The 14th International Conference on Intelligent Biology and Medicine (ICIBM 2026): Bioinformatics Methods and Applications for Human Health and Disease

Recent advances in high-throughput technologies, large-scale data generation, and artificial intelligence have fundamentally reshaped genetics, genomics, and biomedical research. The rapid accumulation of diverse biological data, ranging from genomes, transcriptomes, and epigenomes to single-cell, spatial, and multi-omics data, as well as clinical and population-level datasets, has created unprecedented opportunities to elucidate biological mechanisms, disease etiology, and therapeutic responses. However, the scale, complexity, and heterogeneity of these data present substantial analytical challenges. There is an urgent need for new bioinformatics methods and computational tools, including integrative analytical frameworks that can translate omics data into biological discoveries and insights into human health and disease.This Frontiers Research Topic aims to showcase recent methodological advances and practical applications in bioinformatics, computational biology, and artificial intelligence, with an emphasis on genetics and genomics research. The Topic is motivated by and affiliated with the 14th International Conference on Intelligent Biology and Medicine (ICIBM) 2026, to be held on August 2-6, 2026, in Buffalo, New York, USA, and will serve as a platform to disseminate high-quality research presented at ICIBM.We invite submissions of original, unpublished research articles and review papers describing recent advances in bioinformatics methodologies, computational modeling, and data-driven applications across genetics, genomics, neurogenomics, genomic medicine, and other biomedical disciplines. Topics of interest include, but are not limited to, the following areas:Bioinformatics and Computational Methods for Human Health and Disease• Human genetics and epigenetics for disease studies, including functional and integrative genomics• Next-generation sequencing data analysis for disease research (WGS, WES, RNA-Seq, ATAC-Seq, ChIP-Seq)• Regulatory genomics, noncoding variants, and structural variation in human health and disease• Single-cell and spatial omics methods for understanding disease mechanisms• Multi-omics data integration for disease subtyping, prognosis, and treatment response• Microbiome and metagenomics analysis in human health and disease• Proteomics and post-translational modification analysis for disease biomarkers• Network- and pathway-based analysis of disease-associated biological processesPrecision Medicine and Translational Bioinformatics• Precision medicine approaches for disease diagnosis, prognosis, and therapy selection• Biomarker discovery and validation for human disease• Pharmacogenomics and drug response prediction• Drug target identification, drug repositioning, and combination therapy discovery• Clinical interpretation of genomic variants and pathogenicity prediction• Population genomics and health disparities in disease researchNeurogenomics and Brain Disorders• Genetic and epigenetic mechanisms underlying neurological and neuropsychiatric disorders• Single-cell and spatial omics in brain development and brain disease• Brain cell-type-specific transcriptomics and regulatory network analysis in disease contexts• Integrative neurogenomics combining omics, imaging, and clinical data• Computational and AI-based approaches for neurogenomic disease studiesArtificial Intelligence and Machine Learning for Disease Bioinformatics• Machine learning and deep learning methods for disease risk prediction and classification• AI-driven analysis of genomics, transcriptomics, and multi-omics disease data• Large language models and knowledge graphs for disease gene, pathway, and drug discovery• Natural language processing for biomedical literature and clinical text mining• Integrative analysis of biomedical images and omics data for disease diagnosisSystems Biology of Human Disease• Network and pathway modeling of disease-related biological systems• Systems-level analysis of signaling, regulatory, and metabolic networks in disease• Computational modeling of disease progression and treatment response• Multi-scale modeling integrating molecular, cellular, and clinical dataBiomedical and Clinical Informatics for Disease Research• Cohort discovery and EHR-based phenotyping for disease studies• Genotype-phenotype association and disease risk modeling• Integration of clinical, genomic, and multi-omics data for translational research• Predictive modeling for disease onset, progression, and clinical outcomesThis Research Topic aims to provide a comprehensive overview of emerging bioinformatics and computational approaches that advance our understanding of human health and disease and accelerate the translation of genomic discoveries into clinical and public health applications. Topic editors: Zhongming Zhao, Qianqian Song, Yijun Sun, Dawei Li Source: https://www.frontiersin.org/research-topics/77404/the-14th-international-conference-on-intelligent-biology-and-medicine-icibm-2026-bioinformatics-methods-and-applications-for-human-health-and-disease