850 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 authors introduce BaySeq-Y, a novel Bayesian method that directly and accurately quantifies mosaic loss of chromosome Y from sequencing data by integrating read depth, allelic imbalance, and haplotype phasing, outperforming existing approaches in both simulations and biological validations.
By implementing a functional model of the insect head direction circuit on a robot, researchers demonstrated that while the system can successfully calibrate and substitute orientation cues like wind for light, it also reveals a directional bias caused by conflicts between recurrent and instantaneous inputs that real insects likely compensate for through evolved neural mechanisms.
This exploratory analysis of the MSK-CHORD dataset suggests that, unlike in L858R-only or T790M-only contexts where osimertinib is superior or equivalent, the EGFR L858R+T790M compound mutation in non-small cell lung cancer may represent a distinct pharmacological entity where erlotinib numerically outperforms osimertinib, warranting prospective validation.
This study reveals that cognitive resilience to Alzheimer's disease pathology is characterized by a distinct molecular state centered on preserved NPTX2 expression, which maintains core synaptic and inhibitory programs while selectively recruiting adaptive proteostasis, trafficking, and immune pathways in high-pathology individuals, a coordination that is lost in symptomatic disease.
This study demonstrates that pooled correlation coefficients in bulk and single-cell transcriptomic data frequently mislead network inference by reversing direction due to Simpson's paradox driven by biological heterogeneity, necessitating the reporting of context-specific correlations and heterogeneity statistics rather than relying on single global estimates.
OpenGerminal presents a fully open-source implementation of the Germinal antibody design pipeline that replaces proprietary components with an open stack and adopts AbLang1, achieving significantly higher cofolding pass rates and broader deployment accessibility while maintaining equivalent structural confidence metrics.
The paper argues that the stalled predictive performance in modeling peptide skin penetration stems from an ill-posed reliance on conflated transdermal flux labels that ignore delivery vehicles and endpoints, proposing instead a reframed approach that separates intrinsic barrier-crossing potential from delivery-specific retention and risk.
The paper introduces EnzymeArt, a function-conditioned generative framework that successfully converts functional descriptions into experimentally validated enzymes with quantitative catalytic activity across multiple protein families, achieving performance that often matches or exceeds wild-type and commercial references.
This paper critically reviews and proposes homology-aware cross-validation strategies to address data leakage and ensure fair generalization assessment for both classical and deep learning-based RNA secondary structure prediction methods.
Bamsnap-LRS is an automated command-line tool designed to overcome the scalability and optimization limitations of existing visualization software by enabling high-throughput, publication-ready batch visualization of long-read sequencing alignments with support for long-read-specific features, phased SNP inspection, and diverse genomic analyses.