ssbio: a Python framework for structural systems biology
Abstract 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 thou...
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| Published in: | Bioinformatics Vol. 34; no. 12; pp. 2155 - 2157 |
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| Main Authors: | , , , , , , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
England
Oxford University Press
15.06.2018
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| Subjects: | |
| ISSN: | 1367-4803, 1367-4811, 1460-2059, 1367-4811 |
| Online Access: | Get full text |
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| Abstract | Abstract
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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| AbstractList | 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.SummaryWorking 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.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.Availability and implementationssbio 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 data are available at Bioinformatics online.Supplementary informationSupplementary data are available at Bioinformatics online. 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. 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 data are available at Bioinformatics online. Abstract 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. |
| Author | Brunk, Elizabeth Palsson, Bernhard O Catoiu, Edward Kavvas, Erol Monk, Jonathan M Zhang, Zhen Sastry, Anand Mih, Nathan Chen, Ke |
| AuthorAffiliation | 1 Department of Bioengineering, Bioinformatics and Systems Biology Graduate Program 2 Department of Bioengineering, University of California, San Diego, CA, USA |
| AuthorAffiliation_xml | – name: 1 Department of Bioengineering, Bioinformatics and Systems Biology Graduate Program – name: 2 Department of Bioengineering, University of California, San Diego, CA, USA |
| Author_xml | – sequence: 1 givenname: Nathan orcidid: 0000-0002-4302-9052 surname: Mih fullname: Mih, Nathan email: nmih@ucsd.edu organization: Department of Bioengineering, Bioinformatics and Systems Biology Graduate Program – sequence: 2 givenname: Elizabeth surname: Brunk fullname: Brunk, Elizabeth organization: Department of Bioengineering, University of California, San Diego, CA, USA – sequence: 3 givenname: Ke surname: Chen fullname: Chen, Ke organization: Department of Bioengineering, University of California, San Diego, CA, USA – sequence: 4 givenname: Edward surname: Catoiu fullname: Catoiu, Edward organization: Department of Bioengineering, University of California, San Diego, CA, USA – sequence: 5 givenname: Anand surname: Sastry fullname: Sastry, Anand organization: Department of Bioengineering, University of California, San Diego, CA, USA – sequence: 6 givenname: Erol surname: Kavvas fullname: Kavvas, Erol organization: Department of Bioengineering, University of California, San Diego, CA, USA – sequence: 7 givenname: Jonathan M surname: Monk fullname: Monk, Jonathan M organization: Department of Bioengineering, University of California, San Diego, CA, USA – sequence: 8 givenname: Zhen surname: Zhang fullname: Zhang, Zhen organization: Department of Bioengineering, University of California, San Diego, CA, USA – sequence: 9 givenname: Bernhard O surname: Palsson fullname: Palsson, Bernhard O organization: Department of Bioengineering, University of California, San Diego, CA, USA |
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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... 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... |
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| SubjectTerms | Applications Notes Computational Biology - methods Models, Biological Protein Conformation Software |
| Title | ssbio: a Python framework for structural systems biology |
| URI | https://www.ncbi.nlm.nih.gov/pubmed/29444205 https://www.proquest.com/docview/2002485674 https://pubmed.ncbi.nlm.nih.gov/PMC6658713 |
| Volume | 34 |
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