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.
The paper introduces MeSyTo, an open-source, ontology-driven framework that harmonizes metadata for toxicological omics studies by semantically aligning diverse reporting standards to enable consistent annotation, automated validation, and interoperable data exchange across transcriptomics, proteomics, and metabolomics.
This study integrates host transcriptomic and vector small RNA datasets to reveal a tightly synchronized tripartite molecular crosstalk between tomato antiviral immunity, Begomovirus siRNA accumulation, and *Bemisia tabaci* small RNA remodeling, identifying specific cross-kingdom regulatory modules as promising targets for dual-action RNA interference strategies to control virus transmission.
Lacuna is an open-source Python tool that discovers cryptic binding pockets by generating conformational ensembles from a single input structure, detecting pockets across these conformers, and ranking them to identify sites that are invisible in static protein structures, all while maintaining high accuracy and computational efficiency without requiring extensive simulation budgets.
The paper introduces AlphaConformers, a structure-guided pipeline that leverages structural information from protein databases to steer AlphaFold2 toward generating multiple alternative protein conformations, significantly outperforming existing methods in modeling subtle ligand-induced structural changes.
The authors developed MetaChlam, an automated Nextflow pipeline that integrates multiple bioinformatics tools to accurately detect and type *Chlamydia trachomatis* strains in metagenomic samples with as few as 250 reads, overcoming limitations of traditional genotyping methods and revealing unexpected contamination in non-infectious datasets.
This study introduces improved brain aging prediction models by leveraging Oxford Nanopore long-read sequencing of over 28 million CpG sites across diverse African and European ancestry cohorts, demonstrating that these long-read epigenetic clocks outperform existing array-based methods and highlight the critical importance of inclusive, ancestry-aware training datasets.
This study integrates fragmented antimicrobial resistance (AMR) surveillance data from private, public, and academic sources across Africa into interactive GIS dashboards to visualize disparities in reporting and infrastructure, thereby providing a unified evidence base to guide policy, research, and public health interventions.
This paper introduces nf-sarcopipe, a modular Nextflow pipeline that integrates de novo and reference-guided miRNA discovery with transcriptomic analysis to identify novel and known exercise-responsive miRNAs and their regulatory networks involved in skeletal muscle adaptation.
This study benchmarks three codon-focused masked language models against traditional methods, demonstrating that while no single model dominates all tasks, they effectively capture translational context to generate variants with superior expression performance, suggesting that sampling across multiple models is a promising strategy for optimizing nucleic acid-based medicines.
This paper demonstrates that previously reported advantages of codon language models in synonymous-variant prediction are evaluation artifacts caused by data leakage, as these gains disappear under strict leakage-controlled benchmarks like the newly released CodonBench.