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Modelling steroidogenesis: a framework model to support hypothesis generation and testing across endocrine studies

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posted on 2025-05-08, 20:46 authored by Laura O'Hara, Peter J. O'Shaughnessy, Tom C. Freeman, Lee B. Smith
Objective: Steroid hormones are responsible for the control of a wide range of physiological processes such as development, growth, reproduction, metabolism, and aging. Because of the variety of enzymes, substrates and products that take part in steroidogenesis and the compartmentalisation of its constituent reactions, it is a complex process to visualise and document. One of the goals of systems biology is to quantitatively describe the behaviour of complex biological systems that involve the interaction of many components. This can be done by representing these interactions visually in a pathway model and then optionally constructing a mathematical model of the interactions. Results: We have used the modified Edinburgh Pathway Notation to construct a framework diagram describing human steroidogenic pathways, which will be of use to endocrinologists. To demonstrate further utility, we show how such models can be parameterised with empirical data within the software Graphia Professional, to recapitulate specific examples of steroid hormone production, and also to mimic gene knockout. These framework models support in silico hypothesis generation and testing with utility across endocrine endpoints, with significant potential to reduce costs, time and animal numbers, whilst informing the design of planned studies.

History

Journal title

BMC Research Notes

Volume

11

Article number

252

Publisher

BioMed Central

Language

  • en, English

College/Research Centre

Faculty of Science

School

School of Environmental and Life Sciences

Rights statement

© 2018 The Author(s). This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

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