COLLOQUIUM: Palash Sashittal, Illinois Computer Science, "Algorithms for Infection and Cancer Genomics"
From Erin Klapacz
Continuous innovations and advances in sequencing technologies have led to the birth and development of several fields of research. Today, I will talk about my work on developing algorithms to solve problems in two such fields, infection genomics and cancer genomics. In infection genomics, we will focus on reconstruction of transmission history of an outbreak from genomic and epidemiological information gathered from the infected hosts. The transmission history of an outbreak provides crucial information that facilitates public health policy decisions. Often there are multiple transmission histories that can explain the observations equally well. Most current methods for transmission history inference generate just one of the possible solutions leading to biases in downstream analyses. In this talk, I will present a transmission history inference method that accounts for the uncertainty in the solutions and summarizes a set of candidate solutions in a biological meaningful way. On the cancer genomics side, we will discuss the problem of cancer tumor phylogeny reconstruction. Cancer is the result of an evolutionary process where cells acquire somatic mutations and eventually lead to multiple subpopulations of tumor cells with distinct genomes. Tumor phylogenies provide evolutionary relationship between these subpopulations of cells in a cancer tumor and have several clinical applications, such as identifying targets for cancer treatment and understanding the development of metastasis. While cancer cells contain mutations that alter genomes at varying length scales, current tumor phylogeny reconstruction methods only focus on either the small-scale or the large-scale mutations, but not both. In this talk, I will present a novel method of reconciling the results from existing methods to generate a tumor phylogeny with both small and large-scale mutations providing a comprehensive picture of the clonal architecture of the cancer tumor.
Palash Sashittal is a graduate student at University of Illinois, Urbana Champaign. He is pursuing PhD in Aerospace Engineering and Masters in Computer Science. Prior to this, he completed B.Tech. in Aerospace Engineering at Indian Institute of Technology, Bombay.