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...

Descripción completa

Detalles Bibliográficos
Autores principales: Wang, Yi Kan, Hurley, Daniel G., Schnell, Santiago, Print, Cristin G., Crampin, Edmund J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2013
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3743784/
https://www.ncbi.nlm.nih.gov/pubmed/23967277
http://dx.doi.org/10.1371/journal.pone.0072103

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3743784/
https://www.ncbi.nlm.nih.gov/pubmed/23967277
http://dx.doi.org/10.1371/journal.pone.0072103

Ejemplares similares