2018

• Hiranmayi Duvvuri, Lucas C. Wheeler, and Michael J. Harms. Pytc: open-source python software for global analyses of isothermal titration calorimetry data. Biochemistry, 57(18):2578–2583, 2018. PMID: 29620867. URL: https://doi.org/10.1021/acs.biochem.7b01264, arXiv:https://doi.org/10.1021/acs.biochem.7b01264, doi:10.1021/acs.biochem.7b01264.
  [abstract▼] [BibTeX▼]

  Here we describe pytc, an open-source Python package for global fits of thermodynamic models to multiple isothermal titration calorimetry experiments. Key features include simplicity, the ability to implement new thermodynamic models, a robust maximum likelihood fitter, a fast Bayesian Markov-Chain Monte Carlo sampler, rigorous implementation, extensive documentation, and full cross-platform compatibility. pytc fitting can be done using an application program interface or via a graphical user interface. It is available for download at https://github.com/harmslab/pytc.

  @article{doi:10.1021/acs.biochem.7b01264,
      author = "Duvvuri, Hiranmayi and Wheeler, Lucas C. and Harms, Michael J.",
      title = "pytc: Open-Source Python Software for Global Analyses of Isothermal Titration Calorimetry Data",
      journal = "Biochemistry",
      volume = "57",
      number = "18",
      pages = "2578-2583",
      year = "2018",
      doi = "10.1021/acs.biochem.7b01264",
      note = "PMID: 29620867",
      URL = "https://doi.org/10.1021/acs.biochem.7b01264",
      eprint = "https://doi.org/10.1021/acs.biochem.7b01264"
  }