Basavaraj Mallikarjunayya Vastrad

The paper identifies differentially expressed genes and pathways in Parkinson's disease using NGS data and analyzes their diagnostic potential through ROC curves.

This paper identifies hub genes, miRNAs, and TFs in Huntington's disease using NGS data and bioinformatics analysis, revealing potential molecular markers for diagnosis and treatment.

The paper identifies differentially expressed genes and signaling pathways in recurrent implantation failure using bioinformatics analysis of next-generation sequencing data.

This study identifies candidate biomarkers and signaling pathways in Alzheimer's disease using NGS data analysis, revealing key genes, miRNAs, and TFs involved in AD pathogenesis.

This study identifies differentially expressed genes in HCM, analyzes their regulatory networks, and predicts molecular docking and ADMET properties of phytoconstituents targeting dysregulated genes.

This study identifies key biomarkers for endometriosis using NGS data analysis, revealing 10 hub genes and potential miRNAs and TFs involved in the disease.

This study identifies key genes, miRNAs, and pathways in cardiac arrest using NGS data and bioinformatics analysis.

The paper identifies potential prognostic targets in acute kidney injury using bioinformatics analysis of NGS data from a GEO dataset.

This study identifies differentially expressed genes and hub genes in COPD using NGS data and bioinformatics analysis, suggesting potential biomarkers and molecular targets.

This study identifies novel biomarkers and pathways in multiple sclerosis using NGS data analysis and predicts potential therapeutic drugs.

This study identifies key genes and pathways in schizophrenia using bioinformatics and NGS data analysis of neural progenitor cells and neurons from healthy controls and schizophrenia patients.

The paper identifies differentially expressed genes and pathways in sepsis using NGS data, highlighting potential hub genes and regulatory elements involved in sepsis progression.

The paper identifies differentially expressed genes and enriched pathways in IBD using NGS data and bioinformatics tools, highlighting potential therapeutic targets.

The paper identifies novel prognostic targets in coronary artery disease using bioinformatics analysis of NGS data to find differentially expressed genes and hub genes.

This study identifies key genes and pathways in PCOS and its complications using NGS data and bioinformatics analysis.

The paper identifies differentially expressed genes and hub genes in cystic fibrosis using NGS data from GEO, revealing potential molecular targets and biomarkers.

This study identifies hub genes and key pathways in pediatric Crohn's disease using NGS data and bioinformatics analysis.

The paper identifies differentially expressed genes and hub genes in FSGS using NGS data and bioinformatics tools, suggesting potential molecular mechanisms and biomarkers.

This study identifies hub genes and biological pathways in bipolar disorder using NGS data and bioinformatics analysis, revealing potential biomarkers and therapeutic targets.

The paper uses NGS data to identify differentially expressed genes and pathways in T1DM, revealing potential hub genes involved in disease mechanisms.

This study analyzes NGS data to identify differentially expressed genes and hub genes associated with COVID-19 and its secondary complications, showing diagnostic potential.

The paper identifies differentially expressed genes in NAFLD using NGS data and suggests potential hub genes as diagnostic biomarkers.

The paper identifies differentially expressed genes and enriched pathways in COVID-19 infection and complications using bioinformatics analysis, highlighting potential diagnostic targets.

The paper identifies differentially expressed genes and hub genes in myocardial infarction using bioinformatics analysis of RNA-seq data from GEO database.

This study identifies key genes and pathways in T2DM using bioinformatics analysis of a gene expression dataset, highlighting potential therapeutic targets.

The paper identifies key genes and pathways in heart failure using bioinformatics analysis of NGS data from GEO, highlighting potential biomarkers and therapeutic targets.

This study identifies hub genes and potential drug targets for heart failure through bioinformatics analysis of gene expression data.