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Notions of similarity for computational biology models

View ORCID ProfileRon Henkel, View ORCID ProfileRobert Hoehndorf, View ORCID ProfileTim Kacprowski, View ORCID ProfileChristian Knüpfer, View ORCID ProfileWolfram Liebermeister, View ORCID ProfileDagmar Waltemath
doi: https://doi.org/10.1101/044818
Ron Henkel
Heidelberg Institute for Theoretical Studies, Heidelberg, Germany
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Robert Hoehndorf
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Tim Kacprowski
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Christian Knüpfer
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Wolfram Liebermeister
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Dagmar Waltemath
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Abstract

Computational models used in biology are rapidly increasing in complexity, size, and numbers. To build such large models, researchers need to rely on software tools for model retrieval, model combination, and version control. These tools need to be able to quantify the differences and similarities between computational models. However, depending on the specific application, the notion of “similarity” may greatly vary. A general notion of model similarity, applicable to various types of models, is still missing. Here, we introduce a general notion of quantitative model similarities, survey the use of existing model comparison methods in model building and management, and discuss potential applications of model comparison. To frame model comparison as a general problem, we describe a theoretical approach to defining and computing similarities based on different model aspects. Potentially relevant aspects of a model comprise its references to biological entities, network structure, mathematical equations and parameters, and dynamic behaviour. Future similarity measures could combine these model aspects in flexible, problem-specific ways in order to mimic users’ intuition about model similarity, and to support complex model searches in databases.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted March 21, 2016.
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Notions of similarity for computational biology models
Ron Henkel, Robert Hoehndorf, Tim Kacprowski, Christian Knüpfer, Wolfram Liebermeister, Dagmar Waltemath
bioRxiv 044818; doi: https://doi.org/10.1101/044818
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Notions of similarity for computational biology models
Ron Henkel, Robert Hoehndorf, Tim Kacprowski, Christian Knüpfer, Wolfram Liebermeister, Dagmar Waltemath
bioRxiv 044818; doi: https://doi.org/10.1101/044818

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