Literature DB >> 11076023

Representing and analysing molecular and cellular function using the computer.

J van Helden1, A Naim, R Mancuso, M Eldridge, L Wernisch, D Gilbert, S J Wodak.   

Abstract

Determining the biological function of a myriad of genes, and understanding how they interact to yield a living cell, is the major challenge of the post genome-sequencing era. The complexity of biological systems is such that this cannot be envisaged without the help of powerful computer systems capable of representing and analysing the intricate networks of physical and functional interactions between the different cellular components. In this review we try to provide the reader with an appreciation of where we stand in this regard. We discuss some of the inherent problems in describing the different facets of biological function, give an overview of how information on function is currently represented in the major biological databases, and describe different systems for organising and categorising the functions of gene products. In a second part, we present a new general data model, currently under development, which describes information on molecular function and cellular processes in a rigorous manner. The model is capable of representing a large variety of biochemical processes, including metabolic pathways, regulation of gene expression and signal transduction. It also incorporates taxonomies for categorising molecular entities, interactions and processes, and it offers means of viewing the information at different levels of resolution, and dealing with incomplete knowledge. The data model has been implemented in the database on protein function and cellular processes 'aMAZE' (http://www.ebi.ac.uk/research/pfbp/), which presently covers metabolic pathways and their regulation. Several tools for querying, displaying, and performing analyses on such pathways are briefly described in order to illustrate the practical applications enabled by the model.

Mesh:

Year:  2000        PMID: 11076023     DOI: 10.1515/BC.2000.113

Source DB:  PubMed          Journal:  Biol Chem        ISSN: 1431-6730            Impact factor:   3.915


  12 in total

Review 1.  Metabolic pathway analysis in trypanosomes and malaria parasites.

Authors:  Alan H Fairlamb
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2002-01-29       Impact factor: 6.237

Review 2.  Network genomics--a novel approach for the analysis of biological systems in the post-genomic era.

Authors:  Christian V Forst
Journal:  Mol Biol Rep       Date:  2002-09       Impact factor: 2.316

3.  Dynamic generation and qualitative analysis of metabolic pathways by a joint database/graph theoretical approach.

Authors:  F Ehrentreich; D Schomburg
Journal:  Funct Integr Genomics       Date:  2003-10-16       Impact factor: 3.410

4.  The aMAZE LightBench: a web interface to a relational database of cellular processes.

Authors:  Christian Lemer; Erick Antezana; Fabian Couche; Frédéric Fays; Xavier Santolaria; Rekin's Janky; Yves Deville; Jean Richelle; Shoshana J Wodak
Journal:  Nucleic Acids Res       Date:  2004-01-01       Impact factor: 16.971

5.  KDBI: Kinetic Data of Bio-molecular Interactions database.

Authors:  Z L Ji; X Chen; C J Zhen; L X Yao; L Y Han; W K Yeo; P C Chung; H S Puy; Y T Tay; A Muhammad; Y Z Chen
Journal:  Nucleic Acids Res       Date:  2003-01-01       Impact factor: 16.971

6.  Pathway discovery in metabolic networks by subgraph extraction.

Authors:  Karoline Faust; Pierre Dupont; Jérôme Callut; Jacques van Helden
Journal:  Bioinformatics       Date:  2010-03-12       Impact factor: 6.937

7.  Computing biological functions using BioPsi, a formal description of biological processes based on elementary bricks of actions.

Authors:  Sabine Pérès; Liza Felicori; Stéphanie Rialle; Elodie Jobard; Franck Molina
Journal:  Bioinformatics       Date:  2010-05-06       Impact factor: 6.937

Review 8.  Cataloging the relationships between proteins: a review of interaction databases.

Authors:  Carol Rohl; Yancey Price; Tiffany B Fischer; Melissa Paczkowski; Michael F Zettel; Jerry Tsai
Journal:  Mol Biotechnol       Date:  2006-09       Impact factor: 2.860

9.  SPIKE--a database, visualization and analysis tool of cellular signaling pathways.

Authors:  Ran Elkon; Rita Vesterman; Nira Amit; Igor Ulitsky; Idan Zohar; Mali Weisz; Gilad Mass; Nir Orlev; Giora Sternberg; Ran Blekhman; Jackie Assa; Yosef Shiloh; Ron Shamir
Journal:  BMC Bioinformatics       Date:  2008-02-20       Impact factor: 3.169

10.  A distance difference matrix approach to identifying transcription factors that regulate differential gene expression.

Authors:  Pieter De Bleser; Bart Hooghe; Dominique Vlieghe; Frans van Roy
Journal:  Genome Biol       Date:  2007       Impact factor: 13.583

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