HIGHLIGHTS
- who: . and collaborators from the Harvard Medical School, United States Qufu Normal University, China have published the paper: Geometric complement heterogeneous information and random forest for predicting lncRNA-disease associations, in the Journal: (JOURNAL)
- what: The authors proposed a geometric complement heterogeneous information and random forest-based approach for predicting LDAs (named GCHIRFLDA). The AUC and AUPR comparison with other LDA prediction models based on fivefold cross-validation and the case studies show that the model has better LDA prediction performance.
- how: The authors proposed a novel LDA prediction model based on geometric . . .
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