ArticleInternational journal of molecular sciences2025
Multiscale Interactome-Guided Discovery Candidate Herbs and Active Ingredients Against Hyperthyroidism by Biased Random Walk Algorithm.
Article in International journal of molecular sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Hyperthyroidism features excess thyroid hormone and a hypermetabolic state; although drugs and definitive therapies exist, mechanism-anchored options are still needed. We built a multiscale interactome and applied a biased random-walk diffusion model to prioritize herbal candidates, active ingredients, and mechanisms. Herb-compound records came from OASIS; targets from DrugBank, TTD, and STITCH; and disease genes from DisGeNET. For each herb and compound, we simulated diffusion profiles, computed the correlation with the hyperthyroidism profile, and assessed target overlap ratio. Herbs were ranked by correlation and
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