Om Prakash

The paper investigates the impact of immunomodulatory and antimicrobial molecules on blood lipid profiles to explore their potential for early cancer detection.

This paper introduces a new algorithm, NCT, to identify gene signatures for early cancer detection using RNA-seq data from TCGA and GTEx, showing improved classification performance.

The paper compares invasion performance across 64 cell lines using ANN models based on gene expression data to identify biologically relevant clusters for drug repositioning and targeting.

The paper establishes a protocol for clustering non-unified protein sequences using memory-map guided deep learning, validated on human hormonal system disease-related genes.

The paper hypothesizes, develops, and implements an algorithm to derive a universal indicative rule for biomolecule activity and selectivity based on 3D structure analysis.

This paper introduces an algorithm that identifies co-expression of bio-strings from protein sequences and validates results using existing databases.

The paper introduces an algorithm to extract sub-structures from co-crystallized ligands to identify selective binding regions for protein targets.