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Data Management in Computational Systems Biology: Exploring Standards, Tools, Databases, and Packaging Best Practices

Stanford, Natalie J. and Scharm, Martin and Dobson, Paul D. and Golebiewski, Martin and Hucka, Michael and Kothamachu, Varun B. and Nickerson, David and Owen, Stuart and Pahle, Jürgen and Wittig, Ulrike and Waltemath, Dagmar and Goble, Carole and Mendes, Pedro and Snoep, Jacky (2019) Data Management in Computational Systems Biology: Exploring Standards, Tools, Databases, and Packaging Best Practices. In: Yeast Systems Biology: Methods and Protocols. Methods in Molecular Biology. No.2049. Humana Press , New York, NY, pp. 285-314. ISBN 978-1-4939-9735-0. https://resolver.caltech.edu/CaltechAUTHORS:20191014-145835970

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Abstract

Computational systems biology involves integrating heterogeneous datasets in order to generate models. These models can assist with understanding and prediction of biological phenomena. Generating datasets and integrating them into models involves a wide range of scientific expertise. As a result these datasets are often collected by one set of researchers, and exchanged with others researchers for constructing the models. For this process to run smoothly the data and models must be FAIR—findable, accessible, interoperable, and reusable. In order for data and models to be FAIR they must be structured in consistent and predictable ways, and described sufficiently for other researchers to understand them. Furthermore, these data and models must be shared with other researchers, with appropriately controlled sharing permissions, before and after publication. In this chapter we explore the different data and model standards that assist with structuring, describing, and sharing. We also highlight the popular standards and sharing databases within computational systems biology.


Item Type:Book Section
Related URLs:
URLURL TypeDescription
https://doi.org/10.1007/978-1-4939-9736-7_17DOIArticle
ORCID:
AuthorORCID
Hucka, Michael0000-0001-9105-5960
Nickerson, David0000-0003-4667-9779
Waltemath, Dagmar0000-0002-5886-5563
Additional Information:© 2019 Springer Science+Business Media, LLC, part of Springer Nature. First Online 11 October 2019. Natalie J. Stanford and Martin Scharm share joint lead authorship.
Subject Keywords:Standards; Metadata; Databases; Data storage; Model storage; FAIR; Reproducible research
Series Name:Methods in Molecular Biology
Issue or Number:2049
Record Number:CaltechAUTHORS:20191014-145835970
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20191014-145835970
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:99263
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:14 Oct 2019 22:08
Last Modified:14 Oct 2019 22:08

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