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VERSION:2.0
PRODID:IEEE vTools.Events//EN
CALSCALE:GREGORIAN
BEGIN:VTIMEZONE
TZID:America/Costa_Rica
BEGIN:STANDARD
DTSTART:19920314T230000
TZOFFSETFROM:-0500
TZOFFSETTO:-0600
TZNAME:CST
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BEGIN:VEVENT
DTSTAMP:20180903T195324Z
UID:57E6C056-AFDF-4437-81AF-6E7DE592F576
DTSTART;TZID=America/Costa_Rica:20180716T080000
DTEND;TZID=America/Costa_Rica:20180716T180000
DESCRIPTION:COPASI is a software application for simulation and analysis of
  biochemical networks and their dynamics. COPASI is a stand-alone program 
 that supports models in the SBML standard and can simulate their behavior 
 using ODEs or Gillespie&#39;s stochastic simulation algorithm\; arbitrary disc
 rete events can be included in such simulations.\n\nSpeaker(s): Pedro Mend
 es\, PhD.\, \n\nAgenda: \n8 am to 12pm\n-Construction of Mathematical Mode
 ls and\nvisualization.\n- Construction of data files for parameter estimat
 ion.\n- Steady State Analysis.\n- Time Course Simulations.\n- Parameter Sc
 ans.\n- Sensitivity Analysis.\n\n1pm to 6pm\n\n- Metabolic Control Analysi
 s.\n- Lyapunov Exponents.\n- Time Scale Separation.\n- Cross Section.\n- P
 arameter identifiability.\n- Cloud COPASI.\n- ManyCell.\n- Large scale mod
 eling and reverse engineering.\n\nAuditorio de Física Matemática\, Unive
 rsidad de Costa Rica\, San José\, San Jose\, Costa Rica
LOCATION:Auditorio de Física Matemática\, Universidad de Costa Rica\, San
  José\, San Jose\, Costa Rica
ORGANIZER:rodrigo.morarodriguez@ucr.ac.cr
SEQUENCE:2
SUMMARY:Workshop on Systems Biology using COPASI
URL;VALUE=URI:https://events.vtools.ieee.org/m/174509
X-ALT-DESC:Description: &lt;br /&gt;&lt;div style=&quot;left: 70.6667px\; top: 627.678px\
 ; font-size: 20px\; font-family: serif\; transform: scaleX(0.978794)\;&quot;&gt;CO
 PASI is a software application for simulation and analysis of biochemical 
 networks and their dynamics. COPASI is a stand-alone program that supports
  models in the SBML standard and can simulate their behavior using ODEs or
  Gillespie&#39;s stochastic simulation algorithm\; arbitrary discrete events c
 an be included in such simulations.&lt;/div&gt;&lt;br /&gt;&lt;br /&gt;Agenda: &lt;br /&gt;&lt;p&gt;8 am
  to 12pm&lt;/p&gt;\n&lt;div style=&quot;left: 82.6667px\; top: 1173.07px\; font-size: 17
 .5px\; font-family: serif\; transform: scaleX(0.997078)\;&quot;&gt;-Construction o
 f Mathematical Models and&lt;/div&gt;\n&lt;div style=&quot;left: 82.6667px\; top: 1192.5
 7px\; font-size: 17.5px\; font-family: serif\; transform: scaleX(0.994236)
 \;&quot;&gt;visualization.&lt;/div&gt;\n&lt;div style=&quot;left: 82.6667px\; top: 1212.24px\; f
 ont-size: 17.5px\; font-family: serif\; transform: scaleX(0.996769)\;&quot;&gt;- C
 onstruction of data files for parameter estimation.&lt;/div&gt;\n&lt;div style=&quot;lef
 t: 82.6667px\; top: 1212.24px\; font-size: 17.5px\; font-family: serif\; t
 ransform: scaleX(0.996769)\;&quot;&gt;- Steady State Analysis.&lt;/div&gt;\n&lt;div style=&quot;
 left: 82.6667px\; top: 1212.24px\; font-size: 17.5px\; font-family: serif\
 ; transform: scaleX(0.996769)\;&quot;&gt;- Time Course Simulations.&lt;/div&gt;\n&lt;div st
 yle=&quot;left: 82.6667px\; top: 1271.07px\; font-size: 17.5px\; font-family: s
 erif\; transform: scaleX(0.994864)\;&quot;&gt;- Parameter Scans.&lt;/div&gt;\n&lt;div style
 =&quot;left: 82.6667px\; top: 1271.07px\; font-size: 17.5px\; font-family: seri
 f\; transform: scaleX(0.994864)\;&quot;&gt;- Sensitivity Analysis.&lt;/div&gt;\n&lt;div sty
 le=&quot;left: 82.6667px\; top: 1290.74px\; font-size: 17.5px\; font-family: se
 rif\; transform: scaleX(0.982324)\;&quot;&gt;&amp;nbsp\;&lt;/div&gt;\n&lt;div style=&quot;left: 82.6
 667px\; top: 1290.74px\; font-size: 17.5px\; font-family: serif\; transfor
 m: scaleX(0.982324)\;&quot;&gt;1pm to 6pm&lt;/div&gt;\n&lt;div style=&quot;left: 502.667px\; top
 : 1155.98px\; font-size: 16.6667px\; font-family: serif\; transform: scale
 X(0.988697)\;&quot;&gt;&amp;nbsp\;&lt;/div&gt;\n&lt;div style=&quot;left: 502.667px\; top: 1174.81px
 \; font-size: 16.6667px\; font-family: serif\; transform: scaleX(0.991403)
 \;&quot;&gt;- Metabolic Control Analysis.&lt;/div&gt;\n&lt;div style=&quot;left: 502.667px\; top
 : 1193.65px\; font-size: 16.6667px\; font-family: serif\; transform: scale
 X(0.994925)\;&quot;&gt;- Lyapunov Exponents.&lt;/div&gt;\n&lt;div style=&quot;left: 502.667px\; 
 top: 1212.48px\; font-size: 16.6667px\; font-family: serif\; transform: sc
 aleX(0.994341)\;&quot;&gt;- Time Scale Separation.&lt;/div&gt;\n&lt;div style=&quot;left: 502.66
 7px\; top: 1231.31px\; font-size: 16.6667px\; font-family: serif\; transfo
 rm: scaleX(0.993534)\;&quot;&gt;- Cross Section.&lt;/div&gt;\n&lt;div style=&quot;left: 502.667p
 x\; top: 1249.98px\; font-size: 16.6667px\; font-family: serif\; transform
 : scaleX(0.99385)\;&quot;&gt;- Parameter identifiability.&lt;/div&gt;\n&lt;div style=&quot;left:
  502.667px\; top: 1268.81px\; font-size: 16.6667px\; font-family: serif\; 
 transform: scaleX(0.988413)\;&quot;&gt;- Cloud COPASI.&lt;/div&gt;\n&lt;div style=&quot;left: 50
 2.667px\; top: 1287.65px\; font-size: 16.6667px\; font-family: serif\; tra
 nsform: scaleX(0.993706)\;&quot;&gt;- ManyCell.&lt;/div&gt;\n&lt;div style=&quot;left: 502.667px
 \; top: 1287.65px\; font-size: 16.6667px\; font-family: serif\; transform:
  scaleX(0.993706)\;&quot;&gt;- Large scale modeling and reverse engineering.&lt;/div&gt;
 \n&lt;div style=&quot;left: 82.6667px\; top: 1290.74px\; font-size: 17.5px\; font-
 family: serif\; transform: scaleX(0.982324)\;&quot;&gt;&amp;nbsp\;&lt;/div&gt;
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