Author

Zainab A. Ayinla

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#protein folding Review Open access Oct 2026

Artificial intelligence detects the dismantling of nutrient co-occurrence architecture by ultra-processing: explainable machine learning and network analysis of 22,481 usda-classified foods

UPFNet is constructed, an artificial-intelligence framework that couples nutrient co-occurrence network analysis with explainable machine learning across 22,481 foods from two USDA composition databases spanning 788,582 measurements across 33 nutrients, with NOVA group assignment via a validated 67-term keyword algorit...

O. Agboola, Z. Ayinla, Samuel S. Agboola et al. · International Journal of Foo... · 0 citations

Aug 2026

Activity cliffs resist prediction within and across protein kinases: a leakage-controlled machine-learning analysis of structure-potency discontinuities.

Activity cliffs, that is pairs of closely related molecules with large potency differences, limit the reliability of structure-activity models, and inferences about target specificity are highly sensitive to how within-target validation is grouped.

Samuel S. Agboola, O. Agboola, O. Olasehinde et al. · Bioorganic chemistry (Print) · 1 citation