MUMBAI, India, Jan. 23 -- Intellectual Property India has published a patent application (202511093770 A) filed by Deen Dayal Upadhyaya Gorakhpur University, Gorakhpur, Uttar Pradesh, on Sept. 30, 2025, for 'a computer-implemented method and system for machine learning-guided selection of candidate genes for stress tolerance in finger millet.'
Inventor(s) include Dr. Varsha Rani; and Prof. Dinesh Yadav.
The application for the patent was published on Jan. 23, under issue no. 04/2026.
According to the abstract released by the Intellectual Property India: "The present invention relates to a computer-implemented method and system for machine learning-guided selection of candidate genes for stress tolerance in finger millet (Eleusine coracana). The method receives finger millet specific multi-omics and phenotype data, preprocesses and engineers gene-level features, trains or applies machine learning models and computes explainability-based importance values. Network propagation and motif/conservation analyses are integrated with model outputs to compute composite ranking scores. A selection logic applies configurable thresholds and concordance rules to yield a prioritized list of candidate genes with confidence scores and suggested experimental validation designs. The pipeline improves candidate prioritization for downstream breeding and molecular validation."
Disclaimer: Curated by HT Syndication.
