BEGIN:VCALENDAR VERSION:2.0 PRODID:-//wp-events-plugin.com//7.2.3.1//EN TZID:Asia/Kolkata X-WR-TIMEZONE:Asia/Kolkata BEGIN:VEVENT UID:20@cds.iisc.ac.in DTSTART;TZID=Asia/Kolkata:20231208T150000 DTEND;TZID=Asia/Kolkata:20231208T160000 DTSTAMP:20231205T090746Z URL:https://cds.iisc.ac.in/events/seminar-cds-102-08th-december-algorithms -to-study-micro-evolutionary-systems/ SUMMARY:{Seminar} @ CDS: #102 : 08th December: "Algorithms to study micro-e volutionary systems" DESCRIPTION:Department of Computational and Data Sciences\n\nDepartment Sem inar\n\n\n\nSpeaker : Dr. Palash Sashittal\nTitle : "Algorithms to study m icro-evolutionary systems"\nDate &\; Time : December 08\, 2023\, 03:00 PM\n\nVenue : # 102\, CDS Seminar Hall\n\n\n\nABSTRACT\n\nRapid advancemen ts in sequencing technologies are revolutionizing the fields of modern med icine and public health management. In recent years\, several groundbreaki ng techniques such as CRISPR-Cas9 genome editing and barcoding of biomolec ules from individual cells have emerged. These breakthroughs\, coupled wit h the decreasing costs of genomic sequencing\, have resulted in the develo pment of various “*-Seq” protocols for measuring DNA\, RNA\, and prote ins at unprecedented throughput and resolution.\n\nIn many biological appl ications\, the bottleneck is not in the generation of sequence data\, but rather in the computational analysis and interpretation of this data. Spec ifically\, the diverse characteristics of these sequencing methods have cr eated a pressing need for specialized algorithms capable of effectively in terpreting the vast amounts of sequencing data.\n\nIn this talk\, I will i ntroduce two such algorithms designed to analyse data from recently develo ped single-cell sequencing technologies. First\, I will present ConDoR\, a n algorithm to infer the evolutionary history of a cancer tumor using targ eted single-cell DNA sequencing (scDNA-seq) data. Underlying ConDoR is a n ew evolutionary model\, the Constrained k-Dollo model\, which generalizes existing models used for cancer evolution. I will show that ConDoR outperf orms existing methods for tumor phylogeny inference methods on simulated a nd real targeted scDNA-seq data. Second\, I will present Startle\, an algo rithm to infer cell lineage trees from CRISPR-Cas9-based lineage tracing d ata. Startle uses a new model\, the star homoplasy model\, which captures the unique characteristics of mutations induced by CRISPR-Cas9. I will dem onstrate that Startle infers more accurate phylogenies on simulated lineag e tracing data compared to existing methods\, and finds parsimonious phylo genies with fewer metastatic migrations on lineage tracing data from mouse metastatic lung adenocarcinoma.\n\nBIOGRAPHY\n\nDr. Palash Sashittal is a Postdoctoral Research Associate with Prof. Ben Raphael in the Computer Sc ience Department at Princeton University. His research focuses on the desi gn of combinatorial and statistical algorithms to analyze and interpret se quencing data. Recent areas of emphasis include infectious disease evoluti on and transmission\, cancer genome evolution\, and cell fate mapping in d evelopmental systems.\n\nHe received a Ph.D. in Aerospace Engineering and M.S. in Computer Science from the University of  Illinois Urbana-Champaig n (UIUC)\, and B.Tech. in Aerospace Engineering from Indian Institute of T echnology Bombay (IIT Bombay). Palash’s work has been recognized by mult iple awards and honors\, including Best Paper Award at RECOMB CCB\, Mistle toe Research Fellowship\, Cornell Future Faculty Fellowship and Mavis Futu re Faculty Fellowship (UIUC). Palash is firmly committed to enhancing dive rsity\, equity\, and inclusion in STEM through mentoring\, outreach\, and service activities.\n\nHost Faculty: Dr. Chirag Jain\n\n\n\nALL ARE WELCOM E CATEGORIES:Events END:VEVENT BEGIN:VTIMEZONE TZID:Asia/Kolkata X-LIC-LOCATION:Asia/Kolkata BEGIN:STANDARD DTSTART:20221208T150000 TZOFFSETFROM:+0530 TZOFFSETTO:+0530 TZNAME:IST END:STANDARD END:VTIMEZONE END:VCALENDAR