BICePs - Bayesian Inference of Conformational Populations
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:
-
NMR chemical shifts (
HA,NH,CAandN). -
J couplings (both small molecules and amino acids) (
J). -
Hydrogen--deuterium exchange (
HDX).
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
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.
Metadata
Release files for biceps 2.0.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| biceps-2.0.0.tar.gz | 51.4 kB | Without provenance | Details for biceps-2.0.0.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| biceps-2.0.0-py3-none-any.whl | Python 3 | none | any | Details for biceps-2.0.0-py3-none-any.whl |
Total release size: 103.9 kB
Release files / biceps-2.0.0.tar.gz
| Download URL | biceps-2.0.0.tar.gz |
|---|---|
| Size | 51.4 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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|
|
BLAKE2b-256 checksum How to use checksums |
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|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.8.13
|
Release files / biceps-2.0.0-py3-none-any.whl
| Download URL | biceps-2.0.0-py3-none-any.whl |
|---|---|
| Size | 52.5 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
63713300433128e3a7b7a03d0583b3848d5736e34ee353c7344bc3ce8fa371a5
|
|
BLAKE2b-256 checksum How to use checksums |
305210b61ea3eee8e4b881615a54b3dda49a44165579e0be45b99b20b6728e83
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.8.13
|
Security for biceps 2.0.0
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No provenance found
None of the files in this release were uploaded with provenance metadata.
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