Literature DB >> 21281658

Probabilistic functional gene societies.

Insuk Lee1.   

Abstract

A cellular system may be viewed as a social network of genes. Genes work together to conduct physiological processes in the cells. Thus if we have a view of the functional association among genes, we may also be able to unravel the association between genotypes and phenotypes; the emergent properties of interactive activities of genes. We could have various points of view for a gene network. Perhaps the most common standpoints are protein-protein interaction networks (PPIN) and transcriptional regulatory networks (TRN). Here I introduce another type of view for the gene network; the probabilistic functional gene network (PFGN). A 'functional view' of association between genes enables us to have a holistic model of the gene society. A 'probabilistic view' makes the model of gene associations derived from noisy high-throughput data more robust. In addition, the dynamics of gene association may be presented in a single static network model by the probabilistic view. By combining the two modeling views, the probabilistic functional gene networks have been constructed for various organisms and proved to be highly useful in generating novel biological hypotheses not only for simple unicellular microbes, but also for highly complex multicellular animals and plants.
Copyright © 2011 Elsevier Ltd. All rights reserved.

Mesh:

Year:  2011        PMID: 21281658     DOI: 10.1016/j.pbiomolbio.2011.01.003

Source DB:  PubMed          Journal:  Prog Biophys Mol Biol        ISSN: 0079-6107            Impact factor:   3.667


  7 in total

1.  Genetic dissection of the biotic stress response using a genome-scale gene network for rice.

Authors:  Insuk Lee; Young-Su Seo; Dusica Coltrane; Sohyun Hwang; Taeyun Oh; Edward M Marcotte; Pamela C Ronald
Journal:  Proc Natl Acad Sci U S A       Date:  2011-10-31       Impact factor: 11.205

2.  Systems biology and cancer.

Authors:  Ana M Soto; Carlos Sonnenschein; Philip K Maini; Denis Noble
Journal:  Prog Biophys Mol Biol       Date:  2011-08       Impact factor: 3.667

Review 3.  Applications of comparative evolution to human disease genetics.

Authors:  Claire D McWhite; Benjamin J Liebeskind; Edward M Marcotte
Journal:  Curr Opin Genet Dev       Date:  2015-09-04       Impact factor: 5.578

4.  System-level insights into the cellular interactome of a non-model organism: inferring, modelling and analysing functional gene network of soybean (Glycine max).

Authors:  Yungang Xu; Maozu Guo; Quan Zou; Xiaoyan Liu; Chunyu Wang; Yang Liu
Journal:  PLoS One       Date:  2014-11-25       Impact factor: 3.240

5.  Identification and Analysis of Rice Yield-Related Candidate Genes by Walking on the Functional Network.

Authors:  Jing Jiang; Fei Xing; Chunyu Wang; Xiangxiang Zeng
Journal:  Front Plant Sci       Date:  2018-11-20       Impact factor: 5.753

6.  JiffyNet: a web-based instant protein network modeler for newly sequenced species.

Authors:  Eiru Kim; Hanhae Kim; Insuk Lee
Journal:  Nucleic Acids Res       Date:  2013-05-17       Impact factor: 16.971

7.  Global study of holistic morphological effectors in the budding yeast Saccharomyces cerevisiae.

Authors:  Godai Suzuki; Yang Wang; Karen Kubo; Eri Hirata; Shinsuke Ohnuki; Yoshikazu Ohya
Journal:  BMC Genomics       Date:  2018-02-20       Impact factor: 3.969

  7 in total

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