Computational Intelligence for Bioinformatics, Computational Biology, and Biomedical Informatics

Computational intelligence (CI) methods, including machine learning, deep learning, and evolutionary computation, are increasingly central to biomedical engineering, computational biology, and bioinformatics. The growing scale and complexity of omics, imaging, and clinical data have driven demand for models that can detect patterns, predict outcomes, and support decision-making across healthcare and the life sciences. At the same time, questions of interpretability, robustness, fairness, and regulatory compliance remain pressing, open challenges. This Research Topic builds on the discussions held at the 2026 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (IEEE CIBCB 2026), bringing together extended contributions and new submissions from the wider research community working at the interface of AI and the life sciences.This Research Topic aims to capture the latest advances in computational intelligence as applied to biomedical engineering, computational biology, and bioinformatics, while extending the reach of the IEEE CIBCB 2026 community to a broader global audience of researchers, clinicians, and practitioners. We invite substantially extended versions of papers presented at IEEE CIBCB 2026, as well as new submissions addressing similar themes, to present novel methods, applications, and critical perspectives. A central goal is to showcase how CI techniques can be made more accurate, interpretable, and trustworthy when applied to real-world biomedical and biological problems, and to identify open challenges that warrant further investigation, including data heterogeneity, model generalizability, and translation into clinical or laboratory practice.We welcome submissions on, but not limited to, the following themes: AI/CI in biomedical engineering and healthcare informatics (medical and pathology image analysis, biomedical data modelling, personalized medicine, drug discovery and repurposing, biomarker discovery); AI/CI in computational biology (systems and synthetic biology, structure prediction and protein folding, modelling and optimization of biological systems, computational epidemiology, epigenomics); AI/CI in bioinformatics (scRNA-seq analysis, comparative genomics, gene expression analysis, sequence alignment, evolution and phylogeny); and AI/CI in medical ethics and legal aspects, including explainability, interpretability, and sustainability. Original Research, Review, Methods, and Perspective articles are all welcome, including benchmarking and reproducibility studies, from both IEEE CIBCB 2026 presenters and the broader scientific community. Topic editors: Sotiris Tasoulis, Daniele Maria Papetti, Spiros Georgakopoulos, Vassilis P. Plagianakos Source: https://www.frontiersin.org/research-topics/83556/computational-intelligence-for-bioinformatics-computational-biology-and-biomedical-informatics