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.
This study utilizes AlphaMissense to map pathogenicity patterns across the GLUT transporter family, revealing that missense mutations are most detrimental in transmembrane domains, pore-lining residues, and the central cavity, while variations in pathogenicity across the family suggest the influence of functional redundancy and physiological essentiality.
ProteoDUDes is an open-source tool that enhances the accuracy of taxonomic profiling in metaproteomics by processing results from popular annotation tools to significantly reduce false positive rates, thereby enabling more reliable identification of functionally active organisms in complex samples.
The paper introduces GAZE, a physics-informed graph neural network that integrates gene expression, enzyme functional embeddings, and metabolite descriptors to achieve accurate zero-shot prediction of metabolite concentrations across diverse biological contexts without requiring metabolite-specific training.
WattmaMod is a novel deep learning framework that leverages self-supervised pretraining, wavelet-guided encoding, and dynamic cross-attention to enable robust, high-resolution, and extensible profiling of diverse RNA modifications from nanopore direct RNA sequencing data, even with limited labeled resources.
MCD Stitcher is an open-source Python tool that converts proprietary Imaging Mass Cytometry (.mcd) files into interoperable OME-TIFF formats with automated whole-slide stitching, enabling large-scale spatial analysis on standard workstations without vendor-specific software.
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.