Knowledge-Guided Gene Prioritization

Knowledge-Guided Gene Prioritization

How could genomic analyses help solve the issue of chemotherapy drug resistance in cancer therapy? Existing methods can rank genes by their predicted role in drug resistance from gene expression of untreated cancer cell lines.

A new computational method “ProGENI” published in Genome Biology pushes this one step further by incorporating prior knowledge on the biochemistry of the relationships between genes, greatly improving the predictions. This gives new insight into the mechanisms of drug resistance and allows researchers to better target genes for new therapies to overcome resistance. The research was led by Amin Emad and Saurabh Sinha, from the KnowEnG BD2K center at UIUC and Junmei Cairns, Krishna R. Kalari and Liewei Wang from Mayo Clinic.

For more information: http://bit.ly/2uY9vE8

Read the article here: http://bit.ly/2v4C7uN

This project is supported by grant U54GM114838 awarded by NIGMS through funds provided by the trans-NIH Big Data to Knowledge (BD2K) initiative.

By |2017-12-12T11:29:59+00:00|Categories: News|