858 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.
Protenix-v1 is the first fully open-source biomolecular structure prediction model that surpasses AlphaFold3 in accuracy while matching its constraints, featuring inference-time scaling, expanded template and RNA capabilities, and a larger 2025-trained variant alongside improved benchmarking tools.
This study demonstrates that host-derived inflammation acts as a selective pressure that restructures the oral microbiome from carbohydrate-utilizing commensals to metabolically specialized, catabolic inflammophilic communities, providing a framework for microbiome-targeted therapies to restore ecological stability.
This study demonstrates through systematic simulations that gene tree estimation error (GTEE) typically exerts a stronger detrimental impact on species tree accuracy than incomplete lineage sorting (ILS), despite comparable overall discordance levels, by revealing that GTEE generates uniform, high-entropy noise while ILS produces structured, constrained skew in quartet distributions.
The authors present Folddisco, a free software tool and webserver that enables rapid, accurate, and storage-efficient searching of structural motifs across 53 million protein structures by utilizing a compact index of position-independent geometric features and a rarity-based scoring system.
This paper introduces a formal, agnostic framework for deriving synteny blocks directly from sequence data by partitioning genomic elements to avoid obscuring rearrangements, proving that while general optimization is NP-hard, a linear-time algorithm exists to simultaneously minimize block count and length under collinearity constraints.
ProteoMapper is a user-friendly computational framework that integrates domain annotation with motif detection to quantify the spatial relationships and evolutionary conservation of motif-domain patterns within protein families, thereby facilitating the investigation of disease mutations and regulatory mechanisms.
This paper introduces Q-FSNet and Q-DirichNet, novel sparse Bayesian quantile neural network frameworks that effectively identify optimal physiological ranges ("sweet spots") for biomarkers to minimize biological age acceleration, as demonstrated by their application to metabolite data from the Canadian Longitudinal Study on Aging.
The paper introduces OT-knn, a robust spatial transcriptomics alignment framework that integrates local neighborhood information into an optimal transport model to accurately match tissue regions across diverse samples despite noise, geometric distortions, and biological heterogeneity.
The paper introduces wavess 1.2, an enhanced within-host virus sequence simulation framework that incorporates HLA-aware cytotoxic T-lymphocyte responses and variable recombination rates to more accurately model immune-driven viral evolution and diversification.
This study presents the first large-scale analysis of chemical probe literature, revealing that these tools provide crucial early evidence for target-disease associations, uncover novel therapeutic opportunities in underexplored diseases, and strengthen validation beyond correlative data.