Knock-Down of 8 RAS-Pathway Genes in Colon Cancer

Inference and validation of predictive gene networks from literature and gene expression data

Description: Although many methods have been developed for inference of biological networks, the validation of the resulting models has largely remained an unsolved problem. Here we present a framework for quantitative assessment of inferred gene interaction networks using knock-down data from cell line experiments. Using this framework we are able to show that network inference based on integration of prior knowledge derived from the biomedical literature with genomic data significantly improves the quality of inferred networks relative to other approaches. Our results also suggest that cell line experiments can be used to quantitatively assess the quality of networks inferred from tumor samples.
Authors: Olsen C, Fleming K, Prendergast N, Rubio R, Emmert-Streib F, Bontempi G, Haibe-Kains B, Quackenbush J
Lab: Haibe-Kains
Year: 2013
Keywords:

Citation

Olsen C, Bontempi G, Emmert-Streib F, Quackenbush J et al. Relevance of different prior knowledge sources for inferring gene interaction networks. Front Genet 2014;5:177. PMID:

125 samples

Sample Type:N/A
Species:Human
Datatype:N/A
Technology:Array

Contact

This dataset is public.

Contact: Benjamin Haibe-Kains

Contact email: Email