Herb-disease association prediction model based on network consistency projection.

ABSTRACT: A growing number of biological and clinical reports indicate the usefulness of herbs in the treatment of complex human diseases, giving an essential supplement for modern medicine. Similar to drugs, the use of experimental validation to identify related diseases of given herbs is both expensive and time-consuming. Such validation is even more difficult because each herb always contains several components. It is alternative to design computational models to predict herb-disease associations (HDAs). Nevertheless, only a few computational models have been developed for HDA prediction. In this study, we make full use of several properties of herbs and diseases, which are collected in a public database HERB, to design a model named HDAPM-NCP for predicting HDAs. Based on these properties, six h

SUBMITTER: Chen L 

PROVIDER: S-EPMC11770172 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature