Literature DB >> 34262852

The Spectrum of Mechanism-Oriented Models and Methods for Explanations of Biological Phenomena.

C Anthony Hunt1, Ahmet Erdemir2, William W Lytton3, Feilim Mac Gabhann4, Edward A Sander5, Mark K Transtrum6, Lealem Mulugeta7.   

Abstract

Developing and improving mechanism-oriented computational models to better explain biological phenomena is a dynamic and expanding frontier. As the complexity of targeted phenomena has increased, so too has the diversity in methods and terminologies, often at the expense of clarity, which can make reproduction challenging, even problematic. To encourage improved semantic and methodological clarity, we describe the spectrum of Mechanism-oriented Models being used to develop explanations of biological phenomena. We cluster explanations of phenomena into three broad groups. We then expand them into seven workflow-related model types having distinguishable features. We name each type and illustrate with examples drawn from the literature. These model types may contribute to the foundation of an ontology of mechanism-based biomedical simulation research. We show that the different model types manifest and exert their scientific usefulness by enhancing and extending different forms and degrees of explanation. The process starts with knowledge about the phenomenon and continues with explanatory and mathematical descriptions. Those descriptions are transformed into software and used to perform experimental explorations by running and examining simulation output. The credibility of inferences is thus linked to having easy access to the scientific and technical provenance from each workflow stage.

Entities:  

Keywords:  computational model; explanatory model; hybrid model; mechanism; mechanistic model; modeling methods; provenance; simulation; systems modeling; workflow

Year:  2018        PMID: 34262852      PMCID: PMC8277120          DOI: 10.3390/pr6050056

Source DB:  PubMed          Journal:  Processes (Basel)        ISSN: 2227-9717            Impact factor:   2.847


  2 in total

1.  Utilizing virtual experiments to increase understanding of discrepancies involving in vitro-to-in vivo predictions of hepatic clearance.

Authors:  Preethi Krishnan; Andrew K Smith; Glen E P Ropella; Lopamudra Dutta; Ryan C Kennedy; C Anthony Hunt
Journal:  PLoS One       Date:  2022-07-22       Impact factor: 3.752

Review 2.  Development of and insights from systems pharmacology models of antibody-drug conjugates.

Authors:  Inez Lam; Venkatesh Pilla Reddy; Kathryn Ball; Rosalinda H Arends; Feilim Mac Gabhann
Journal:  CPT Pharmacometrics Syst Pharmacol       Date:  2022-07-03
  2 in total

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