JMIR Bioinformatics Opens Submissions on AI, Genomics, and Digital Twins in Healthcare

The overlap between computational biology and clinical medicine has grown substantially over the past decade - large-scale genomic datasets, AI-driven imaging analysis, and drug discovery algorithms built on molecular simulation are no longer experimental curiosities. They are active areas of research with clinical implications. A new open-access theme issue from JMIR Bioinformatics and Biotechnology is soliciting original research and reviews focused on how those tools are advancing healthcare.

JMIR Publications announced the call for papers February 17, 2026, for a theme issue titled "Bridging Data, AI, and Innovation to Transform Health." The journal, indexed in PubMed and Scopus, is the official publication of the MidSouth Computational Biology and Bioinformatics Society (MCBIOS). Submissions from researchers presenting at the MCBIOS 2026 Conference (March 27-29, 2026, Moffitt Cancer Center, Tampa, Florida) are specifically encouraged.

Research areas the call covers

The scope spans six broad domains, each reflecting an area where computational approaches are actively changing how medicine works:

AI in medicine covers machine learning and deep learning applied to diagnostics, treatment modeling, and personalized medicine. This includes predictive models for disease risk, classification of medical images, and algorithms that synthesize multi-modal patient data to guide clinical decisions.

Computational genomics and precision oncology addresses genomic data analysis and epigenetic regulation in cancer research. With tumor sequencing becoming routine in many cancer centers, computational tools for interpreting that data - identifying driver mutations, predicting drug sensitivity, characterizing tumor heterogeneity - represent an active research front.

Radiogenomics and imaging targets AI applications in radiology and the integration of imaging data with molecular characterization. Combining what a scan reveals about tumor morphology with what sequencing reveals about its genomic landscape has shown potential for more accurate prognosis and treatment selection than either data type alone.

Drug discovery encompasses computational modeling and AI-driven pipelines for accelerating drug development and identifying new uses for existing compounds. Deep learning models trained on molecular structure data can now screen virtual compound libraries at scales not achievable through physical screening, substantially accelerating the early stages of the discovery process.

Large language models as applied specifically to bioinformatics and genomics - including analysis of clinical text, tabular biological data, and web-based bioinformatics tools - represent a newer but rapidly growing area. LLMs trained on biomedical literature or fine-tuned on genomic sequences are being tested for a range of applications from literature synthesis to variant interpretation.

Digital twins in healthcare covers computational patient modeling, virtual cohorts, and predictive simulation. A digital twin in a clinical context is a computational model of a specific patient's biology that can be used to simulate disease progression or predict treatment response before administering an intervention. Genomics-driven digital twins represent an emerging approach to personalized medicine that moves beyond population-level evidence toward individual prediction.

The MCBIOS connection

The MidSouth Computational Biology and Bioinformatics Society has been organizing researchers in computational biology across the US mid-south region since its founding. Its annual conference provides a venue for early-stage work and collaborative exchange. Linking the theme issue directly to the MCBIOS 2026 conference creates a pathway for conference presentations to reach the peer-reviewed literature, giving authors an incentive to expand their research into full manuscripts.

Researchers interested in submitting can find full submission guidelines at the JMIR Bioinformatics and Biotechnology website. The call is open to researchers, clinicians, and technologists working at the intersection of computation and health.