Difference between revisions of "CNLS q-bio Seminars"

Revision as of 16:13, 21 January 2010

This weekly series of seminars aims to advance predictive modeling of cellular regulation, decision making, and other information processing phenomena. The emphasis is on deep theoretical understanding, detailed modeling, and quantitative experimentation directed at understanding the behavior of particular regulatory systems and/or elucidating general principles of cellular information processing. The seminar series has the same scientific and educational goals as the q-bio Conference and Summer School. CNLS also sponsors a monthly series of q-bio public lectures, which are aimed at disseminating biological knowledge gained through quantitative experimentation and mathematical, computational, and/or statistical analyses of data.

Logistics

• Time: Tuesday, 2:15-3:15 PM, starting September 2, 2008. Speakers will be at LANL all of Tuesday and the preceding Monday or following Wednesday.
• Place: CNLS Conference Room, Building 1690, TA-3, Los Alamos National Laboratory

Schedule

• Past Seminars
• Winter 2009-2010

  Jan 26: Graham Mackay, University of Melbourne, Expression and Function of Antibody Fc Receptors on Human Airway Smooth Muscle Cells

  Feb 2: TBA

  Feb 9: TBA

  Feb 16: no seminar because of federal holiday on 01/15

  Feb 23: TBA

  Mar 2: Eric Klavins, University of Washington

  Mar 9: Jin Yang, Chinese Academy of Sciences-Max Planck Society Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences

  Mar 16: TBA

  Mar 23: Linda Petzold, University of California, Santa Barbara

  Mar 30: TBA

• Future Seminars

Organizers

• S. "Gnana" Gnanakaran, Los Alamos National Laboratory
• William S. Hlavacek, Los Alamos National Laboratory
• Yi Jiang, Los Alamos National Laboratory
• Brian Munsky, Los Alamos National Laboratory
• Janet M. Oliver, University of New Mexico
• Bridget S. Wilson, University of New Mexico
• Anton Zilman, Los Alamos National Laboratory

Sponsor

• Center for Nonlinear Studies (CNLS)