Bioinformatics or computational biology is an exciting new area of interdisciplinary science. Bioinformatics tries to solve biological problems using computational techniques to make sense of the large amount of data generated from high-throughput molecular biology experiments. Some application areas of bioinformatics are drug development, cancer research, personalized medicine and agriculture.
In our lab, we develop statistical methods to better understand gene regulation. We often use existing machine learning techniques to predict biological properties of systems. Our current focus is to understand the interplay between RNA-binding proteins and microRNAs. We also collaborate with other labs on diverse areas such as drug-drug interactions, variant effect prediction, protein binding preference prediction etc.
Faculty: Hilal Kazan
• D Ray*, H Kazan*, KB Cook*, MT Weirauch*, HS Najafabadi* et al., (2013) A compendium of RNA-binding motifs for decoding gene-regulation. Nature 499:172-177 *co-first authors
• H Kazan, D Ray, E Chan, TR Hughes and Q Morris (2010) RNAcontext: A new method for learning the sequence and structure binding preferences of RNA-binding proteins. PLoS Comput Biol 6(7): e1000832.
• D Ray*, H Kazan*, E Chan, LP Castillo, S Talukder et. al. (2009) Rapid and systematic characterization of the RNA recognition specificities of RNA-binding proteins. Nature Biotechnology, 27: 667-670 *co-first authors