Eli Upfal And Collaborators Receive A 2023 RECOMB Test Of Time Award

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Every year, the International Conference on Research in Computational Molecular Biology (RECOMB) bestows its Test of Time Award on regular or special issue papers presented at the conference that were influential in providing a major stepping stone for theoretical advances in computational biology and their applications in molecular biology and medicine. In April, the 2023 conference held in Istanbul, Turkey, recognized the paper “De Novo Discovery of Mutated Driver Pathways in Cancer” presented at RECOMB 2011 and authored by Brown CS faculty member Eli Upfal, Fabio Vandin, now at the University of Padova, Italy, and Ben Raphael, now at Princeton University.

The paper presents research conducted when all three authors were at Brown CS and CCMB. It addresses the challenge of distinguishing functional driver mutations from random passenger mutations in cancer genomes. The conventional approach of identifying driver mutations based on their significant frequency in a large cohort of cancer genomes, the researchers explain, is confounded by the fact that driver mutations target multiple cellular pathways, leading to variations in the combinations of mutations among patients. The paper proposes a de novo approach to address this problem by analyzing genome-wide somatic mutation data, highlighting two potential constraints: (1) important cancer pathways should be perturbed in a large number of patients, resulting in high coverage of mutations within the pathway; and (2) most patients are expected to have a single driver mutation in a pathway. By analyzing these patterns of mutually exclusive driver mutations within a pathway, the research aims to discover and characterize novel mechanisms driving tumorigenesis in diverse cancer types. 

“The significance of this work was that it demonstrated how combinatorial considerations can inform and streamline biology research,” Eli says. “It also developed efficient randomized approximations for related computation problems that are hard to solve precisely.”

Eli explains that the preliminary version of this work was published in the CS venue of RECOMB, while the full paper was published in the biology journal Genome Research, exposing both communities to this work. 

Eli Upfal is a computer scientist who has made contributions to various areas of theoretical computer science, including algorithms, probability theory, and randomized algorithms. His research focuses on the design and analysis of algorithms, and the applications of his research range from communication networks to computational biology and computational finance.

Fabio Vandin is a researcher in the field of computational biology and bioinformatics. His focus is on the design and analysis of combinatorial and statistical algorithms for biological data, with emphasis on problems that arise in the analysis of datasets from high-throughput technologies. He has made contributions to the analysis of cancer genomics data, particularly in the context of identifying driver mutations and understanding the genetic alterations that drive cancer progression. His work often involves developing statistical and computational methods to analyze large-scale genomic datasets.

Ben Raphael is a computer scientist and computational biologist who has made contributions to the field of cancer genomics. His research focuses on developing algorithms and computational methods to analyze genomic data and identify driver mutations in cancer. He has worked on problems such as inferring cancer evolution, reconstructing tumor phylogenies, and predicting cancer progression.

For more information, please click the link that follows to contact Brown CS Communications Manager Jesse C. Polhemus.