Statistical Framework for Uncertainty Quantification in Computational Molecular Modeling.

ABSTRACT: As computational modeling, simulation, and predictions are becoming integral parts of biomedical pipelines, it behooves us to emphasize the reliability of the computational protocol. For any reported quantity of interest (QOI), one must also compute and report a measure of the uncertainty or error associated with the QOI. This is especially important in molecular modeling, since in most practical applications the inputs to the computational protocol are often noisy, incomplete, or low-resolution. Unfortunately, currently available modeling tools do not account for uncertainties and their effect on the final QOIs with sufficient rigor. We have developed a statistical framework that expresses the uncertainty of the QOI as the probability that the reported value deviates from the true value b

SUBMITTER: Rasheed M 

PROVIDER: S-EPMC6857703 | biostudies-literature | 2019 Jul-Aug

REPOSITORIES: biostudies-literature