Abstract:

Computational systems biology complements experimental biology in
unique ways that are hoped to reveal insights and a depth of
understanding not achievable without systems approaches. A major
challenge of systems biology continues to be the determination of
parameter values for mathematical models. While some models can be
analyzed in symbolic form, these are few and far between, and the lack
of parameter values is a true obstacle for most computational analyses
of realistic biological phenomena. As a consequence, computational
modelers tend to take on a problem only if there is a relatively solid
database for parameter estimation. Interestingly, biologists very
often have very detailed mental models of the phenomenon they are
investigating and are not really interested in absolutely precise
numerical results, as long as they can test relevant,
semi-quantitative hypotheses. However, neither they nor their
modeling colleagues have the means of translating the mental models
into numerical mathematical structures that would allow advanced
diagnosis and testing. I will speculate in this presentation on a
possible way to bridge the cleft between mental and numerical models,
using modern methods from Biochemcial Systems Theory. The envisioned
technique is tentatively called “concept map modeling” and seems quite
reasonable, but I do not have proof yet that it will actually work in
real-world applications.

Date: 2007-Nov-29     Time: 17:00:00     Room: 336

For more information:

• svinga@kdbio.inesc-id.pt