Why model?

dc.contributor.authorWolkenhauer, Olafen_ZA
dc.identifier.citationWolkenhauer, O. 2014. Why model? Frontiers in Physiology, 5:21. doi: 10.3389/fphys.2014.00021.
dc.identifier.issn1664-042X (online)
dc.identifier.otherdoi: 10.3389/fphys.2014.00021
dc.descriptionCITATION: Wolkenhauer, O. 2014. Why model? Frontiers in Physiology, 5:21. doi: 10.3389/fphys.2014.00021.
dc.descriptionThe original publication is available at
dc.description.abstractNext generation sequencing technologies are bringing about a renaissance of mining approaches. A comprehensive picture of the genetic landscape of an individual patient will be useful, for example, to identify groups of patients that do or do not respond to certain therapies. The high expectations may however not be satisfied if the number of patient groups with similar characteristics is going to be very large. I therefore doubt that mining sequence data will give us an understanding of why and when therapies work. For understanding the mechanisms underlying diseases, an alternative approach is to model small networks in quantitative mechanistic detail, to elucidate the role of gene and proteins in dynamically changing the functioning of cells. Here an obvious critique is that these models consider too few components, compared to what might be relevant for any particular cell function. I show here that mining approaches and dynamical systems theory are two ends of a spectrum of methodologies to choose from. Drawing upon personal experience in numerous interdisciplinary collaborations, I provide guidance on how to model by discussing the question “Why model?”en_ZA
dc.format.extent5 pages
dc.publisherFrontiers Media
dc.subjectSystems biologyen_ZA
dc.subjectSystems medicineen_ZA
dc.subjectMathematical modelingen_ZA
dc.subjectCell biologyen_ZA
dc.subjectIntervening sequences (Genetics)en_ZA
dc.subjectSequential pattern miningen_ZA
dc.titleWhy model?en_ZA
dc.description.versionPublisher's version
dc.rights.holderAuthor retains copyright

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