Zeeshan Ahmed

Translational bioinformatics and machine learning framework for biomarker discovery, disease prediction, and patient profiling for precision medicine

Hepatic Ketogenesis Attenuates Cardiac Hypertrophy via Metabolic Reprogramming

This study shows that hepatic ketogenesis reduces cardiac hypertrophy in HFpEF by maintaining beta-hydroxybutyrate levels, which modulate myocardial metabolism.

3D IntelliGenes: AI/ML application using multi-omics data for biomarker discovery and disease prediction with multi-dimensional visualization

This paper introduces 3D IntelliGenes, a tool for visualizing AI/ML results on multi-omics data to discover biomarkers and predict diseases through 3D clustering and feature analysis.

VAREANT: a bioinformatics application for gene variant reduction and annotation

VAREANT is a bioinformatics tool that simplifies variant data preprocessing, annotation, and AI/ML preparation for genomic analysis.

Multimodal AI/ML for discovering novel biomarkers and predicting disease using multi-omics profiles of patients with cardiovascular diseases

The paper develops a multimodal AI/ML framework to identify biomarkers and predict cardiovascular disease using multi-omics data, finding a 27-component signature with high predictive accuracy.

Discovering biomarkers associated and predicting cardiovascular disease with high accuracy using a novel nexus of machine learning techniques for precision medicine

This study identifies 18 significant transcriptomic biomarkers for cardiovascular disease with 96% accuracy using a combination of statistical tests and machine learning classifiers.

Investigating variant and expression of CVD genes associated phenotypes among high-risk Heart Failure patients

The paper integrates gene expression, genetic variants, and clinical data from high-risk Heart Failure patients to identify differentially expressed genes and functionally relevant mutations associated with CVD.

Integrated ACMG approved genes and ICD codes for the translational research and precision medicine

The paper develops a gene-disease-code database linking ICD codes with ACMG-approved genes to support genomic and clinical data integration for precision medicine.

IntelliEppi: Intelligent reaction monitoring and holistic data management system for the molecular biology lab