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DTSTART:20260308T030000
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DTSTART:20261101T010000
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DTSTAMP:20261011T233119Z
UID:F1DEF433-6C1B-4250-8505-306BE744AA54
DTSTART;TZID=America/Los_Angeles:20261008T183000
DTEND;TZID=America/Los_Angeles:20261008T193000
DESCRIPTION:Data clustering and classification are fundamental problems in 
 data science\, with applications in almost every field of study. In this t
 alk\, we present prototype software that applies a data science approach t
 o identifying groups of closely related species and possible species compl
 exes.\n\nWe will present our prototype software\, which implements a pipel
 ine that queries the GenBank and BOLD databases for genetic data\, uses se
 quence alignment to generate measures of genetic similarity\, and augments
  these measures with morphological data. Similarity relationships are visu
 alized as network graphs\, allowing users to identify and propose potentia
 l species groupings for further investigation.\n\nThis ongoing project has
  been jointly funded by Okanagan College’s Grants-in-Aid Fund and the Co
 llege’s Department of Applied Science.\n\nSpeaker(s): Dr. Jim Nastos\, C
 lara Elliott\n\nRoom: 309\, Bldg: E\, 1000 K. L. O. Rd\, Kelowna\, British
  Columbia\, Canada\, V1Y 4X8\, Virtual: https://events.vtools.ieee.org/m/5
 82734
LOCATION:Room: 309\, Bldg: E\, 1000 K. L. O. Rd\, Kelowna\, British Columbi
 a\, Canada\, V1Y 4X8\, Virtual: https://events.vtools.ieee.org/m/582734
ORGANIZER:Youry@ieee.org
SEQUENCE:21
SUMMARY:A Computational Approach to Species Complexes
URL;VALUE=URI:https://events.vtools.ieee.org/m/582734
X-ALT-DESC:Description: <br /><div class="entry-content">\n<p>Data clusteri
 ng and classification are fundamental problems in data science\, with appl
 ications in almost every field of study. In this talk\, we present prototy
 pe software that applies a data science approach to identifying groups of 
 closely related species and possible species complexes.</p>\n<p>We will pr
 esent our prototype software\, which implements a pipeline that queries th
 e GenBank and BOLD databases for genetic data\, uses sequence alignment to
  generate measures of genetic similarity\, and augments these measures wit
 h morphological data. Similarity relationships are visualized as network g
 raphs\, allowing users to identify and propose potential species groupings
  for further investigation.</p>\n<p>This ongoing project has been jointly 
 funded by Okanagan College&rsquo\;s Grants-in-Aid Fund and the College&rsq
 uo\;s Department of Applied Science.</p>\n</div>
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