BEGIN:VCALENDAR
VERSION:2.0
PRODID:Linklings LLC
BEGIN:VTIMEZONE
TZID:America/Chicago
X-LIC-LOCATION:America/Chicago
BEGIN:DAYLIGHT
TZOFFSETFROM:-0600
TZOFFSETTO:-0500
TZNAME:CDT
DTSTART:19700308T020000
RRULE:FREQ=YEARLY;BYMONTH=3;BYDAY=2SU
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0500
TZOFFSETTO:-0600
TZNAME:CST
DTSTART:19701101T020000
RRULE:FREQ=YEARLY;BYMONTH=11;BYDAY=1SU
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTAMP:20260522T150115Z
LOCATION:C2/3/4 Ballroom
DTSTART;TZID=America/Chicago:20181113T083000
DTEND;TZID=America/Chicago:20181113T170000
UID:submissions.supercomputing.org_SC18_sess322_post131@linklings.com
SUMMARY:Capsule Networks for Protein Structure Classification
DESCRIPTION:Dan A. Rosa de Jesus, Julian Cuevas Paniagua, and Wilson River
 a (Lawrence Berkeley National Laboratory, University of Puerto Rico at May
 aguez) and Silvia Crivelli (Lawrence Berkeley National Laboratory)\n\nCaps
 ule Networks have great potential to tackle problems in structural biology
  because of their attention to hierarchical relationships. This work descr
 ibes the implementation and application of a capsule network architecture 
 to the classification of RAS protein family structures on GPU-based comput
 ational resources. Our results show that the proposed capsule network trai
 ned on 2D and 3D structural encodings can successfully classify HRAS and K
 RAS structures. The capsule network can also classify a protein-based data
 set derived from a PSI-BLAST search on sequences of KRAS and HRAS mutation
 s. Experimental results show an accuracy improvement compared to tradition
 al convolutional networks.\n\nRegistration Category: Tech Program Reg Pass
 , Exhibits Reg Pass\n\n
END:VEVENT
END:VCALENDAR