Regulatory network inferred using expression data of small sample size: application and validation in erythroid system | Zendy

Fan Zhu | Zendy; Lihong Shi | Zendy; James Douglas Engel | Zendy; Yuanfang Guan | Zendy

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Regulatory network inferred using expression data of small sample size: application and validation in erythroid system

Author(s) -

Fan Zhu,

Lihong Shi,

James Douglas Engel,

Yuanfang Guan

Publication year - 2015

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btv186

Subject(s) - sample size determination , expression (computer science) , computer science , sample (material) , computational biology , data mining , statistics , biology , mathematics , chromatography , chemistry , programming language

Modeling regulatory networks using expression data observed in a differentiation process may help identify context-specific interactions. The outcome of the current algorithms highly depends on the quality and quantity of a single time-course dataset, and the performance may be compromised for datasets with a limited number of samples.

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