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

Leviathan: A fast, memory-efficient, and scalable taxonomic and pathway profiler for (pan)genome-resolved metagenomics and metatranscriptomics

Leviathan is an open-source software package that enables ultra-fast, memory-efficient, and accurate taxonomic and functional profiling of metagenomes and metatranscriptomes at genome and pangenome resolution by combining alignment-free taxonomic methods with DNA-space pseudo-alignment to bypass computationally expensive translated-search steps.

Espinoza, J. L., Dupont, C. L., Phillips, A.2026-05-28

💻 bioinformatics

Minimal Computational Framework for Systematic Identification of Antimicrobial Targets

This paper presents a minimal, multi-scale computational framework that leverages protein dynamics and recurrent disruption mechanisms to systematically identify and prioritize antimicrobial targets for rational polypharmacology, aiming to enhance therapeutic efficacy while minimizing toxicity and mutational escape.

Hassan, S. A.2026-05-28

💻 bioinformatics

gTranslate: rapid and accurate translation table prediction for prokaryotic genomes

The paper introduces gTranslate, a computationally efficient machine learning tool that accurately predicts translation tables for prokaryotic genomes without prior taxonomic classification, achieving over 99.99% accuracy and enabling the discovery of novel genetic code variations in specific bacterial lineages.

Chaumeil, P.-A., Hugenholtz, P., Parks, D. H.2026-05-28

💻 bioinformatics

Sequence-Based Prioritization of Promoter Regulatory Variants in Colorectal Cancer Using a DNA Foundation Model

This study presents a computational framework leveraging the Evo2 DNA foundation model to prioritize noncoding regulatory variants in colorectal cancer by quantifying their impact on promoter sequences, successfully identifying high-impact candidates enriched in cancer-relevant pathways and GWAS loci without relying on supervised training or predefined annotations.

Shome, S., Vajinepalli, S., Saraf, A.2026-05-28

💻 bioinformatics

SQANTI-browser: visualization and curation of SQANTI3-classified long-read transcriptomes within the UCSC Genome Browser

SQANTI-browser is a novel visualization framework that integrates SQANTI3-classified long-read transcriptome data into the UCSC Genome Browser, enabling interactive filtering, evidence-guided curation, and the resolution of alignment artifacts to rescue actionable novel isoforms across diverse datasets.

Paniagua, A., Blanco-Gomez, C., Colomer Fernandez, A., Diekhans, M., Conesa, A., Monzo, C.2026-05-28

💻 bioinformatics

CARIBOU: Computational AI Research Interface for Bioinformatics, Omics, and Unifying Agents

CARIBOU is a multi-agent AI framework designed for autonomous, iterative, and reproducible bioinformatics analysis within institutional high-performance computing environments, utilizing researcher-editable blueprints and persistent executable states to overcome the limitations of static code generation in processing large-scale single-cell and spatial omics datasets.

Riffle, D., Shirooni, N., Sureshkumar, P., Vijay, V., Rose, M. F.2026-05-28

💻 bioinformatics

VaxjoOnto: A Vaccine Ontology-driven Framework for Adjuvant Selection

VaxjoOnto is a novel framework that leverages a vaccine ontology-driven heterogeneous knowledge graph and a graph neural network to effectively prioritize adjuvants for both known and novel diseases, addressing a critical bottleneck in vaccine development by shifting focus from antigen discovery to adjuvant selection.

He, Y., Zheng, Y.2026-05-27

💻 bioinformatics

Signal, Bounds, and Baselines: Principles for Evaluating Virtual Cell Perturbation Models

This paper introduces the SBB (Signal, Bounds, and Baselines) framework to rigorously evaluate virtual cell perturbation models, revealing that complex deep learning methods often fail to meaningfully outperform simple linear baselines and highlighting the need for standardized metrics to distinguish genuine biological signal from statistical artifacts.

Vollenweider, M. S., Bühlmann, P.2026-05-27

💻 bioinformatics

There and back again: a multi-omics tale of thyroid co-expression network rewiring

This study establishes a best-practice framework for constructing simultaneous multi-omics weighted gene co-expression networks to analyze thyroid toxicity and recovery in a rodent model, demonstrating that concatenating unscaled omics layers preserves biological structure while revealing extensive molecular disruption and partial restoration through complementary module preservation and differential connectivity analyses.

Pozhidaeva, M., Bussmann, H., Huisinga, M., Buesen, R., Hackermüller, J., Canzler, S.2026-05-27

💻 bioinformatics

GAE-Δ: A Graph-Learning Framework for Gene Network Rewiring and Clinical Outcome Prediction from Multi-Omics Data

The GAE-Δ framework leverages a graph autoencoder to model phenotype-specific gene network rewiring across multi-omics data, achieving superior clinical outcome prediction and identifying biologically relevant cancer drivers compared to existing linear factorization and network-based methods.

Tang, Z., Chen, Z., Chen, M., Wang, Y., Ennis, S., Niranjan, M., Ewing, R.2026-05-26

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