The role of data imbalance bias in the prediction of protein stability change upon mutation.

ABSTRACT: There is a controversy over what causes the low robustness of some programs for predicting protein stability change upon mutation. Some researchers suggested that low-quality data and insufficiently informative features are the primary reasons, while others attributed the problem largely to a bias caused by data imbalance as there are more destabilizing mutations than stabilizing ones. In this study, a simple approach was developed to construct a balanced dataset that was then conjugated with a leave-one-protein-out approach to illustrate that the bias may not be the primary reason for poor performance. A balanced dataset with some seemly good conventional n-fold CV results should not be used as a proof that a model for predicting protein stability change upon mutations is robust. Thus, so

SUBMITTER: Fang J 

PROVIDER: S-EPMC10062539 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature