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Computational Modeling Under Uncertainty: Challenges and Opportunities

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Uncertainty in Biology

Part of the book series: Studies in Mechanobiology, Tissue Engineering and Biomaterials ((SMTEB,volume 17))

Abstract

Computational Biology has increasingly become an important tool for biomedical and translational research. In particular, when generating novel hypothesis despite fundamental uncertainties in data and mechanistic understanding of biological processes underpinning diseases. While in the present book, we have reviewed the necessary background and existing novel methodologies that set the basis for dealing with uncertainty, there are still many “grey”, or less well-defined, areas of investigations offering both challenges and opportunities. This final chapter in the book provides some reflections on those areas, namely: (1) the need for novel robust mathematical and statistical methodologies to generate hypothesis under uncertainty; (2) the challenge of aligning those methodologies in a context that requires larger computational resources; (3) the accessibility of modeling tools for less mathematical literate researchers; and (4) the integration of models with—omics data and its application in clinical environments.

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Notes

  1. 1.

    http://www.digital-patient.net/files/DP-Roadmap_FINAL_N.pdf.

  2. 2.

    http://cordis.europa.eu/fp7/ict/e-infrastructure/docs/bms-agenda.pdf.

  3. 3.

    https://ec.europa.eu/digital-agenda/en/pillar-v-research-and-innovation/action-53-financially-support-joint-ict-research-infrastructures.

  4. 4.

    http://cordis.europa.eu/fp7/ict/e-infrastructure/docs/bms-presa-6.pdf.

  5. 5.

    http://www.scilogs.com/scientific_and_medical_libraries/what-is-e-science-and-how-should-it-be-managed/.

  6. 6.

    http://meetings.cshl.edu/courses/2014/c-comp14.shtml.

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Author information

Authors and Affiliations

  1. Unit of Computational Medicine, Department of Medicine, Karolinska Institutet, Solna, Sweden

    David Gomez-Cabrero & Jesper Tegnér

  2. Center for Molecular Medicine, Stockholm, Sweden

    David Gomez-Cabrero & Jesper Tegnér

  3. Biomechanics Research Unit, University of Liège, Chemin des Chevreuils 1 B52/3, 4000, Liège, Belgium

    Liesbet Geris

  4. Prometheus, Division of Skeletal Tissue Engineering Leuven, KU Leuven, Herestraat 49, Box 813, 3000, Leuven, Belgium

    Liesbet Geris

  5. Biomechanics Section, KU Leuven, Celestijnenlaan 300 C, Box 2419, 3001, Leuven, Belgium

    Liesbet Geris

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  1. David Gomez-Cabrero
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  2. Jesper Tegnér
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Correspondence to David Gomez-Cabrero .

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Editors and Affiliations

  1. Biomechanics Research Unit, University of Liège, Liège 1, Belgium

    Liesbet Geris

  2. Center for Molecular Medicine, Karolinska University Hospital, Stockholm, Sweden

    David Gomez-Cabrero

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Gomez-Cabrero, D., Tegnér, J., Geris, L. (2016). Computational Modeling Under Uncertainty: Challenges and Opportunities. In: Geris, L., Gomez-Cabrero, D. (eds) Uncertainty in Biology. Studies in Mechanobiology, Tissue Engineering and Biomaterials, vol 17. Springer, Cham. https://doi.org/10.1007/978-3-319-21296-8_18

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