Literature DB >> 20127971

The Roche Cancer Genome Database (RCGDB).

Jan Küntzer1, Daniela Eggle, Hans-Peter Lenhof, Helmut Burtscher, Stefan Klostermann.   

Abstract

Sequence variations are being studied for a better understanding of the mechanism and development of cancer as a mutation-driven disease. The systematic sequencing of genes in tumors and technological advances in high-throughput techniques combined with efficient data acquisition methods have resulted in an explosion of available cancer genome-related data. Despite the technological progress and increase of data, improvements in the application area, for example, drug target discovery, have failed to keep pace with increased research and development spending. One reason for this discrepancy is the ever increasing number of databases and the absence of a unified access to the mutation data. Currently, researchers typically have to browse several, often highly specialized databases to obtain the required information. A more complete understanding of relations and dependencies between mutations and cancer, however, requires the availability of an efficient integrative cancer genome information system. To facilitate this, we developed the Roche Cancer Genome Database (RCGDB), a freely available biological information system integrating different kinds of mutation data. The database is the first comprehensive integration of disparate cancer genome data like single nucleotide variants, single nucleotide polymorphisms, and chromosomal aberrations (CGH and FISH). RCGDB is freely accessible via a Google-like Web interface at http://rcgdb.bioinf.uni-sb.de/MutomeWeb/. (c) 2010 Wiley-Liss, Inc.

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Year:  2010        PMID: 20127971     DOI: 10.1002/humu.21207

Source DB:  PubMed          Journal:  Hum Mutat        ISSN: 1059-7794            Impact factor:   4.878


  7 in total

1.  Immunogenicity of autoantigens.

Authors:  Christina Backes; Nicole Ludwig; Petra Leidinger; Christian Harz; Jana Hoffmann; Andreas Keller; Eckart Meese; Hans-Peter Lenhof
Journal:  BMC Genomics       Date:  2011-07-04       Impact factor: 3.969

Review 2.  Pathological unfoldomics of uncontrolled chaos: intrinsically disordered proteins and human diseases.

Authors:  Vladimir N Uversky; Vrushank Davé; Lilia M Iakoucheva; Prerna Malaney; Steven J Metallo; Ravi Ramesh Pathak; Andreas C Joerger
Journal:  Chem Rev       Date:  2014-05-15       Impact factor: 60.622

Review 3.  Human variation databases.

Authors:  Jan Küntzer; Daniela Eggle; Stefan Klostermann; Helmut Burtscher
Journal:  Database (Oxford)       Date:  2010-07-17       Impact factor: 3.451

4.  The Roche Cancer Genome Database 2.0.

Authors:  Jan Küntzer; Daniela Maisel; Hans-Peter Lenhof; Stefan Klostermann; Helmut Burtscher
Journal:  BMC Med Genomics       Date:  2011-05-17       Impact factor: 3.063

5.  An integer linear programming approach for finding deregulated subgraphs in regulatory networks.

Authors:  Christina Backes; Alexander Rurainski; Gunnar W Klau; Oliver Müller; Daniel Stöckel; Andreas Gerasch; Jan Küntzer; Daniela Maisel; Nicole Ludwig; Matthias Hein; Andreas Keller; Helmut Burtscher; Michael Kaufmann; Eckart Meese; Hans-Peter Lenhof
Journal:  Nucleic Acids Res       Date:  2011-12-30       Impact factor: 16.971

6.  Intrinsic disorder in PTEN and its interactome confers structural plasticity and functional versatility.

Authors:  Prerna Malaney; Ravi Ramesh Pathak; Bin Xue; Vladimir N Uversky; Vrushank Davé
Journal:  Sci Rep       Date:  2013       Impact factor: 4.379

7.  Colon cancer cells adopt an invasive phenotype without mesenchymal transition in 3-D but not 2-D culture upon combined stimulation with EGF and crypt growth factors.

Authors:  Kirsten Ludwig; Edison S Tse; Jean Yj Wang
Journal:  BMC Cancer       Date:  2013-05-02       Impact factor: 4.430

  7 in total

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