{"categories":[{"label":"Scientific/Engineering","url":"https://skillfed.io/packages/category/scientific-engineering/7"}],"enrichment":{"capability":"pymbar implements the multistate Bennett acceptance ratio (MBAR) method to estimate free energy differences and expectation values from equilibrium samples across multiple thermodynamic states.","skillfed_tags":["molecular-dynamics","free-energy","statistical-analysis"],"use_cases":["Computing free energy differences between ligand-bound and unbound protein states in drug discovery","Analyzing alchemical transformation simulations to estimate binding affinities","Estimating thermodynamic properties and their uncertainties from parallel tempering or replica exchange simulations","Extracting equilibrium averages and covariance information from multi-state sampling experiments","Validating molecular simulation convergence by computing free energy estimates across different equilibration lengths"],"what_it_does":"pymbar is a Python library that implements the multistate Bennett acceptance ratio method, a statistical technique for analyzing molecular simulation data. It takes reduced potential matrices from equilibrium samples across multiple thermodynamic states and computes free energy differences between those states along with their uncertainties. The package also estimates expectation values for observables across all states, providing covariance matrices for error propagation.\n\nThe library is designed for computational chemistry and molecular dynamics workflows. It accepts reduced potential data (typically from molecular simulations), initializes an MBAR object, and provides methods to compute free energy differences and expectations with associated standard errors. It depends on numpy, scipy, and numexpr for numerical computation, and optionally uses JAX for acceleration if available.","worth_installing":"Yes, if you work with molecular simulations and need to analyze multi-state equilibrium data. The package is stable, has no known vulnerabilities, installs easily, and is widely used in computational chemistry. The aging maintenance status (876 days since release) is not a blocker\u2014the last commit is recent and the core algorithm is mature\u2014but verify that it meets your specific simulation software's version requirements before committing to a large analysis pipeline."},"id":"pymbar","links":{"html":"https://skillfed.io/packages/pymbar","md":"https://skillfed.io/packages/pymbar.md","pypi":"https://pypi.org/project/pymbar/"},"maintenance":{"status":"aging"},"meta":{"latest_release":"2024-03-21","license_spdx":null,"license_treatment":"permissive","name":"pymbar","python_support":"supports_current","summary":"Python implementation of the multistate Bennett acceptance ratio (MBAR) method"},"popularity":{"monthly_downloads":125476,"position":11814,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"4.0.3"}