Author

E. M.

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Open access Oct 2026

K-Medoids guided cell reduction and Node2Vec based complementary graph fusion for gene regulatory network inference from single-cell expression data

Gene regulatory network (GRN) inference from single-cell gene expression data remains challenging because such datasets are often noisy, sparse, and computationally large. Moreover, different inference algorithms may recover different regulatory edges. To address these challenges, this study proposes a two-stage framew...

E. M., A. S. Jereesh, G. S. Kumar · Discover Computing · 0 citations

Open access Jul 2026

CoReGRN: a context-aware post-processing framework for gene regulatory network inference revealing regulatory signatures in HIV-Leishmaniasis.

CoReGRN (Contextual Refinement of Gene Regulatory Networks), a nonparametric, context-aware post-processing framework that refines inferred GRNs by reweighting candidate regulatory interactions using Mutual Information based association strength and local network context, is proposed.

E. M., Jereesh A. S., G. S. Kumar · BMC Genomics · 0 citations