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.
The paper introduces RepurAgent, a human-supervised hierarchical multi-agent AI system that successfully automates and supports the entire drug repurposing lifecycle—from hypothesis generation and experimental design to data analysis and candidate refinement—across diverse disease scenarios including Acute Myeloid Leukemia, COVID-19, and Multiple Sulfatase Deficiency.
The paper introduces Surleton, a novel inverse protein folding framework that jointly models backbone geometry and protein surface organization to overcome the limitations of backbone-only representations, thereby significantly improving sequence recovery and modeling balance for both buried and exposed residues.
By employing a phylogenetic comparison of proteomes between cyst-forming Sarcocystidae and non-cyst-forming Eimeriidae parasites, this study identifies distinct conservation patterns of *Toxoplasma gondii* proteins and pinpoints a specific cluster of bradyzoite-conserved proteins as a promising source for discovering novel genes involved in bradyzoite differentiation.
This paper introduces HMCVelo, a deterministic ODE-based framework that leverages Joint-snhmC-seq data to model hydroxymethylation dynamics and infer high-confidence cellular trajectories, demonstrating superior performance over repurposed RNA velocity methods and providing theoretical insights into trajectory resolution within cyclic biochemical systems.
This paper presents a closed-loop in silico framework that integrates generative modeling, molecular simulations, and multi-objective Bayesian optimization to successfully design cell-penetrating peptides with receptor-selective binding profiles, as validated by experimental imaging showing preferential enrichment in CXCR4-positive regions over NRP1-positive regions.
ProNA3D is a unified computational tool and UCSF ChimeraX plug-in designed to analyze protein-nucleic acid and nucleic acid-only interfaces by integrating structural data, AlphaFold3 scoring, and interactive visualization to reveal functional connectivity and interaction modes in both experimental and predicted biomolecular complexes.
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.