Introduction

Omics data from clinical samples is the predominant source of target discovery and drug development. Typically, hundreds or thousands of differentially expressed genes or proteins are identified from omics data. This scale of possibility is overwhelming for target discovery and validation using biochemical or cellular experiments. Most of these proteins or genes have no corresponding drugs or even active compounds. Moreover, a proportion of these proteins or genes might have been previously reported relevant to the disease of interest. To facilitate the translational drug discovery from omics data, we have developed a new classification tool named OTTM (Omics and Text driven Translational Medicine). This tool is able to sharply narrow the range of proteins or genes worth further validation, via drug availability assessment and literature mining.

Citation

OTTM: an automated classification tool for translational drug discovery from omics data
DOI: XXX