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ssbio: a Python framework for structural systems biology

2018; Oxford University Press; Volume: 34; Issue: 12 Linguagem: Inglês

10.1093/bioinformatics/bty077

1367-4811

Nathan Mih, Elizabeth Brunk, Ke Chen, Edward Catoiu, Anand V. Sastry, Erol Kavvas, Jonathan M. Monk, Zhen Zhang, Bernhard Ø. Palsson,

Protein Structure and Dynamics

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.