What is Computational Biology and Bioinformatics?
The goal of computational biology and bioinformatics is to understand biology through the development of mathematical models, the use of computer simulation techniques and statistical analysis of large biological data-sets. Researchers in computational biology and bioinformatics develop algorithms that can predict the behavior of a biological system and explore the molecular mechanisms of function of nucleic acids and/or proteins.
Our research in the area of Computational Biology and Bioinformatics
The BMP department has expertise in many different areas, and computational biology and bioinformatics are key or central components for many of our studies. The Schiffer group uses molecular dynamics, detailed structural analysis, sequence analysis and structure based drug design to elucidate the molecular mechanisms by which mutations confer drug resistance and to develop strategies for avoiding drug resistance. The Royer laboratory uses computational methods to analyze protein structures and, currently, to design inhibitors to the cancer target, C-terminal Binding Protein (CtBP), a transcriptional co-regulator involved in regulation of hundreds of genes. The Massi group uses computer simulations to understand the fundamental aspects of molecular recognition and binding specificity of RNA binding proteins that regulate the stability of mRNA transcripts encoding key cancer-related proteins. The Kelch lab uses molecular dynamics simulations and molecular modeling approaches to determine the structures and mechanisms of large complicated macromolecular machines. The Weng laboratory builds and applies computational algorithms to integrate deep sequencing genomic, epigenomic, and transcriptomic data to study gene regulation. The Rhind lab uses mathematical models to analyze genome-wide DNA replication kinetics. The Rando lab uses a variety of genome-wide methods to study chromatin structure and function, and epigenetic inheritance, and collaborates extensively with computational biologists to both implement extant analytical approaches as well as design novel types of data analysis.
Our breakthrough discoveries
Our researchers have made important breakthroughs in many areas. The Schiffer lab has demonstrated that drug resistance can be predicted and avoided through the incorporation of the substrate envelope in structure based drug design and has shown that mutations remote from the active site can confer resistance by altering the dynamic network of the drug target. Efforts from the Royer labs have resulted in a number of new inhibitors that are explored as potential lead compounds for the development of highly selective antineoplastic CtBP inhibitors. The Massi lab has determined the molecular origin of the order/disorder transition in the TIS11 family of RNA-binding proteins and characterized how this structural transition affects the activity of these proteins in the cell. The Kelch Lab recently used molecular modeling to produce a structural model of an exceptionally powerful DNA motor used in viruses to package their genomes. The Weng lab is a leading analytical member of the ENCODE and psychENCODE consortia and has determined molecular mechanisms of gene regulation as well as how genetic variations in the human population affect gene regulation and susceptibility for diseases. The Rhind lab predicted from computational analysis of genome-wide replication kinetics data that multiple MCM initiation complexes are loaded at each replication origin and confirmed that prediction experimentally.