1012 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.
This paper argues that co-expression network analysis offers a more effective and parsimonious framework than traditional differential expression analysis for characterizing microglia, as it reveals context-dependent, concurrent molecular programs that better explain the cell type's functional heterogeneity.
The paper introduces Locat, a novel framework that identifies highly specific marker genes in single-cell transcriptomics by jointly testing for expression enrichment within compact cellular regions and depletion elsewhere, thereby enabling robust, interpretable, and batch-free cross-condition comparisons of cell populations and developmental trajectories.
This paper introduces CASPA, an automated, end-to-end pipeline for single-cell proteomics that overcomes existing analytical limitations through adaptive quality control, entropy-guided batch correction, and a refined large language model framework for context-aware cell type annotation, achieving high accuracy validated against orthogonal ground truth across diverse biological datasets.
This study demonstrates that ultra low-coverage whole genome sequencing (ulcWGS) serves as a cost-effective and reliable alternative to high-coverage methods for accurately estimating canine inbreeding levels across diverse breeds.
REBEL is a framework that ensures long-term, FAIR-compliant reproducibility in bioinformatics by using deep code inspection and curated knowledge to resolve missing system dependencies and generate self-contained, deterministic environments without requiring containerization expertise.
This study utilizes flow molecular dynamics simulations to demonstrate how hydrodynamic forces drive von Willebrand factor from an autoinhibited compact state to an activated extended conformation, revealing the specific roles of glycan-modulated autoinhibitory modules in mechanosensitive regulation.
Leveraging the 2021 release of AlphaFold2 as a quasi-experiment, this study demonstrates that AI predictions can expand scientific frontiers by reversing the decline in research on novel proteins and redirecting collective attention toward understudied genes and targets, thereby challenging concerns that AI merely reinforces established scientific canons.
This paper presents a suite of open-source plugins for Fiji (ImageJ) and Python designed to analyze signal-to-noise ratio, contrast, and resolution in Scanning Electron Microscopy images, including support for custom FIB-SEM instruments.
RastQC is a high-performance, unified sequencing quality control tool written in Rust that replaces the Java-based FastQC by offering a single 2.1 MB static binary capable of analyzing both short and long reads with matching accuracy, significantly faster processing speeds, and reduced memory consumption.
This study demonstrates that the protein fold repertoire of archaea is broadly conserved across deep phylogenetic distances, revealing that the scarcity of experimentally determined archaeal structures stems from classification sensitivity to divergent sequences rather than a lack of known structural diversity.