HIGHLIGHTS
- who: January and colleagues from the University of California, San Diego, United States have published the article: Big Data analytics for improved prediction of ligand binding and conformational selection, in the Journal: (JOURNAL)
- what: In the prior work (Akondi et_al, 2019; Gupta et_al, 2022; Sripriya Akondi et_al, 2022), a novel two-stage sampling-based classifier framework was proposed with the primary goal of addressing the class imbalance problem and maximizing the detection of potential binding protein conformations as conventional machine_learning (ML) algorithms are ill-equipped to deal with the issue of class imbalance during the . . .
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