Literature DB >> 17098324

Perturbations to uncover gene networks.

Jesper Tegnér1, Johan Björkegren.   

Abstract

After the major achievements of the DNA sequencing projects, an equally important challenge now is to uncover the functional relationships among genes (i.e. gene networks). It has become increasingly clear that computational algorithms are crucial for extracting meaningful information from the massive amount of data generated by high-throughput genome-wide technologies. Here, we summarise how systems identification algorithms, originating from physics and control theory, have been adapted for use in biology. We also explain how experimental perturbations combined with genome-wide measurements are being used to uncover gene networks. Perturbation techniques could pave the way for identifying gene networks in more complex settings such as multifactorial diseases and for improving the efficacy of drug evaluation.

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Year:  2006        PMID: 17098324     DOI: 10.1016/j.tig.2006.11.003

Source DB:  PubMed          Journal:  Trends Genet        ISSN: 0168-9525            Impact factor:   11.639


  15 in total

1.  Systems biology of innate immunity.

Authors:  Jesper Tegnér; Roland Nilsson; Vladimir B Bajic; Johan Björkegren; Timothy Ravasi
Journal:  Cell Immunol       Date:  2007-04-11       Impact factor: 4.868

Review 2.  Application of a systems approach to study developmental gene regulation.

Authors:  Joshua W K Ho
Journal:  Biophys Rev       Date:  2012-09-01

Review 3.  Structure and dynamics of molecular networks: a novel paradigm of drug discovery: a comprehensive review.

Authors:  Peter Csermely; Tamás Korcsmáros; Huba J M Kiss; Gábor London; Ruth Nussinov
Journal:  Pharmacol Ther       Date:  2013-02-04       Impact factor: 12.310

4.  Allo-network drugs: harnessing allostery in cellular networks.

Authors:  Ruth Nussinov; Chung-Jung Tsai; Peter Csermely
Journal:  Trends Pharmacol Sci       Date:  2011-09-16       Impact factor: 14.819

5.  Multi-organ expression profiling uncovers a gene module in coronary artery disease involving transendothelial migration of leukocytes and LIM domain binding 2: the Stockholm Atherosclerosis Gene Expression (STAGE) study.

Authors:  Sara Hägg; Josefin Skogsberg; Jesper Lundström; Peri Noori; Roland Nilsson; Hua Zhong; Shohreh Maleki; Ming-Mei Shang; Björn Brinne; Maria Bradshaw; Vladimir B Bajic; Ann Samnegård; Angela Silveira; Lee M Kaplan; Bruna Gigante; Karin Leander; Ulf de Faire; Stefan Rosfors; Ulf Lockowandt; Jan Liska; Peter Konrad; Rabbe Takolander; Anders Franco-Cereceda; Eric E Schadt; Torbjörn Ivert; Anders Hamsten; Jesper Tegnér; Johan Björkegren
Journal:  PLoS Genet       Date:  2009-12-04       Impact factor: 5.917

6.  Lipopolysaccharide-induced early response genes in bovine peripheral blood mononuclear cells implicate GLG1/E-selectin as a key ligand-receptor interaction.

Authors:  Cong-jun Li; Robert W Li; Theodore H Elsasser; Stanislaw Kahl
Journal:  Funct Integr Genomics       Date:  2009-03-05       Impact factor: 3.410

7.  Cognition, quality-of-life, and symptom clusters in breast cancer: Using Bayesian networks to elucidate complex relationships.

Authors:  Selene Xu; Wesley Thompson; Sonia Ancoli-Israel; Lianqi Liu; Barton Palmer; Loki Natarajan
Journal:  Psychooncology       Date:  2017-11-21       Impact factor: 3.894

8.  Inference and validation of predictive gene networks from biomedical literature and gene expression data.

Authors:  Catharina Olsen; Kathleen Fleming; Niall Prendergast; Renee Rubio; Frank Emmert-Streib; Gianluca Bontempi; Benjamin Haibe-Kains; John Quackenbush
Journal:  Genomics       Date:  2014-03-29       Impact factor: 5.736

9.  Evidence of highly regulated genes (in-Hubs) in gene networks of Saccharomyces cerevisiae.

Authors:  Jesper Lundström; Johan Björkegren; Jesper Tegnér
Journal:  Bioinform Biol Insights       Date:  2008-07-14

Review 10.  Can modular analysis identify disease-associated candidate genes for therapeutics?

Authors:  Jesper Tegnér
Journal:  J Biol       Date:  2009-05-28
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