Workshop on Systems Biology using COPASI

#systems #biology #simulation #copasi
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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's stochastic simulation algorithm; arbitrary discrete events can be included in such simulations.


  Date and Time

  Location

  Hosts

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  • Date: 16 Jul 2018
  • Time: 08:00 AM to 06:00 PM
  • All times are (GMT-06:00) America/Costa_Rica
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  • Auditorio de Física Matemática, Universidad de Costa Rica
  • San José, San Jose
  • Costa Rica

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  • Starts 02 July 2018 08:00 AM
  • Ends 15 July 2018 11:59 PM
  • All times are (GMT-06:00) America/Costa_Rica
  • No Admission Charge


  Speakers

Pedro Mendes, PhD. of University of Connecticut

Topic:

Systems Biology using COPASI

Biography:

Pedro Mendes is a professor of the University of Connecticut (University of Connecticut Health Center, Center for Quantitative Medicine, Department of Cell Biology, and Center for Cell Analysis and Modeling.). His backgroun is in Biochemistry at the University of Lisboa and obtained his PhD at the University of Wales Aberystwyth, the Computer simulation of the dynamics of biochemical pathways), under the supervision of Douglas B. Kell. Mendes has published more than 120 manuscripts having a total of 17734 citations and h-index of 49 according to Google Scholar. His background is in Biochemistry and computer science. He has interest and research in both areas and their joint application. His area of research is in computational  systems biology, where he has demonstrated leadership in biochemical modeling and simulation; he was the author of Gepasi, a popular and pioneering software package for modeling biochemical networks, which then became COPASI, now one of the top simulators for systems biology.





Agenda

8 am to 12pm

-Construction of Mathematical Models and

visualization.

- Construction of data files for parameter estimation.

- Steady State Analysis.

- Time Course Simulations.

- Parameter Scans.

- Sensitivity Analysis.

 

1pm to 6pm

 

- Metabolic Control Analysis.

- Lyapunov Exponents.

- Time Scale Separation.

- Cross Section.

- Parameter identifiability.

- Cloud COPASI.

- ManyCell.

- Large scale modeling and reverse engineering.