Vanathi Gopalakrishnan
University of Pittsburgh School of Medicine, USA
Title: Novel methods for integrative modeling of biomedical data
Biography
Biography: Vanathi Gopalakrishnan
Abstract
Molecular profiling data from scientific studies aiming for early detection and better management of diseases such as cancer has accumulated at rates far beyond our abilities to efficiently extract knowledge of value to the practice of precision medicine. A major challenge is that these data are often generated using multiple high-throughput technologies giving rise to panomics data such as gene expression and DNA methylation for the same or related classification task. In this talk, I will present novel computational methods and tools that are being developed in my laboratory for the integrative modeling of panomics data to improve disease state classification from related molecular profiling studies. We are extending the novel Transfer Rule Learning (TRL) methods that were previously developed to deal with sparse data from biomarker profiling studies, by automatically learning classification rules from one dataset, transferring that knowledge and using it when learning rules from a related dataset. The extensions include methods for knowledge transfer using ontological or taxonomic hierarchies along with classification rule learning. Preliminary results from collaborative studies involving biomarker profiling data for the early detection of lung cancer and microbiome data for infectious disease classification will be presented.