856 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 identifies epigenetically constrained basal astrocytes in the prefrontal cortex as a key vulnerability factor in Down syndrome-associated Alzheimer's disease, characterized by a loss of homeostatic functions and diminished responsiveness to stress and inflammatory signals rather than classical reactive activation.
This paper presents a reproducible, open analytical pipeline combining a fine-tuned Cellpose-SAM model for cellular structures and an empirical Bayes approach for nanoparticles to achieve fully quantitative 3D reconstruction of nanoparticle distribution and cellular morphology within tumor spheroids using volume electron microscopy.
This study presents the first comprehensive genome-wide identification and characterization of 237 NAC transcription factor genes in *Cynodon dactylon*, revealing their phylogenetic diversity, tissue-specific expression patterns, and distinct upregulation or downregulation profiles in response to drought, heat, salt, and submergence stresses, thereby establishing a foundation for breeding stress-resilient bermudagrass.
This study demonstrates that mutation-induced biophysical destabilization of protein folding and binding interactions is a key contributor to cancer-driving potential, revealing a strong positive correlation between structural perturbations and oncogenicity across the human structural protein interactome.
The paper introduces Buscar, an open-source Python method for high-content screening that improves hit calling by leveraging full single-cell heterogeneity to define morphology signatures and quantify both compound efficacy and specificity, thereby overcoming the limitations of traditional aggregate statistics.
By integrating large-scale targeted genome mining of approximately 2 million bacterial genomes with structure-guided modeling, this study uncovers over 900 uncharacterized 7-deazapurine biosynthetic gene clusters and elucidates the enzymatic mechanisms driving their structural diversification.
DOME Copilot is a scalable, large language model-based solution designed to enhance the transparency and reproducibility of artificial intelligence in life sciences by automatically extracting structured method reports from manuscripts to interpret and annotate global AI literature.
This study addresses the clinical interpretation gap for in-frame indels by calibrating eight computational predictors using a high-confidence dataset and a statistical framework to establish ACMG/AMP-compliant score thresholds, demonstrating their measurable utility while highlighting their currently lower performance compared to missense variant tools.
This study demonstrates that in heterogeneous pan-cancer cohorts treated with immune checkpoint inhibitors, clinical variables significantly outperform and overshadow genomic features like tumor mutational burden in predicting survival, revealing fundamental structural limits to the added value of integrating whole-genome sequencing data into current predictive models.
The paper introduces LagCI, a computational framework that overcomes the limitations of sparse sampling and existing methods to infer robust, time-lagged causal relationships from dense multi-omic time-series data, successfully identifying a vast network of molecular interactions that orchestrate metabolic and immune responses.