💻 Category

bioinformatics

1210 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

Deciphering the links between metabolism and health by building small-scale knowledge graphs: application to endometriosis and persistent pollutants

This paper introduces Kg4j, a computational framework that generates tailored, small-scale knowledge graphs from a large-scale biomedical database to integrate experimental data and generate hypotheses, demonstrating its efficacy in uncovering novel links between persistent organic pollutants and endometriosis while validating the approach through literature comparison and precision optimization.

Mathe, M., Laisney, G., Filangi, O., Giacomoni, F., Delmas, M., Cano-Sancho, G., Jourdan, F., Frainay, C.2026-03-04
💻 bioinformatics

T cell-Macrophage Interactions Potentially Influence Chemotherapeutic Response in Ovarian Cancer Patients.

By analyzing naturally occurring doublets in single-cell RNA sequencing data, this study reveals that physical T cell-macrophage interactions in ovarian cancer drive therapeutic resistance through M2-polarized macrophage-induced T cell exhaustion, whereas M1-polarized interactions in sensitive patients support effective antigen presentation without exhaustion.

Hameed, S. A., kolch, W., Zhernovkov, V.2026-03-04
💻 bioinformatics

Formalized scientific methodology enables rigorous AI-conducted research across domains

This paper proposes and validates a formalized, phase-gated scientific protocol for language models that decomposes research into procedural, integrity, and governance layers, demonstrating through six end-to-end projects that such constraints enable AI agents to produce rigorous, evidence-backed, and auditable scientific outputs across diverse domains while mitigating integrity risks compared to unconstrained approaches.

Zhang, Y., Zhao, J.2026-03-04
💻 bioinformatics

STCS: A Platform-Agnostic Framework for Cell-Level Reconstruction in Sequencing-Based Spatial Transcriptomics

STCS is a platform-agnostic, reference-free framework that reconstructs coherent single-cell transcriptomes from high-density spatial sequencing data by integrating nuclei segmentation with a joint transcriptomic-spatial distance model, thereby overcoming the fundamental bottleneck of cell-level analysis in technologies like Visium HD and Stereo-seq.

Chen Wu, L., Hu, X., Zhan, F., Sun, C., Gonzales, J., Ofer, R., Tran, T., Verzi, M. P., Liu, L., Yang, J.2026-03-03
💻 bioinformatics

snputils: A High-Performance Python Library for Genetic Variation and Population Structure

snputils is a high-performance, open-source Python library designed to unify the efficient I/O, transformation, and statistical analysis of genomic and population genetic data within a single, reproducible framework that addresses the limitations of existing fragmented tools.

Bonet, D., Comajoan Cara, M., Barrabes, M., Smeriglio, R., Agrawal, D., Aounallah, K., Geleta, M., Dominguez Mantes, A. (…)2026-03-03
💻 bioinformatics

A comprehensive assessment of tandem repeat genotyping methods for Nanopore long-read genomes

This study systematically benchmarks seven actively maintained Nanopore long-read tandem repeat genotyping tools across accuracy, usability, and diverse genomic contexts, revealing that no single tool is universally superior and that sequence-level evaluation is essential for selecting the right method for population studies and clinical diagnostics.

Aliyev, E., Avvaru, A., De Coster, W., Arner, G. M., Nyaga, D. M., Gibson, S. B., Weisburd, B., Gu, B., Gonzaga-Jauregui (…)2026-03-03