Literature DB >> 21183477

Validation of gene regulatory networks: scientific and inferential.

Edward R Dougherty1.   

Abstract

Gene regulatory network models are a major area of study in systems and computational biology and the construction of network models is among the most important problems in these disciplines. The critical epistemological issue concerns validation. Validity can be approached from two different perspectives (i) given a hypothesized network model, its scientific validity relates to the ability to make predictions from the model that can be checked against experimental observations; and (ii) the validity of a network inference procedure must be evaluated relative to its ability to infer a network from sample points generated by the network. This article examines both perspectives in the framework of a distance function between two networks. It considers some of the obstacles to validation and provides examples of both validation paradigms.

Mesh:

Year:  2010        PMID: 21183477     DOI: 10.1093/bib/bbq078

Source DB:  PubMed          Journal:  Brief Bioinform        ISSN: 1467-5463            Impact factor:   11.622


  12 in total

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Journal:  Bioinformatics       Date:  2012-03-14       Impact factor: 6.937

5.  Learning restricted Boolean network model by time-series data.

Authors:  Hongjia Ouyang; Jie Fang; Liangzhong Shen; Edward R Dougherty; Wenbin Liu
Journal:  EURASIP J Bioinform Syst Biol       Date:  2014-07-15

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Authors:  Edward R Dougherty; Ilya Shmulevich
Journal:  Curr Genomics       Date:  2012-11       Impact factor: 2.236

7.  Validation of gene regulatory network inference based on controllability.

Authors:  Xiaoning Qian; Edward R Dougherty
Journal:  Front Genet       Date:  2013-12-12       Impact factor: 4.599

8.  Stability indicators in network reconstruction.

Authors:  Michele Filosi; Roberto Visintainer; Samantha Riccadonna; Giuseppe Jurman; Cesare Furlanello
Journal:  PLoS One       Date:  2014-02-27       Impact factor: 3.240

9.  DTW-MIC Coexpression Networks from Time-Course Data.

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Journal:  PLoS One       Date:  2016-03-31       Impact factor: 3.240

10.  Metric projection for dynamic multiplex networks.

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Journal:  Heliyon       Date:  2016-08-04
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