Bioinformatics sits at the exciting intersection where biology meets data science, using powerful computer tools to decode the vast complexity of living systems. From mapping the human genome to tracking how viruses evolve, this field transforms raw biological information into actionable insights that drive modern medicine and research forward without requiring a supercomputer to understand the basics.

On Gist.Science, we ensure you never miss a breakthrough by processing every new preprint in this category directly from bioRxiv. Our team provides both plain-language explanations and detailed technical summaries for each paper, making cutting-edge discoveries accessible to everyone regardless of their background.

Below are the latest bioinformatics papers added from bioRxiv, ready for you to explore with clarity and depth.

💻 bioinformatics

Introducing non-enzymatic crosslinks into atomistic simulations of collagen fibrils

This paper introduces an extension to the ColBuilder framework that enables the generation of atomistic collagen fibril models incorporating non-enzymatic advanced glycation end-product (AGE) crosslinks, providing validated force-field parameters and demonstrating their distinct structural and mechanical impacts compared to enzymatic crosslinks.

Giannetti, G., Pils, J., Graeter, F., Monego, D., Dellago, C.2026-03-16
💻 bioinformatics

Scaling the PBWT for Long-Range Shared Ancestry Detection in Large Haplotype Panels

The paper introduces PBML, a novel algorithm that efficiently identifies biologically significant, long-range shared ancestry tracts (kL-SMEMs) in large, diverse haplotype panels by filtering out uninformative short matches on a single compressed PBWT index, achieving substantial speed and memory improvements over existing methods.

Islam, U. I., Cozzi, D., Gagie, T., Varki, R., Colonna, V., Garrison, E., Bonizzoni, P., Boucher, C.2026-03-15
💻 bioinformatics

Bayesian AMMI-Based Simulation of Genotype x Environment Interactions

This paper proposes a Bayesian AMMI-based simulation framework that generates interpretable genotype-by-environment interaction effects using high-throughput environmental covariance matrices, demonstrating its ability to capture directional relationships and improve genomic selection strategies under complex environmental conditions compared to traditional simulation methods.

Lee, H., Segae, V. S., Garcia-Abadillo, J., de Oliveira Bussiman, F., Trujano Chavez, M. Z., Hidalgo, J., Jarquin, D.2026-03-15
💻 bioinformatics

Efficient protein structure prediction fromcompact computers to datacenters withOpenFold-TRT

This paper introduces OpenFold-TRT, a set of accelerations combining TensorRT and MMseqs2-GPU that enables high-throughput, accurate protein structure prediction across diverse hardware—from compact ARM systems to large-scale datacenters—achieving up to 131x faster inference than AlphaFold2 without compromising accuracy.

Didi, K., Sohani, P., Berressem, F., Nesterovskiy, A., Fomitchev, B., Ohannessian, R., Elbalkini, M., Cogan, J., Costa (…)2026-03-15
💻 bioinformatics

Resistance to Pyrethroids in Aedes aegypti: Insights into Transcriptomic Response to Different Insecticide Concentrations Transcriptomic responses of Aedes aegypti to insecticide concentrations

This study reveals that *Aedes aegypti* mosquitoes employ distinct, concentration-dependent transcriptomic strategies to resist type I and type II pyrethroids, ranging from cuticle thickening and metabolic detoxification for permethrin to mitochondrial and oxidative stress adaptations for lambda-cyhalothrin, highlighting the need to consider both insecticide type and dosage in vector control programs.

Munoz, A. M., Mejia-Jaramillo, A. M., Lowenberger, C., Rodriguez, K. S., Triana-Chavez, O.2026-03-15
💻 bioinformatics

stMCP: Spatial Transcriptomics with a Model Context Protocol Server

The paper introduces stMCP, a Model Context Protocol framework that enables accessible, reproducible, and privacy-preserving spatial transcriptomics analysis by allowing large language models to orchestrate local computational tools through natural language, thereby empowering biologists to independently explore complex datasets without the costs and risks of uploading massive data to cloud-based AI services.

Smith, J. J., Wang, X., McPheeters, M., Widjaja-Adhi, M. A., Littleton, S., Saban, D., Golczak, M., Jenkins, M. W.2026-03-14
💻 bioinformatics

Evidence of off-target probe binding affecting 10x Genomics Xenium gene panels compromise accuracy of spatial transcriptomic profiling

This study introduces the Off-target Probe Tracker (OPT) tool to identify and validate off-target probe binding in 10x Genomics Xenium panels, demonstrating that such non-specific interactions can significantly distort spatial gene expression profiles and compromise data accuracy.

Hallinan, C., Ji, H. J., Tsou, E., Salzberg, S. L., Fan, J.2026-03-13