pathway data substantially easier to collect, index, interpret and share. BioPAX can represent metabolic and signaling pathways, molecular and genetic interactions and gene regulation networks. Using BioPAX, millions of interactions, organized into thousands of pathways, from many organisms are available from a growing number of databases. This large amount of pathway data in a computable form will support visualization, analysis and biological discovery.


Nucleic Acids Research | 2003

Ensembl 2002: accommodating comparative genomics

Michele Clamp; D. Andrews; Darren Barker; Paul Bevan; Graham Cameron; Yuting Chen; Louise Clark; Tony Cox; James Cuff; Val Curwen; Thomas A. Down; Richard Durbin; Eduardo Eyras; James Gilbert; Martin Hammond; Tim Hubbard; Arek Kasprzyk; Damian Keefe; Heikki Lehväslaiho; Vishwanath R. Iyer; Craig Melsopp; Emmanuel Mongin; Roger Pettett; Simon Potter; Alistair G. Rust; Esther Schmidt; Steve Searle; Guy Slater; James Smith; William Spooner

The Ensembl (http://www.ensembl.org/) database project provides a bioinformatics framework to organise biology around the sequences of large genomes. It is a comprehensive source of stable automatic annotation of human, mouse and other genome sequences, available as either an interactive web site or as flat files. Ensembl also integrates manually annotated gene structures from external sources where available. As well as being one of the leading sources of genome annotation, Ensembl is an open source software engineering project to develop a portable system able to handle very large genomes and associated requirements. These range from sequence analysis to data storage and visualisation and installations exist around the world in both companies and at academic sites. With both human and mouse genome sequences available and more vertebrate sequences to follow, many of the recent developments in Ensembl have focusing on developing automatic comparative genome analysis and visualisation.


The Plant Cell | 2008

Arabidopsis Reactome: A Foundation Knowledgebase for Plant Systems Biology

Nicolas Tsesmetzis; Matthew Couchman; Janet Higgins; Alison M. Smith; John H. Doonan; Georg Seifert; Esther Schmidt; Imre Vastrik; Ewan Birney; Guanming Wu; Peter D'Eustachio; Lincoln Stein; Richard J. Morris; Michael W. Bevan; Sean Walsh

New ways of capturing and representing biological knowledge are needed to enable individual researchers to remain abreast of relevant discoveries and to permit computational approaches for interpreting the large volumes of diverse data generated by modern biological research. Here, we describe a


Genome Biology | 2009

Correction: Reactome: a knowledge base of biologic pathways and processes

Imre Vastrik; Peter D'Eustachio; Esther Schmidt; Gopal Gopinath; David Croft; Bernard de Bono; Marc Gillespie; Bijay Jassal; Suzanna E. Lewis; Lisa Matthews; Guanming Wu; Ewan Birney; Lincoln Stein

Reactome http://www.reactome.org, an online curated resource for human pathway data, provides infrastructure for computation across the biologic reaction network. We use Reactome to infer equivalent reactions in multiple nonhuman species, and present data on the reliability of these inferred reactions for the distantly related eukaryote Saccharomyces cerevisiae. Finally, we describe the use of Reactome both as a learning resource and as a computational tool to aid in the interpretation of microarrays and similar large-scale datasets.


Nature Biotechnology | 2012

The BioPAX community standard for pathway data sharing (Nature Biotechnology (2010) 28, (935-942))

Emek Demir; Michael P. Cary; Suzanne M. Paley; Ken Fukuda; Christian Lemer; Imre Vastrik; Guanming Wu; Peter D'Eustachio; Carl F. Schaefer; Joanne S. Luciano; Frank Schacherer; Irma Martínez-Flores; Zhenjun Hu; Verónica Jiménez-Jacinto; Geeta Joshi-Tope; Kumaran Kandasamy; Alejandra López-Fuentes; Huaiyu Mi; Elgar Pichler; Igor Rodchenkov; Andrea Splendiani; Sasha Tkachev; Jeremy Zucker; Gopal Gopinath; Harsha Rajasimha; Ranjani Ramakrishnan; Imran Shah; Mustafa Syed; Nadia Anwar; Özgün Babur

BioPAX (Biological Pathway Exchange) is a standard language to represent biological pathways at the molecular and cellular level. Its major use is to facilitate the exchange of pathway data (http://www.biopax.org). Pathway data captures our understanding of biological processes, but its rapid growth necessitates development of databases and computational tools to aid interpretation. However, the current fragmentation of pathway information across many databases with incompatible formats presents barriers to its effective use. BioPAX solves this problem by making pathway data substantially easier to collect, index, interpret and share. BioPAX can represent metabolic and signaling pathways, molecular and genetic interactions and gene regulation networks. BioPAX was created through a community process. Through BioPAX, millions of interactions organized into thousands of pathways across many organisms, from a growing number of sources, are available. Thus, large amounts of pathway data are available in a computable form to support visualization, analysis and biological discovery.


Current protocols in human genetics | 2008

Installing a local copy of the Reactome Web site and database.

Imre Vastrik

The Reactome project builds, maintains, and publishes a database of biological pathways. The information in the database is gathered from the experts in the field, peer reviewed, and edited by Reactome editorial staff and then published to the Reactome Web site, http://www.reactome.org (see UNIT ). Reactome software is open source and builds on top of other open‐source or freely available software. Reactome data and code can be freely downloaded in its entirety and the Web site installed locally. This allows for more flexible interrogation of the data and also makes it possible to add ones own information to the database. Curr. Protoc. Bioinform. 21:9.10.1‐9.10.9.

Collaboration


Dive into the Imre Vastrik's collaboration.

Top Co-Authors

Avatar
Top Co-Authors

Avatar

Guanming Wu

Ontario Institute for Cancer Research

View shared research outputs
Top Co-Authors

Avatar

Esther Schmidt

European Bioinformatics Institute

View shared research outputs
Top Co-Authors

Avatar

Gopal Gopinath

Center for Food Safety and Applied Nutrition

View shared research outputs
Top Co-Authors

Avatar

Ewan Birney

European Bioinformatics Institute

View shared research outputs
Top Co-Authors

Avatar

Lincoln Stein

Ontario Institute for Cancer Research

View shared research outputs
Top Co-Authors

Avatar

Bijay Jassal

European Bioinformatics Institute

View shared research outputs
Top Co-Authors

Avatar
Top Co-Authors

Avatar

Suzanna E. Lewis

Lawrence Berkeley National Laboratory

View shared research outputs
Top Co-Authors

Avatar
Researchain Logo
Decentralizing Knowledge