BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//jEvents 2.0 for Joomla//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
BEGIN:VTIMEZONE
TZID:America/New_York
BEGIN:STANDARD
DTSTART:20251102T010000
RDATE:20260308T030000
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:America/New_York EST
END:STANDARD
BEGIN:STANDARD
DTSTART:20261101T010000
RDATE:20270314T030000
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:America/New_York EST
END:STANDARD
BEGIN:STANDARD
DTSTART:20271107T010000
RDATE:20280312T030000
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:America/New_York EST
END:STANDARD
BEGIN:STANDARD
DTSTART:20281105T010000
RDATE:20290311T030000
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:America/New_York EST
END:STANDARD
BEGIN:DAYLIGHT
DTSTART:20250421T104500
RDATE:20251102T010000
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:America/New_York EDT
END:DAYLIGHT
BEGIN:DAYLIGHT
DTSTART:20260308T030000
RDATE:20261101T010000
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:America/New_York EDT
END:DAYLIGHT
BEGIN:DAYLIGHT
DTSTART:20270314T030000
RDATE:20271107T010000
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:America/New_York EDT
END:DAYLIGHT
BEGIN:DAYLIGHT
DTSTART:20280312T030000
RDATE:20281105T010000
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:America/New_York EDT
END:DAYLIGHT
END:VTIMEZONE
BEGIN:VEVENT
UID:16d4c613f5dd4507147fcb2a52a0536e
CATEGORIES:Mathematical Physics Seminar
CREATED:20260405T115333
SUMMARY:Webinar: John Paul Barton – Statistical models to interpret and predict pathogen evolution
LOCATION:zoom
DESCRIPTION:John Paul Barton – University of Pittsburgh\nWednesday, April 22, 2026\nZoo
 m opens: 10:30AM EDT\nSeminar begins: 10:45AM EDT\nStatistical models to in
 terpret and predict pathogen evolution\nPathogen evolution is complex. Viru
 ses must mutate constantly to escape from human immune responses that would
  otherwise prevent infection, all the while preserving their ability to ent
 er cells, replicate, and efficiently transmit from person to person. Do we 
 need similarly complex models to understand their behavior? In this talk, I
 ’ll describe how we can combine simple models with methods from statistical
  physics to both interpret and predict virus evolution, with a particular f
 ocus on influenza.\n
X-ALT-DESC;FMTTYPE=text/html:<p style="text-align: center;"><strong>John Paul Barton – University of Pit
 tsburgh</strong></p><p style="text-align: center;"><strong>Wednesday,&nbsp;
 April 22,&nbsp;2026</strong></p><p style="text-align: center;"><strong>Zoom
  opens: 10:30AM EDT</strong></p><p style="text-align: center;"><strong>Semi
 nar begins: 10:45AM EDT</strong></p><p style="text-align: center;"><strong>
 Statistical models to interpret and predict pathogen evolution</strong></p>
 <p>Pathogen evolution is complex. Viruses must mutate constantly to escape 
 from human immune responses that would otherwise prevent infection, all the
  while preserving their ability to enter cells, replicate, and efficiently 
 transmit from person to person. Do we need similarly complex models to unde
 rstand their behavior? In this talk, I’ll describe how we can combine simpl
 e models with methods from statistical physics to both interpret and predic
 t virus evolution, with a particular focus on influenza.</p>
DTSTAMP:20260826T211413
DTSTART;TZID=America/New_York:20260422T104500
DTEND;TZID=America/New_York:20260422T120000
SEQUENCE:0
TRANSP:OPAQUE
END:VEVENT
END:VCALENDAR