Skip to main content
Python Software Foundation 20th Year Anniversary Fundraiser  Donate today!

BICePs

Project description

BICePs - Bayesian Inference of Conformational Populations

Documentation Status

The BICePs algorithm (Bayesian Inference of Conformational Populations) is a statistically rigorous Bayesian inference method to reconcile theoretical predictions of conformational state populations with sparse and/or noisy experimental measurements and objectively compare different models. Supported experimental observables include:

Citation DOI for Citing BICePs

Check our BICePs website for more details!

Please check out the theory of BICePs to learn more.

Installation (in progress)

BICePs supports Python 2.7 (see tag v1.0) or Python 3.4+ (v2.0 or greater) on Mac, Linux, and Windows.

Dependencies of BICePs

  • pymbar == 3.0.2
  • mdtraj >= 1.5.0
  • matplotlib >= 2.1.2
  • numpy >= 1.14.0
  • multiprocessing (works with Python versions 3.0-3.7)

NOTE: for pymbar, try: $ pip install git+https://github.com/choderalab/pymbar.git@3.0.2


View the workflow of BICePs.

BICePs is research software. If you make use of BICePs in scientific publications, please cite it.

To get started, see biceps/releases for the latest version of BICePs.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Files for biceps, version 2.0b0.post0
Filename, size File type Python version Upload date Hashes
Filename, size biceps-2.0b0.post0-py3-none-any.whl (49.6 kB) File type Wheel Python version py3 Upload date Hashes View
Filename, size biceps-2.0b0.post0.tar.gz (40.9 kB) File type Source Python version None Upload date Hashes View

Supported by

AWS AWS Cloud computing Datadog Datadog Monitoring DigiCert DigiCert EV certificate Facebook / Instagram Facebook / Instagram PSF Sponsor Fastly Fastly CDN Google Google Object Storage and Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Salesforce Salesforce PSF Sponsor Sentry Sentry Error logging StatusPage StatusPage Status page