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 introduces Shiny AMMOA, a user-friendly, interactive R Shiny platform that democratizes integrative multi-omics analysis of murine aging by enabling experimental researchers to explore, visualize, and generate hypotheses from unified transcriptomic, proteomic, and metabolomic datasets without requiring advanced computational skills.
ExplainBind is a novel, structure-free AI framework that predicts protein-ligand binding likelihood, pinpoints specific binding residues, and decodes non-covalent interaction patterns to provide mechanistic insights for drug discovery, outperforming existing black-box models across diverse targets and successfully identifying both inhibitors and activators with distinct functional mechanisms.
This study presents the first integrated genomic and transcriptomic analysis of Tunisian durum wheat landraces, revealing that arid-zone adaptation is primarily driven by trans-regulatory stress-network rewiring rather than selection hotspots, while identifying specific molecular mechanisms and six chromosomal targets for future breeding.
TransXplorer is a freely available, login-free web platform that streamlines the entire RNA-seq analytical workflow—from raw data processing and automated batch correction to functional enrichment, network analysis, and clinical/drug discovery integration—into a single unified environment.
DistPCA is the first distributed, out-of-core C++ framework leveraging MPI-based multi-level parallelism to overcome memory and I/O bottlenecks, enabling highly scalable and accurate Principal Component Analysis for tera-scale genomic datasets across single- and multi-node systems.
This paper introduces Prostate-TriMod, a novel tri-modal histology dataset for prostate cancer that integrates high-resolution multiscale morphology, spatial immune cell maps, and clinical outcomes to facilitate advanced multimodal AI research and prognostic analysis.
This study systematically evaluates 2,1666 plasma cfRNA-Seq samples across multiple studies to demonstrate that technical factors, particularly protocol choice and genomic DNA contamination, overwhelmingly dominate transcriptomic variation over biological phenotypes, thereby establishing evidence-based guidelines to standardize workflows and improve the reproducibility of biomarker discovery.
CatIF-RL is a novel framework that enhances enzyme catalytic activity by steering a graph-based denoising diffusion inverse folding model toward higher predicted kcat values through activity-oriented preference signals and group-relative policy optimization, while maintaining structural fidelity and sequence compatibility.
The paper introduces BiomniBench, a novel process-level evaluation framework that assesses LLM agents on real-world biomedical research tasks using expert-designed rubrics to overcome the limitations of outcome-only benchmarks and reveal critical failures in reasoning and method selection.
This paper demonstrates that a cost-effective, locally-runnable open-weight LLM (specifically qwen3.6:27b) can achieve frontier-level accuracy in orchestrating routine biomedical data analysis tasks, offering a scalable alternative to expensive proprietary models.