|
Statement of Research Interests
My research is focused on developing bioinformatics approaches that utilize large amounts of data to discover novel biology. The field of bioinformatics and computational biology has expanded greatly due to the development of high-throughput experimental methodologies, such as gene expression microarrays, genomic sequencing, physical and genetic interaction mapping, and tandem mass spectrometry. While these experimental methods provide the keys to a greater understanding of molecular processes and specific gene functions, these data remain largely underutilized by both biologists and computationalists. My work utilizes rigorous statistical methods combined with biologically meaningful algorithms that deeply incorporate expert biological knowledge into the comprehensive analysis and visualization of high-throughput gene expression data. In a manner similar to the way that Google is able to perform similarity searches across vast amounts of data, my work is able to identify and analyze the relevant information contained in the myriad of available expression data, and present that data in a meaningful way.
These approaches can discover truly novel biology, and I am committed to applying these systems to realworld problems both through my own work in and strong collaboration with biologists. My computational data mining approaches have already been utilized to identify biological areas requiring further expression studies, to understand the role of specific alleles in important pathways, and to newly characterize biological functions for over 100 genes. Moving forward, I am interested in developing robust statistical and computational approaches based on machine learning and data mining techniques utilizing additional data sources to discover novel biology in a variety of important organisms. 我要提问
|