Souvik Chakraborty

This study identifies potential dopamine receptor D2 antagonists from Rauwolfia serpentina using in-silico virtual screening and ADMET analysis.

The paper identifies hub genes and pathways associated with multiple sclerosis using blood-based gene and miRNA profiles from public datasets.

This study identifies 15 key genes and 37 FDA-approved drugs potentially relevant to Multiple sclerosis, Schizophrenia, and Autism using bioinformatics tools and drug-gene interaction analysis.

The paper identifies common differentially expressed genes and hub genes between glioblastoma and Parkinson's disease using microarray data and bioinformatics tools.

The paper identifies common differentially expressed genes across neurodegenerative disorders and suggests they may serve as potential biomarkers.

The paper identifies common genes and proteins across Alzheimer's Disease, Multiple Sclerosis, and Duchenne Muscular Dystrophy using in-silico analysis of gene expression data.

This study identifies potential proteins and microRNAs associated with Multiple Sclerosis and Huntington's disease using in silico analysis of microarray data.

This study identifies differentially expressed genes and hub genes in Huntington's disease using gene expression analysis and network analysis, but finds no consistent biomarker across datasets.