<html><body><div style="font-family: garamond,new york,times,serif; font-size: 12pt; color: #000000"><div data-marker="__QUOTED_TEXT__"><div style="font-family: garamond,new york,times,serif; font-size: 12pt; color: #000000"><div><div style="font-family: garamond,new york,times,serif; font-size: 12pt; color: #000000"><div>Shilpa Nadimpalli will present her pre-FPO for on Monday, February 13, 2017 at 9am in CS 401.</div><br><div><div dir="ltr"><div>The members of her committee are as follows: <span style="color: #000000; font-family: garamond, 'new york', times, serif; font-size: 16px; font-style: normal; font-variant-ligatures: normal; font-variant-caps: normal; font-weight: normal; letter-spacing: normal; orphans: 2; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px; -webkit-text-stroke-width: 0px; background-color: #ffffff; display: inline !important; float: none;">Mona Singh (Adviser); Readers: Ben Raphael and Olga Troyanskaya; Nonreaders: </span>Barbara Engelhardt and Tom Funkhouser </div></div><div dir="ltr" style="color: #000000; font-family: 'Times New Roman'; font-size: 14.16px; font-style: normal; font-variant-ligatures: normal; font-variant-caps: normal; font-weight: normal; letter-spacing: normal; orphans: 2; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px; -webkit-text-stroke-width: 0px; background-color: #ffffff;"><div dir="ltr" class="gmail_msg"><div class="gmail_msg"><div class="gmail_msg" style="font-size: 13px;"><br></div><div class="gmail_msg" style="font-size: 13px;">The talk abstract follows below: </div><div class="gmail_msg" style="font-size: 13px;"><br></div><div class="gmail_msg" style="font-size: 13px;">Proteins play essential roles in nearly every biological process, from metabolism and sensory perception to immune response and gene regulation.<span class="m_-4901013931597794093inbox-m_-3421117347975420270inbox-m_3639637909403698456m_510502782581226512inbox-inbox-inbox-inbox-Apple-converted-space gmail_msg"> </span><span class="gmail_msg">The vast majority of these functions are carried out through specific protein interactions with DNA, metabolites and other ligands, forming complex biological networks.</span> Although mutations affecting protein interactions have resulted in human disease, other protein interactions evolve naturally within the human population and across species. Experimental techniques to determine the prevalence and functional impact of mutations affecting protein interactions are prohibitively costly<span class="m_-4901013931597794093inbox-m_-3421117347975420270inbox-m_3639637909403698456m_510502782581226512inbox-inbox-Apple-converted-space gmail_msg"> </span>and time-consuming (e.g., x-ray crystallography, protein binding microarrays). In my thesis, I develop and use novel computational approaches to measure the extent to which protein interactions are perturbed across healthy individuals, across individuals with disease, and across species.</div><div class="gmail_msg" style="font-size: 13px;"><br class="gmail_msg"></div><div class="gmail_msg" style="font-size: 13px;">In my talk, I will first describe a tool I have developed to automatically infer interaction sites from sequence data. This tool can infer interaction sites in over 60% of human genes---a nearly threefold increase in coverage over related state-of-the-art methods. Next, I will focus on utilizing this tool to identify genes whose interaction sites are enriched in cancer mutations by contrasting observed natural variants from tens of thousands of healthy individuals to observed cancer mutations from thousands of tumor samples. These genes, often rarely mutated across a cohort of patients and thus easily missed by more standard approaches, are likely to be<span class="m_-4901013931597794093inbox-m_-3421117347975420270inbox-m_3639637909403698456m_510502782581226512inbox-inbox-Apple-converted-space gmail_msg"> </span>critically relevant for cancer development. In the last part of my talk, I will discuss my application of a comparative genomics framework to quantify changes in protein-DNA interactions across species. I find substantial evidence suggesting that, contrary to popular convention, gene regulatory network perturbation can stem from changes in non-duplicated DNA-binding proteins.</div></div></div></div><div dir="ltr" style="color: #000000; font-family: 'Times New Roman'; font-size: 14.16px; font-style: normal; font-variant-ligatures: normal; font-variant-caps: normal; font-weight: normal; letter-spacing: normal; orphans: 2; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px; -webkit-text-stroke-width: 0px; background-color: #ffffff;">--</div></div></div></div></div><br></div></div></body></html>