💻 Category

bioinformatics

1197 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

Surrogate Gradients for Gradient-Based Parameter Estimation in Simplified Neuron Models

This paper introduces a differentiable Adaptive Exponential Integrate-and-Fire model using surrogate gradients within the Jaxley framework, demonstrating that while this approach enables efficient gradient-based parameter estimation for subthreshold dynamics, it currently fails to outperform gradient-free methods in recovering full spike trains due to the non-differentiable nature of the spike mechanism.

Mayer, P., Kozlov, A.2026-09-24
💻 bioinformatics

PoLoCo: A reproducible pooled low-coverage workflow for draft genome assembly and allele frequency analysis from ethanol-preserved small non-model invertebrates

The paper introduces PoLoCo, a reproducible, open-source workflow that enables draft genome assembly and population-level allele frequency analysis from ethanol-preserved small non-model invertebrates, overcoming DNA degradation challenges to facilitate ecological and evolutionary research without requiring high-quality DNA or long-read sequencing.

Shuvo, M. J., Segelbacher, G., Geue, J.2026-09-24
💻 bioinformatics

Benchmarking 16S rRNA gene amplicon analysis in high-diversity microbial communities reveals fundamental trade-offs in clustering and denoising

This study benchmarks four 16S rRNA amplicon analysis pipelines using simulated and real high-diversity communities to demonstrate that pipeline performance involves fundamental trade-offs between species representation, cluster purity, and abundance accuracy that vary with dataset characteristics, thereby arguing against fixed analytical defaults in favor of objective-driven parameter selection.

Stamsaas, C., Rognes, T., Rudi, K., Snipen, L., Vinje, H.2026-09-24
💻 bioinformatics

Predicting single mutation effects on binding affinity at protein-protein interfaces based on MMPBSA calculations

This paper presents a user-friendly, physics-based workflow using MMPBSA calculations to accurately predict the effects of single amino acid substitutions on protein-protein and protein-peptide binding affinity, demonstrating performance that matches or exceeds established methods across diverse targets including SARS-CoV-2 spike protein complexes.

Noske, J., Janzen, M., Lepoivre, T., Höcker, B.2026-09-24
💻 bioinformatics

Comparative analysis of 15 chromosome-scale near T2T assemblies of Brazilian Fusarium graminearum isolates

This study presents fifteen high-quality, near telomere-to-telomere chromosome-scale assemblies of Brazilian *Fusarium graminearum* isolates, revealing a highly conserved genomic structure and suggesting that the observed phenotypic variation in aggressiveness is likely driven by regulatory differences or the accessory genome rather than large-scale structural rearrangements.

Kroll, E., Wood, A. M., Nicolli, C. P., de Klerk, A., Urban, M., Del Ponte, E., Hassani-Pak, K., Hammond-Kosack, K. E.2026-09-23
💻 bioinformatics

A Bayesian modelling framework for inference of latent infection risk patterns from virus neutralisation assay titration data

This paper introduces a two-part Bayesian framework that infers latent infection risk patterns directly from raw virus neutralisation assay titration data by modeling antibody concentrations and propagating uncertainty into an age-structured serocatalytic mixture model, thereby overcoming the limitations of conventional dichotomous methods and revealing distinct infection dynamics for enteroviruses A71, D68, and coxsackievirus A6 in England.

Alrefae, T. A., Pons-Salort, M., Donnelly, C. A., Lambert, B., Kamau, E.2026-09-22