Bottom-up GGM algorithm for constructing multilayered hierarchical gene regulatory networks that govern biological pathways or processes-Reference-Cited by-同舟云学术

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Bottom-up GGM algorithm for constructing multilayered hierarchical gene regulatory networks that govern biological pathways or processes

Published:2016-03-18 Issue:1 Volume:17 Page:
ISSN:1471-2105
Container-title:BMC Bioinformatics
language:en
Short-container-title:BMC Bioinformatics

Author:

Kumari Sapna,Deng Wenping,Gunasekara Chathura,Chiang Vincent,Chen Huann-sheng,Ma Hao,Davis Xin,Wei Hairong

Funder

National Science Foundation Advances in Biological Informatics

Publisher

Springer Science and Business Media LLC

Subject

Applied Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Structural Biology

Link

http://link.springer.com/content/pdf/10.1186/s12859-016-0981-1

Reference70 articles.

1. Jin Y, Guo H, Meng Y. A hierarchical gene regulatory network for adaptive multirobot pattern formation. IEEE Trans Syst Man Cybern B Cybern. 2012;42(3):805–16.

2. Wei H et al. Genetic networks involved in poplar root response to low nitrogen. Plant Signal Behav. 2013;8(11):e27211.

3. Wei H et al. Nitrogen deprivation promotes Populus root growth through global transcriptome reprogramming and activation of hierarchical genetic networks. New Phytol. 2013;200(2):483–97.

4. Lin YC et al. SND1 transcription factor-directed quantitative functional hierarchical genetic regulatory network in wood formation in Populus trichocarpa. Plant Cell. 2013;25(11):4324–41.

5. Lu S et al. Ptr-miR397a is a negative regulator of laccase genes affecting lignin content in Populus trichocarpa. Proc Natl Acad Sci U S A. 2013;110(26):10848–53.

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