Decoding the genes and their alternative splicing variations with splice graphs

Liliana Florea, Johns Hopkins University

Alternative splicing is an essential property of eukaryotic genes: a single stretch of RNA is spliced into multiple variants, each capable of producing a protein with different functionality. The splice graph has emerged as a natural representation of a gene and its splice variants. However, distinguishing the true variants from among the thousands, if not millions of combinations mathematically encoded in the graph presents significant algorithmic challenges. I will present splice graph-based algorithms and software tools we developed to determine genes and their splice variants from high-throughput sequencing data, either conventional (Sanger) or produced with the more recent next generation sequencing technologies. Our methods take into account intrinsic properties of the sequence data to select a subset of candidate variants that captures the genes and their alternative splicing variations with high-accuracy.

Speaker Biography

Liliana Florea is an Assistant Professor with the McKusick-Nathans Institute of Genetic Medicine at the Johns Hopkins University School of Medicine, where she develops algorithms and software tools for analyzing biological data. She previously held faculty positions at the University of Maryland and at the George Washington University. Even earlier, she was a member of the team of scientists at Celera Genomics that sequenced and assembled the first human genome sequence. Dr. Florea was a recipient of a Sloan Foundation Research Fellowship in Computational and Evolutionary Molecular Biology and a finalist for the Microsoft Research Faculty Fellowship. She received her PhD in Computer Science and Engineering from the Pennsylvania State University in 2000.