bioinformatics papers | Gist.Science

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

In silico transcriptomic analysis reveals shared molecular signatures and immune-associated pathways between Hashimotos thyroiditis and type 2 diabetes with exploratory drug repurposing

This study utilizes in silico transcriptomic analysis to identify shared immune-associated molecular signatures and key genes between Hashimoto's thyroiditis and type 2 diabetes, subsequently prioritizing three candidate drugs (gliquidone, oleanolic acid, and glipizide) for potential repurposing to address the comorbidity.

Sharma, O., Ahmed, F., Sharma, D., Sharma, A., Noor, T., Faysal, F., Ahmed, F., Hossain, S., Noman, A., Latif, M. A., Al (…)2026-02-17

💻 bioinformatics

Systematic Evaluation of Transfer Learning Strategies for Clinical Chemotherapy Response Prediction

This study systematically evaluates transfer learning strategies for predicting clinical chemotherapy response using TCGA data, revealing that most direct transfer methods fail to improve performance while hybrid approaches and model fine-tuning offer more reliable gains.

Du, H., Ballester, P.2026-02-17

💻 bioinformatics

rustybam: a composable toolkit for alignment analysis and visualization with SafFire

The paper introduces rustybam, a Rust-based command-line toolkit for CIGAR-aware manipulation of PAF and BAM alignments, and SafFire, a browser-based tool for interactive genome comparison visualization, both of which are open-source and designed to facilitate alignment analysis and structural variant exploration.

Vollger, M. R.2026-02-17

💻 bioinformatics

Gene-based calibration of high-throughput functional assays for clinical variant classification

The paper introduces ExCALIBR, a semi-supervised framework that calibrates high-throughput functional assay data using skew normal mixtures to generate variant-specific probabilities of pathogenicity, thereby overcoming the subjectivity of current gene-specific thresholds and significantly reducing variants of uncertain significance across 80 datasets.

Zeiberg, D., Stewart, R. C., Jain, S., Tejura, M., McEwen, A. E., Fayer, S., Sverchkov, Y., Craven, M., Pejaver, V., Rub (…)2026-02-16

💻 bioinformatics

resLens: genomic language models to enhance antibiotic resistance gene detection

The paper introduces resLens, a family of genomic language models that outperform traditional alignment-based methods in detecting antibiotic resistance genes by leveraging latent genomic representations to identify sequences dissimilar to known references.

Mollerus, M., Dittmar, K., Crandall, K. A., Rahnavard, A.2026-02-16

💻 bioinformatics

rbio1-training scientific reasoning LLMs with biological world models as soft verifiers

This paper introduces rbio1, a biological reasoning model trained via reinforcement learning using biological world models as soft verifiers to simulate experiments, thereby achieving state-of-the-art performance in perturbation prediction and zero-shot transfer to disease-state tasks without requiring costly experimental data.

Istrate, A.-M., Milletari, F., Castrotorres, F., Tomczak, J. M., Torkar, M., Li, D., Karaletsos, T.2026-02-16

💻 bioinformatics

DupyliCate: mining, classifying, and characterizing gene duplications

DupyliCate is a versatile, high-throughput Python tool designed to identify, classify, and characterize gene duplications across diverse species, as demonstrated through its application to various plant and non-plant genomes and specific evolutionary case studies.

Natarajan, S., Pucker, B.2026-02-16

💻 bioinformatics

Learning fragment-based segmentation of binding sites from molecular dynamics: a proof-of-concept on cardiac myosin.

This study introduces FragBEST-Myo, a deep learning-based semantic segmentation tool that utilizes fragment binding propensity maps derived from molecular dynamics to accurately characterize cardiac myosin binding sites and effectively screen apo-state conformations for ensemble docking.

Yang, Y.-Y., Pickersgill, R. W., Fornili, A.2026-02-16

💻 bioinformatics

Benchmarking within-sample minority variant detection with short-read sequencing in M. tuberculosis

This study benchmarks seven variant callers on simulated *Mycobacterium tuberculosis* data to identify FreeBayes as the most effective tool for detecting low-frequency variants and introduces a new error model that significantly reduces false positives while preserving true variants.

Mulaudzi, S., Kulkarni, S., Marin, M. G., Farhat, M. R.2026-02-16

💻 bioinformatics

Leveraging ONT move table values for signal aware variant calling

Clair3 v2 is a computationally efficient variant calling method that leverages the lightweight ONT move table and dwelling time information to significantly improve SNP and Indel accuracy, particularly in complex genomic regions, while maintaining negligible runtime overhead compared to existing signal-aware approaches.

Yu, X., Zheng, Z., Chen, L., Qin, Z., He, M., Luo, R.2026-02-16

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