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DTSTART;TZID="Pacific Time (US & Canada)":20210624T150000
DTEND;TZID="Pacific Time (US & Canada)":20210624T170000
SUMMARY:Jin Tao – Doctoral Defense
LOCATION:Online
DESCRIPTION:Student: Jin Tao\n\nDegree: Computer Science Ph.D.\n\nAdvisor: Dr. Shira Broschat\n\nDissertation Title: A Software System for Assisting with Protein Annotation\n\nAbsract:\n\nAdvances in genome sequencing have accelerated the growth of sequenced genomes but at a cost in the quality of genome annotation. At the same time, computational analysis is widely used for protein annotation, but a dearth of experimental verification has contributed to inaccurate annotation as well as to annotation error propagation. Thus, a tool to help life scientists with accurate protein annotation would be useful. In this work we describe a website we have developed, the Protein Annotation Surveillance Site (PASS), which provides such a tool. This website has three main components: a database of homologous clusters with more than nine million protein sequences deduced from the representative genomes of bacteria, archaea, eukarya, and viruses, together with sequence information; a machine-learning software tool which periodically queries the UniprotKB database to determine whether protein function has been experimentally verified; and a query-able webpage where the FASTA headers of sequences from the cluster best matching an input sequence are returned. The user can choose from these sequences to create a sequence similarity network to assist in annotation or else use their expert knowledge to choose an annotation from the cluster sequences. Illustrations demonstrating use of this website are given, and the Protein Annotation Surveillance Site (PASS) can be accessed at https://pass.eecs.wsu.edu/.
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