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 MAPPIE, a novel method that generates a two-dimensional embedding map of human protein-protein interactions to predict specific functional roles for individual interaction pairs, particularly outperforming existing baselines in regions of the interactome with sparse functional knowledge.
This study introduces VirGenes, a hierarchical orthology framework that integrates sequence, structural, and functional data to uncover a vast, previously underappreciated diversity of viral carbohydrate-active enzymes across the global virosphere, revealing their complex evolutionary origins and significant roles in virus-host interactions.
The study introduces PhyCD, a phylogeny-aided computational tool that analyzed nearly 5 million SARS-CoV-2 genomes to identify over 10,000 contamination events and mask nearly 65,000 erroneous substitutions, thereby improving the reliability of downstream pathogen evolution and transmission analyses.
SLIM is a lightweight, computationally efficient model that leverages 64-dimensional STRING network embeddings and a closed-form ridge-regression estimator to accurately predict cellular responses to genetic perturbations, often outperforming complex deep learning baselines with minimal trainable parameters.
This paper demonstrates that orphaned scientific software, such as the abandoned MATLAB-based NuMorph toolkit, can be successfully rescued and transformed into sustainable, reusable community workflows like nf-core/lsmquant by applying systematic re-engineering guided by FAIR principles and modern software engineering standards.
This study benchmarks the Twist Bioscience genome-wide SNP capture (GxS) platform against whole-genome sequencing and the Illumina GSA-24 array by evaluating genotype concordance and Mendelian violation rates across 555 individuals in 184 nuclear families, aiming to provide a third-party assessment of this emerging targeted sequencing technology.
This paper presents a publicly available database containing 3D unsteady Navier-Stokes simulations and high-quality hexahedral meshes for 779 coronary arteries reconstructed from the FAME 2 trial, aiming to address the scarcity of numerical haemodynamics data for data-driven modeling and machine learning applications.
This paper introduces TranScouter, a lightweight encoder-decoder framework that leverages LLM-derived gene embeddings and target condition transcriptomic profiles to competitively predict transcriptional responses to gene perturbations across both seen and unseen biological conditions.
The paper introduces SAHA, a scalable R package that accelerates cell type identification in single-cell and spatial transcriptomic studies by enabling rapid, privacy-preserving label transfer using summary statistics and user-defined hyperparameters to generate transparent, semi-automated annotation reports.
The authors present BWR-finder, a novel, database-free software tool that utilizes a parallelized BWT-based seed-and-extend algorithm to efficiently detect interspersed repeats in gigantic genomes (over 10 Gb) with improved speed and memory usage compared to existing tools while maintaining high sensitivity.