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Biomolecular Crystallographic Computing with Jupyter

Blaine H. M. Mooers
Department of Biochemistry and Molecular Biology, University of Oklahoma Health Sciences Center, Oklahoma City, OK 97104
Stephenson Cancer Center, University of Oklahoma Health Sciences Center, Oklahoma City, OK 97104
Laboratory of Biomolecular Structure and Function, University of Oklahoma Health Sciences Center, Oklahoma City, OK 97104
Biomolecular Structure Core, Oklahoma COBRE in Structural Biology, University of Oklahoma Health Sciences Center, Oklahoma City, OK 97104

Abstract

The ease of use of Jupyter notebooks has helped biologists enter scientific computing, especially in protein crystallography, where a collaborative community develops extensive libraries, user-friendly GUIs, and Python APIs. The APIs allow users to use the libraries in Jupyter. To further advance this use of Jupyter, we developed a collection of code fragments that use the vast Computational Crystallography Toolbox (cctbx) library for novel analyses. We made versions of this library for use in JupyterLab and Colab. We also made versions of the snippet library for the text editors VS Code, Vim, and Emacs that support editing live code cells in Jupyter notebooks via the GhostText web browser extension. Readers of this paper may be inspired to adapt this latter capability to their domains of science.

Keywords

literate programming, reproducible research, scientific rigor, electronic notebooks, JupyterLab, Jupyter notebooks, Colab notebook, OnDemand notebooks, computational structural biology, computational crystallography, biomolecular crystallography, protein crystallography, biomolecular structure, computational molecular biophysics, biomedical research, data visualization, scientific communication, GhostText, text editors, snippet libraries, SciPy software stack, interactive software development

DOI

10.25080/gerudo-f2bc6f59-004

Bibtex entry

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