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DTSTART:19700308T020000
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BEGIN:VEVENT
DTSTAMP:20211207T055407Z
LOCATION:Online
DTSTART;TZID=America/Chicago:20211115T120000
DTEND;TZID=America/Chicago:20211115T123000
UID:submissions.supercomputing.org_SC21_sess423_ws_mlhpce106@linklings.com
SUMMARY:High-Performance Deep Learning Toolbox for Genome-Scale Prediction
  of Protein Structure and Function
DESCRIPTION:Workshop\n\nHigh-Performance Deep Learning Toolbox for Genome-
 Scale Prediction of Protein Structure and Function\n\nGao, Sedova, Cheng\n
 \nComputational biology is one of many scientific disciplines ripe for inn
 ovation and acceleration with the advent of high-performance computing (HP
 C). In recent years, the field of machine learning has also seen significa
 nt benefits from adopting HPC practices. In this work, we present a novel 
 HPC pipeline that incorporates various machine-learning approaches for str
 ucture-based functional annotation of proteins on the scale of whole genom
 es. Our pipeline makes extensive use of deep learning and provides computa
 tional insights into best practices for training advanced deep-learning mo
 dels for high-throughput data such as proteomics data. We showcase methodo
 logies our pipeline currently supports and detail future tasks for our pip
 eline to envelop, including large-scale sequence comparison using SAdLSA a
 nd prediction of protein tertiary structures using AlphaFold2.\n\nTag: Onl
 ine Only, Machine Learning and Artificial Intelligence\n\nRegistration Cat
 egory: Workshop Reg Pass
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