ssbio: A Framework for Structural Systems Biology


This Python package provides a collection of tools for people with questions in the realm of structural systems biology. The main goals of this package are to:

  1. Provide an easy way to map genes to their encoded proteins sequences and structures
  2. Directly link structures to genome-scale SBML models
  3. Prepare structures for downstream analyses, such as their use in molecular modeling software
  4. Demonstrate fully-featured Python scientific analysis environments in Jupyter notebooks

Example questions you can (start to) answer with this package:

  • How can I determine the number of protein structures available for my list of genes?
  • What is the best, representative structure for my protein?
  • Where, in a metabolic network, do these proteins work?
  • Where do popular mutations show up on a protein?
  • How can I compare the structural features of entire proteomes?
  • How can I zoom in and visualize the interactions happening in the cell at the molecular level?
  • How do structural properties correlate with my experimental datasets?
  • How can I improve the contents of my model with structural data?
  • and more…


First install NGLview using pip:

pip install nglview

Then install ssbio:

pip install ssbio


pip install ssbio --upgrade


pip uninstall ssbio


See: Software Installations for additional programs to install. Most of these additional programs are used to predict or calculate properties of proteins.


Check out some Jupyter notebook tutorials at The Protein Class and The GEM-PRO Pipeline.


The manuscript for the ssbio package can be found and cited at [1].

[1]Mih, N. et al. ssbio: A Python Framework for Structural Systems Biology. bioRxiv 165506 (2017). doi:10.1101/165506