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Computational disease modeling - fact or fiction?
Karolinska University Hospita.
Hospital Clinic Barcelona.
CNRS.
Northwestern University.
Show others and affiliations
2009 (English)In: BMC SYSTEMS BIOLOGY, ISSN 1752-0509, Vol. 3, no 56Article in journal (Refereed) Published
Abstract [en]

Background: Biomedical research is changing due to the rapid accumulation of experimental data at an unprecedented scale, revealing increasing degrees of complexity of biological processes. Life Sciences are facing a transition from a descriptive to a mechanistic approach that reveals principles of cells, cellular networks, organs, and their interactions across several spatial and temporal scales. There are two conceptual traditions in biological computational-modeling. The bottom-up approach emphasizes complex intracellular molecular models and is well represented within the systems biology community. On the other hand, the physics-inspired top-down modeling strategy identifies and selects features of (presumably) essential relevance to the phenomena of interest and combines available data in models of modest complexity. Results: The workshop, "ESF Exploratory Workshop on Computational disease Modeling", examined the challenges that computational modeling faces in contributing to the understanding and treatment of complex multi-factorial diseases. Participants at the meeting agreed on two general conclusions. First, we identified the critical importance of developing analytical tools for dealing with model and parameter uncertainty. Second, the development of predictive hierarchical models spanning several scales beyond intracellular molecular networks was identified as a major objective. This contrasts with the current focus within the systems biology community on complex molecular modeling. Conclusion: During the workshop it became obvious that diverse scientific modeling cultures (from computational neuroscience, theory, data-driven machine-learning approaches, agent-based modeling, network modeling and stochastic-molecular simulations) would benefit from intense cross-talk on shared theoretical issues in order to make progress on clinically relevant problems.

Place, publisher, year, edition, pages
2009. Vol. 3, no 56
National Category
Medical and Health Sciences
Identifiers
URN: urn:nbn:se:liu:diva-19547DOI: 10.1186/1752-0509-3-56OAI: oai:DiVA.org:liu-19547DiVA: diva2:225921
Note
Original Publication: Jesper N Tegner, Albert Compte, Charles Auffray, Gary An, Gunnar Cedersund, Gilles Clermont, Boris Gutkin, Zoltan N Oltvai, Klaas Enno Stephan, Randy Thomas and Pablo Villoslada, Computational disease modeling - fact or fiction?, 2009, BMC SYSTEMS BIOLOGY, (3), 56, . http://dx.doi.org/10.1186/1752-0509-3-56 Licensed by: BioMed Central http://www.biomedcentral.com/ Available from: 2009-07-03 Created: 2009-06-26 Last updated: 2009-07-03Bibliographically approved

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