Literature DB >> 16524837

Modelling in molecular biology: describing transcription regulatory networks at different scales.

Thomas Schlitt1, Alvis Brazma.   

Abstract

Approaches to describe gene regulation networks can be categorized by increasing detail, as network parts lists, network topology models, network control logic models or dynamic models. We discuss the current state of the art for each of these approaches. We study the relationship between different topology models, and give examples how they can be used to infer functional annotations for genes of unknown function. We introduce a new simple way of describing dynamic models called finite state linear model (FSLM). We discuss the gap between the parts list and topology models on one hand, and network logic and dynamic models, on the other hand. The first two classes of models have reached a genome-wide scale, while for the other model classes high-throughput technologies are yet to make a major impact.

Mesh:

Year:  2006        PMID: 16524837      PMCID: PMC1609346          DOI: 10.1098/rstb.2005.1806

Source DB:  PubMed          Journal:  Philos Trans R Soc Lond B Biol Sci        ISSN: 0962-8436            Impact factor:   6.237


  51 in total

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Authors:  T Akutsu; S Miyano; S Kuhara
Journal:  Pac Symp Biocomput       Date:  1999

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Authors:  T Chen; H L He; G M Church
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Journal:  Metab Eng       Date:  1999-01       Impact factor: 9.783

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Journal:  J Comput Biol       Date:  2001       Impact factor: 1.479

Review 5.  Gene networks: how to put the function in genomics.

Authors:  Paul Brazhnik; Alberto de la Fuente; Pedro Mendes
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6.  Network motifs: simple building blocks of complex networks.

Authors:  R Milo; S Shen-Orr; S Itzkovitz; N Kashtan; D Chklovskii; U Alon
Journal:  Science       Date:  2002-10-25       Impact factor: 47.728

7.  Genomic cis-regulatory logic: experimental and computational analysis of a sea urchin gene.

Authors:  C H Yuh; H Bolouri; E H Davidson
Journal:  Science       Date:  1998-03-20       Impact factor: 47.728

8.  A probabilistic functional network of yeast genes.

Authors:  Insuk Lee; Shailesh V Date; Alex T Adai; Edward M Marcotte
Journal:  Science       Date:  2004-11-26       Impact factor: 47.728

Review 9.  Life with 6000 genes.

Authors:  A Goffeau; B G Barrell; H Bussey; R W Davis; B Dujon; H Feldmann; F Galibert; J D Hoheisel; C Jacq; M Johnston; E J Louis; H W Mewes; Y Murakami; P Philippsen; H Tettelin; S G Oliver
Journal:  Science       Date:  1996-10-25       Impact factor: 47.728

10.  Comprehensive identification of cell cycle-regulated genes of the yeast Saccharomyces cerevisiae by microarray hybridization.

Authors:  P T Spellman; G Sherlock; M Q Zhang; V R Iyer; K Anders; M B Eisen; P O Brown; D Botstein; B Futcher
Journal:  Mol Biol Cell       Date:  1998-12       Impact factor: 4.138

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  7 in total

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2.  Introduction. Bioinformatics: from molecules to systems.

Authors:  David T Jones; Michael J E Sternberg; Janet M Thornton
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2006-03-29       Impact factor: 6.237

3.  Discrete dynamical system modelling for gene regulatory networks of 5-hydroxymethylfurfural tolerance for ethanologenic yeast.

Authors:  M Song; Z Ouyang; Z L Liu
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5.  Elucidation of functional consequences of signalling pathway interactions.

Authors:  Adaoha E C Ihekwaba; Phuong T Nguyen; Corrado Priami
Journal:  BMC Bioinformatics       Date:  2009-11-06       Impact factor: 3.169

6.  Comparison of transcription regulatory interactions inferred from high-throughput methods: what do they reveal?

Authors:  S Balaji; Lakshminarayan M Iyer; M Madan Babu; L Aravind
Journal:  Trends Genet       Date:  2008-07       Impact factor: 11.639

7.  Current approaches to gene regulatory network modelling.

Authors:  Thomas Schlitt; Alvis Brazma
Journal:  BMC Bioinformatics       Date:  2007-09-27       Impact factor: 3.169

  7 in total

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