ISE Seminar Calendar

Abstract: Reconstructing the evolutionary past is a prerequisite for a diverse set of biological analyses, including comparative genomics, detecting gene function, detecting signatures of selection, and understanding the microbiome. The reconstructions of these phylogenetic histories spanning millions to billions of years are entirely computational endeavors, as no experiment can directly validate them. As such, much thought has been put into modelling genome evolution and designing algorithms for reconstruction under those models. A key feature of these algorithms is the difficulty of the resulting optimization problems (which are almost always NP-hard). What adds to the complexity is that evolutionary histories vary across the genome, and modeling this heterogeneity further increases complexity. In this talk, we review this literature, focusing on modeling approaches and optimization problems that aim to capture heterogeneity across the genome while remaining scalable, thereby enabling phylogenomics.

Bio: Siavash Mirarab is a Professor in the ECE Department at the University of California, San Diego, and is also affiliated with the CSE department and the Center for Microbiome Innovation. He obtained his Ph.D. from the Computer Science department at UT-Austin and was advised by Prof. Tandy Warnow. His Ph.D. research was supported by an NSERC PGS award and Howard Hughes Medical Institute international student fellowship, and his dissertation won the honorable mention for the 2015 ACM Doctoral Dissertation Award. He has been a recipient of the 2017 Sloan Research Fellowship in Computational & Evolutionary Molecular Biology, the NSF CAREER award, and the MIRA (R35) awrd from NIGMS (NIH). He has been named on the Clarivate Highly Cited Researcher lists in 2023, 2024, and 2025. He has contributed to many international projects and is part of the Vertebrate Genome Project Council. His interest is in computational biology. His lab develops methods that target large-scale analyses in various areas, including phylogenomics, microbiome and metagenomic analyses using phylogenetic approaches, large-scale multiple sequence alignment, and HIV transmission network reconstruction.