BIASD: Bayesian Inference for the Analysis of Sub-temporal-resolution Data

Quick start

Install straight from Github:

pip install git+https://github.com/ckinzthompson/biasd.git

Try running a speed test:

import biasd as b
b.likelihood.use_python_ll()
t,y = b.likelihood.test_speed(10,1000)

Documentation

See the documentation or open Documentation.html for more information.

Manuscripts

Original Paper

• Kinz-Thompson, CD, Gonzalez Jr., RL 2018. Increasing the time resolution of single-molecule experiments with Bayesian inference. Biophysical Journal. 114(2), 289-300. (Biophysical Journal), (Pubmed), (bioRxiv).

Applications

• Ray, K., Kinz-Thompson, C.D., Fei, J., Wang, B., Lin, Q. and Gonzalez Jr., R.L. 2023. Entropic control of the free-energy landscape of an archetypal biomolecular machine. Proc. Natl. Acad. Sci. U.S.A. 120:e2220591120. (PNAS), (Pubmed), (bioRxiv).

Development (Testing)

pip install -e ".[test]"
pytest

Updates

• Version 0.2.2 (October 2024): Adds speciality modes, updates prior collections.
• Version 0.2.1 (October 2024): Bug fixes likelihood switches, adds titration.
• Version 0.2 (July 2024): Updates fix broken libraries and improve clarity.
• Version 0.1 (2017): Original used in paper