{"521231":{"#nid":"521231","#data":{"type":"event","title":"Statistics Seminar - Nancy Zhang","body":[{"value":"\u003Cp\u003ETITLE:\u0026nbsp; Profiling Tumor DNA and inferring its Evolutionary History\u003C\/p\u003E\u003Cp\u003EABSTRACT:\u003C\/p\u003E\u003Cp\u003ECancer is a disease driven by rounds of Darwinian selection on somatic genetic mutations, and recent advances in sequencing technologies is offering new opportunities as well as revealing new challenges in this field.\u0026nbsp; \u0026nbsp;\u0026nbsp;In this talk, I will describe two statistical problems in the genetic analysis of tumors.\u0026nbsp; In the first part, I will describe the problem of allele-specific copy number estimation.\u0026nbsp; Copy number change is a basic type of DNA alteration in tumors, and understanding how they affect the tumor\u2019s genome at the allelic level is fundamental to understanding the tumor\u2019s genetic signature.\u0026nbsp; I will describe a bivariate binomial mixture process for this problem, and a method for detecting change-points in this process.\u0026nbsp; In the second part, I will describe the problem of inferring a tumor\u2019s clonal evolutionary history through repeated bulk DNA sampling.\u0026nbsp; This is similar to classic phylogenetic inference problems, with the key difference being that the observed data are slices of a mixed population.\u0026nbsp; \u0026nbsp;\u0026nbsp;I will describe a framework that we developed to estimate the underlying evolutionary tree by joint modeling single nucleotide mutation and allele-specific copy number profiles.\u0026nbsp;\u003C\/p\u003E\u003Cp\u003EBIO:\u003C\/p\u003E\u003Cp\u003ENancy R. Zhang obtained her doctoral degree in Statistics at Stanford University in 2005.\u0026nbsp; After a year\u2019s post-doctoral study at UC Berkeley, she returned to Stanford as assistant professor in the department of Statistics.\u0026nbsp; She was promoted to associate professor at Stanford in 2011, when she moved to the department of Statistics in the Wharton School at University of Pennsylvania. \u0026nbsp;Currently, she is working in the area of applying statistical concepts to modeling and inference problems in computational genomics.\u0026nbsp; In particular, she is developing computational techniques to study heterogeneous tissues through bulk and single-cell sequencing data.\u0026nbsp;\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Statistics Seminar - Nancy Zhang"}],"uid":"27187","created_gmt":"2016-04-04 08:55:12","changed_gmt":"2017-04-13 21:16:04","author":"Anita Race","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2016-04-07T12:00:00-04:00","event_time_end":"2016-04-07T12:00:00-04:00","event_time_end_last":"2016-04-07T12:00:00-04:00","gmt_time_start":"2016-04-07 16:00:00","gmt_time_end":"2016-04-07 16:00:00","gmt_time_end_last":"2016-04-07 16:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78751","name":"Undergraduate students"},{"id":"78761","name":"Faculty\/Staff"},{"id":"174045","name":"Graduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}}}