Open Problems in Mathematical Biology
Sean T. Vittadello, Michael P.H. Stumpf
Biology is data-rich, and it is equally rich in concepts and hypotheses. Part of trying to understand biological processes and systems is therefore to confront our ideas and hypotheses with data using statistical methods to determine the extent to which our hypotheses agree with reality. But doing so in a systematic way is becoming increasingly challenging as our hypotheses become more detailed, and our data becomes more complex. Mathematical methods are therefore gaining in importance across the life- and biomedical sciences. Mathematical models allow us to test our understanding, make testable predictions about future behaviour, and gain insights into how we can control the behaviour of biological systems. It has been argued that mathematical methods can be of great benefit to biologists to make sense of data. But mathematics and mathematicians are set to benefit equally from considering the often bewildering complexity inherent to living systems. Here we present a small selection of open problems and challenges in mathematical biology. We have chosen these open problems because they are of both biological and mathematical interest.
Comments: 31 pages, 2 figures, 115 references
Subjects: Quantitative Methods (q-bio.QM); Biological Physics (physics.bio-ph)
Cite as: arXiv:2206.09516 [q-bio.QM]
(or arXiv:2206.09516v1 [q-bio.QM] for this version)
https://doi.org/10.48550/arXiv.2206.09516
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Submission history
From: Michael Stumpf [view email]
[v1] Mon, 20 Jun 2022 00:31:27 UTC (1,210 KB)
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