V. Devanarayan : Some important statistical considerations in biomarker discovery from high-dimensional data

Posted by Ryan Martin , part of the Statistics and Data Science Seminar.

At

Oct. 29, 2014, 4 p.m.

In

SEO 636

Abstract

Biomarkers such as those based on genomic, proteomic and imaging modalities play a vital role in biopharmaceutical R&D. Examples include the discovery of novel genes/targets related to various diseases based on which a suitable therapeutic can be developed, diagnostics for different disease subtypes, identification of patients that are more likely to progress in disease or benefit from a particular therapeutic, etc. The discovery of such biomarkers are typically based on the evaluation of high-dimensional datasets that require a strong combination of bioinformatic and statistical considerations. This seminar will provide a practical overview and intuitive explanation of some important concepts and considerations around the analyses of such high-dimensional data.