Adaptive modelling of gene regulatory network using Bayesian information criterion‐guided sparse regression approach-Reference-Cited by-同舟云学术

Adaptive modelling of gene regulatory network using Bayesian information criterion‐guided sparse regression approach

Published:2016-12 Issue:6 Volume:10 Page:252-259
ISSN:1751-8849
Container-title:IET Systems Biology
language:en
Short-container-title:IET syst. biol.

Author:

Shi Ming¹²,Shen Weiming²,Wang Hong‐Qiang¹,Chong Yanwen²

Affiliation:

1. Machine Intelligence and Computational Biology LabInstitute of Intelligent Machines, Chinese Academy of ScienceP.O. Box 1130Hefei230031People's Republic of China

2. State Key Laboratory for Information Engineering in Surveying, Mapping and Remote SensingWuhan University129 Luoyu RoadWuhan430079People's Republic of China

Funder

National Natural Science Foundation of China

Publisher

Institution of Engineering and Technology (IET)

Subject

Cell Biology,Genetics,Molecular Biology,Modelling and Simulation,Biotechnology

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/iet-syb.2016.0005

Reference50 articles.

1. How to infer gene networks from expression profiles;Bansal M.;Mol. Syst. Biol.,2007

2. Gene regulatory networks

3. Inference of gene regulatory networks with sparse structural equation models exploiting genetic perturbations;Cai X.D.;PLoS Comput. Biol.,2013