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Mathematical modeling in systems biology

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Details

Original languageEnglish
Title of host publicationAdvances in Artificial Life, Evolutionary Computation, and Systems Chemistry - 11th Italian Workshop, WIVACE 2016, Revised Selected Papers
PublisherSpringer Verlag
Pages161-166
Number of pages6
ISBN (Print)9783319577104
DOIs
Publication statusPublished - 2017
Publication typeA4 Article in a conference publication
EventItalian Workshop on Artificial Life and Evolutionary Computation -
Duration: 1 Jan 2000 → …

Publication series

NameCommunications in Computer and Information Science
Volume708
ISSN (Print)1865-0929

Conference

ConferenceItalian Workshop on Artificial Life and Evolutionary Computation
Period1/01/00 → …

Abstract

In this opinion paper we describe how mathematical models can serve as the foundation for communication within multidisciplinary research teams by providing a useful joint context. First we consider the role of mathematical modeling in systems biology in the light of our experiences in cancer research and other biological disciplines in the realm of big data. We examine the methodologies of machine learning, observing the differences between the modeling approach and the black box approach. Next, we consider the role of mathematical models in natural sciences, observing three simultaneous goals: prediction, knowledge accumulation, and communication. Finally, we consider the differences of the pathway model and the attractor model in describing genetic networks, and explore the long-standing criticality hypothesis, discussing its value in multidisciplinary research.

ASJC Scopus subject areas

Keywords

  • Computational biology, Mathematical modeling, Systems biology

Publication forum classification

Field of science, Statistics Finland