Research

The underlying goal of my research is to investigate complex biological systems through integrative analysis of molecular data. Over the past six years, I have had the opportunity to work on diverse computational problems including analysis of next-generation sequencing data, prediction of gene function and phenotype, and flux balance analysis. My primary focus is on developing efficient, accurate, and reproducible algorithmic frameworks based on graph theory and machine learning.

My main projects are:

• Accurate and Efficient Gene Function Prediction using a Multi-Bacterial Network
• Computational Construction of Chemical Signaling Networks