Research - Computational Biology

The Brenner Lab develops methods to characterize macromolecular function and relationships using protein and RNA sequence information, evolutionary principles, and computational methods. We also investigate how many natural mRNA transcripts are apparent targets of the nonsense-mediated mRNA decay pathway for RNA surveillance. In many instances, alternative splicing induces NMD for gene regulation.

We study structural and functional characterization of bacterial microcompartments and of proteins involved in photoprotection in photosynthetic organisms.

Associate of the Department

We work on algorithm development for homolog identification, multiple sequence alignment, phylogenetic tree construction, protein fold prediction, identification of domain boundaries (and novel domains), and detection of key amino acids, such as catalytic or binding pocket residues. We integrate phylogenetic tree construction and subfamily identification into our protein structure and function prediction methods, to enable us to infer the changes produced in protein function and structure over the evolution of a protein superfamily.