Integration of Steady-State and Temporal Gene Expression Data for the Inference of Gene Regulatory Networks

Integration of Steady-State and Temporal Gene Expression Data for the Inference of Gene Regulatory Networks

We develop a new regression algorithm, cMIKANA, for inference of gene regulatory networks from combinations of steady-state and time-series gene expression data. Using simulated gene expression datasets to assess the accuracy of reconstructing gene regulatory networks, we show that steady-state and...

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Bibliographic Details
Main Authors: Wang, Yi Kan, Hurley, Daniel G., Schnell, Santiago, Print, Cristin G., Crampin, Edmund J.
Format: Online
Language:English
Published: Public Library of Science 2013
Online Access:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3743784/

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3743784/

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