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Bayesian inference of conformational populations

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BICePs - Bayesian Inference of Conformational Populations

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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:

Installation

We recommend that you install biceps via pip:

    $ pip install BICePs

Some dependencies of BICePs

Documentation

https://biceps.readthedocs.io/en/latest/

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Bayesian inference of conformational populations

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