💻 Category

bioinformatics

1199 papers

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

Drug-Prot: A query system for statistical inference of drug effects and interactions in dynamic proteomic networks

Drug-Prot is a publicly available computational framework and web application that leverages large-scale perturbation proteomics data from breast cancer cell lines to statistically infer causal drug effects, drug-drug interactions, and dynamic protein dependency networks, thereby enabling targeted analysis of protein-level responses to single and combination therapies.

Ulmer, M., Sun, R., Qian, L., Aebersold, R., Guo, T., Buehlmann, P.2026-06-22
💻 bioinformatics

Hierarchical classification of immune cell transcriptomes at population-scale

This paper introduces Suco, a resource of independent expert annotations, and Compocyte, a hierarchical classifier, to establish a robust framework that successfully classified 15.6 million immune cells across nearly 4,000 patients, revealing novel immune phenotypes and advancing population-scale immunology research.

Beltz, C., Qiu, Z., Sadowski, L., Kraske, J. A., Aggarwal, A., Quintanal-Villalonga, A., Manoj, P., Littbarski, A., Baja (…)2026-06-21
💻 bioinformatics

Antibody-Antigen Affinity Prediction with Chain-Aware Protein Language Modeling

The paper introduces AbAffinity, a lightweight, sequence-only deep learning model that utilizes a chain-aware three-stream architecture to accurately predict antibody-antigen affinity by preserving distinct heavy chain, light chain, and antigen representations, thereby outperforming existing methods in scenarios where structural data is unavailable.

Singh, H., Malhotra, A., Srivastava, S. P., SINGH, R. K., Gorantla, R.2026-06-21
💻 bioinformatics

The recount3 Python package for programmatic access to uniformly processed RNA-seq data

The recount3 Python package provides a robust API and CLI to enable efficient programmatic access, caching, and analysis-ready data formatting for tens of thousands of uniformly processed human and mouse RNA-seq samples, thereby bridging the gap between large-scale public transcriptomic data and modern Python-based machine learning ecosystems.

Alsalihi, A., Flight, R. M., Moseley, H. N. B.2026-06-20
💻 bioinformatics

Tox21mer, A transformer foundation model for Tox21 high-throughput concentration-response curves data

The paper introduces Tox21mer, a 43.5-million-parameter transformer foundation model pretrained on 2.5 million Tox21 concentration-response curves via masked-response reconstruction, which generates high-quality 768-dimensional embeddings that achieve state-of-the-art performance in predicting assay outcomes and AC50 values while enabling extrapolation to untested compounds.

Li, L., Hwang, J., Shockley, K., Li, Y., Motsinger-Reif, A., Hsieh, J.-H., Auerbach, S. S., Reif, D.2026-06-19
💻 bioinformatics

Children's DNA Methylation and Family Dynamics in a Congo Basin Subsistence Community: Links with Parental Conflict and Fathers' Caregiving

This study demonstrates that in a Congo Basin subsistence community, children's DNA methylation patterns are significantly associated with parental conflict and father caregiving, linking these family dynamics to genes involved in stress, immunity, and development, thereby suggesting that the biological embedding of family environments is a universal phenomenon across diverse socio-ecological contexts.

Chan, M. H.-M., Merrill, S. S., Zhuang, B. C., Lin, D. T. S., Macisaac, J. L., Miegakanda, V., Lew-Levy, S., Boyette, A. (…)2026-06-19
💻 bioinformatics

Predicting optimal growth temperatures of bacteria using learned structural information from a single protein

The paper introduces ROSEATE, a novel framework that accurately predicts bacterial optimal growth temperatures by leveraging MSA Transformer-derived structural signatures from a single ubiquitous protein, adenylate kinase, enabling robust, phylogenetically generalizable, and community-level thermal inference across diverse environments.

Hoffert, M., Myerscough, D., Dragone, N. B., Gebert, M. J., Silberg, J. J., Fierer, N.2026-06-18
💻 bioinformatics

MetaHarmonizer: robust biomedical metadata harmonization and a contamination control for inflated LLM performance on public benchmarks

MetaHarmonizer is a robust, fully local, and deterministic automated system for biomedical metadata harmonization that combines a multi-stage cascade with controlled vocabularies to prevent hallucinations and inflated benchmark performance, achieving state-of-the-art accuracy in schema and ontology mapping while enabling principled human-in-the-loop triage.

Li, C., Dahl, A., Gravel-Pucillo, K. D., Long, K., Waters, M., de Bruijin, I., Davis, S., Oh, S.2026-06-17