ssbio: a Python framework for structural systems biology Article Swipe
Nathan Mih
,
Elizabeth Brunk
,
Ke Chen
,
Edward Catoiu
,
Anand V. Sastry
,
Erol Kavvas
,
Jonathan M. Monk
,
Zhen Zhang
,
Bernhard Ø. Palsson
·
YOU?
·
· 2018
· Open Access
·
· DOI: https://doi.org/10.1093/bioinformatics/bty077
YOU?
·
· 2018
· Open Access
·
· DOI: https://doi.org/10.1093/bioinformatics/bty077
Summary Working with protein structures at the genome-scale has been challenging in a variety of ways. Here, we present ssbio, a Python package that provides a framework to easily work with structural information in the context of genome-scale network reconstructions, which can contain thousands of individual proteins. The ssbio package provides an automated pipeline to construct high quality genome-scale models with protein structures (GEM-PROs), wrappers to popular third-party programs to compute associated protein properties, and methods to visualize and annotate structures directly in Jupyter notebooks, thus lowering the barrier of linking 3D structural data with established systems workflows. Availability and implementation ssbio is implemented in Python and available to download under the MIT license at http://github.com/SBRG/ssbio. Documentation and Jupyter notebook tutorials are available at http://ssbio.readthedocs.io/en/latest/. Interactive notebooks can be launched using Binder at https://mybinder.org/v2/gh/SBRG/ssbio/master?filepath=Binder.ipynb. Supplementary information Supplementary data are available at Bioinformatics online.
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- Language
- en
- Landing Page
- https://doi.org/10.1093/bioinformatics/bty077
- https://academic.oup.com/bioinformatics/article-pdf/34/12/2155/29153549/bty077.pdf
- OA Status
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- Cited By
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- References
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- Related Works
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- OpenAlex ID
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All OpenAlex metadata
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https://doi.org/10.1093/bioinformatics/bty077Digital Object Identifier
- Title
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ssbio: a Python framework for structural systems biologyWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2018Year of publication
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2018-02-09Full publication date if available
- Authors
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Nathan Mih, Elizabeth Brunk, Ke Chen, Edward Catoiu, Anand V. Sastry, Erol Kavvas, Jonathan M. Monk, Zhen Zhang, Bernhard Ø. PalssonList of authors in order
- Landing page
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https://doi.org/10.1093/bioinformatics/bty077Publisher landing page
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https://academic.oup.com/bioinformatics/article-pdf/34/12/2155/29153549/bty077.pdfDirect link to full text PDF
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YesWhether a free full text is available
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bronzeOpen access status per OpenAlex
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https://academic.oup.com/bioinformatics/article-pdf/34/12/2155/29153549/bty077.pdfDirect OA link when available
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44Total citation count in OpenAlex
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2025: 3, 2024: 7, 2023: 3, 2022: 4, 2021: 8Per-year citation counts (last 5 years)
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30Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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