ArticleBioinformatics (Oxford, England)2023
IntelliGenes: a novel machine learning pipeline for biomarker discovery and predictive analysis using multi-genomic profiles.
Article in Bioinformatics (Oxford, England), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed, 160 citations in OpenAlex.
- Atopic Dermatitis Beyond the Skin Barrier: Precision Medicine Approaches to Immunological Profiling and Therapeutic Innovation.International journal of molecular sciences · 2026Review
- Diagnostic potential of neutrophil extracellular traps in ulcerative colitis: a gene-based predictive model.Molecular and cellular biochemistry · 2026Article
- Mutual learning for joint disease detection and severity prediction reveals multimodal pathogenesis for neurodegenerative disorders.Bioinformatics (Oxford, England) · 2026Article
- Explainable deep learning approaches and clinical insights for cancer biomarker identification.Frontiers in oncology · 2026Review
- Chronic β-Blockade and Systemic Homeostasis: Molecular Integration of Cardiorenal and Immune Pathways, a Narrative Review.Biomolecules · 2025Review
- The impact of artificial intelligence on biomarker discovery.Emerging topics in life sciences · 2025Article
- 3D IntelliGenes: AI/ML application using multi-omics data for biomarker discovery and disease prediction with multi-dimensional visualization.BMC medical research methodology · 2025Article
- Integrative transcriptomics and metabolomics reveal neuroendocrine-lipid crosstalk and adenosine signaling in broiler under heat stress.BMC genomics · 2025Article
- Advancing genome-based precision medicine: a review on machine learning applications for rare genetic disorders.Briefings in bioinformatics · 2025Review
- Artificial intelligence in the management of metabolic disorders: a comprehensive review.Journal of endocrinological investigation · 2025Review
- Integrating Genomics and Molecular Biology in Understanding Peritoneal Adhesion.Current issues in molecular biology · 2025Review
- MultiOmicsAgent: Guided Extreme Gradient-Boosted Decision Trees-Based Approaches for Biomarker-Candidate Discovery in Multiomics Data.Journal of proteome research · 2025Article
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- Crosstalk ofOncoTargets and therapy · 2025Article
- VAREANT: a bioinformatics application for gene variant reduction and annotation.Bioinformatics advances · 2025Article
- Machine Learning Approach and Bioinformatics Analysis Discovered Key Genomic Signatures for Hepatitis B Virus-Associated Hepatocyte Remodeling and Hepatocellular Carcinoma.Cancer informatics · 2025Review
- Applying AI/ML for Analyzing Gene Expression Patterns.Methods in molecular biology (Clifton, N.J.) · 2025Article
- Multimodal AI/ML for discovering novel biomarkers and predicting disease using multi-omics profiles of patients with cardiovascular diseases.Scientific reports · 2024Article
- Computational approaches to investigate the relationship between periodontitis and cardiovascular diseases for precision medicine.Human genomics · 2024Review
- Emerging Strategies in Drug Development and Clinical Care in the Era of Personalized and Precision Medicine.Pharmaceutics · 2024Article
Corrections and comments
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
Abstract
summaryIn this article, we present IntelliGenes, a novel machine learning (ML) pipeline for the multi-genomics exploration to discover biomarkers significant in disease prediction with high accuracy. IntelliGenes is based on a novel approach, which consists of nexus of conventional statistical techniques and cutting-edge ML algorithms using multi-genomic, clinical, and demographic data. IntelliGenes introduces a new metric, i.e. Intelligent Gene (I-Gene) score to measure the importance of individual biomarkers for prediction of complex traits. I-Gene scores can be utilized to generate I-Gene profiles of individuals to comprehend the intricacies of ML used in disease prediction. IntelliGenes is user-friendly, portable, and a cross-platform application, compatible with Microsoft Windows, macOS, and UNIX operating systems. IntelliGenes not only holds the potential for personalized early detection of common and rare diseases in individuals, but also opens avenues for broader research using novel ML methodologies, ultimately leading to personalized interventions and novel treatment targets. AVAILABILITY AND IMPLEMENTATION: The source code of IntelliGenes is available on GitHub (https://github.com/drzeeshanahmed/intelligenes) and Code Ocean (https://codeocean.com/capsule/8638596/tree/v1).
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.