1197 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 Cavebear, a machine learning framework that leverages reference scRNA-seq time-series data from one species or condition to accurately infer pseudotime and map biological aging or disease progression in query contexts lacking reliable temporal labels.
This research demonstrates that the Hamiltonian Auto Decomposition Optimisation Framework (HADOF) can overcome current NISQ hardware limitations to successfully assemble a 7.1 million base pair *Pseudomonas aeruginosa* genome on real quantum hardware, achieving a 99.348% genome fraction and proving the viability of scalable quantum optimisation for large-scale scientific workloads.
This paper introduces PLI-Parallax, a comprehensive dataset that integrates predicted and experimental protein-ligand structures with calibrated accuracy labels and rigorous evaluation splits, enabling the estimation of prediction reliability through method agreement even in the absence of experimental ground truth.
scAtlasPy is a novel, disk-resident computing framework that overcomes the memory limitations of standard workstations, enabling full-resolution analysis of massive single-cell atlases (e.g., 100 million cells) with significantly lower memory usage and higher processing speeds compared to existing state-of-the-art platforms.
This study identifies a reproducible, higher-order "functional organisation" in vascular disease that transcends individual gene or pathway variations, revealing that cardiovascular remodelling across diverse conditions and cell types is driven by a coordinated, dynamic rebalancing of six conserved biological functions.
This paper introduces AnnoAudit, a marker-based protocol that reveals systematic annotation errors in widely used single-cell atlases, such as the CEREBRI traumatic brain injury resource, where the majority of cells labeled as glutamatergic neurons are actually non-neuronal, leading to significant biological artifacts that are corrected upon re-annotation.
bioq is an open-source, lightweight command-line interface that unifies access to a fleet of 38+ containerized AI drug-discovery tools via a serverless gateway, enabling researchers and automated agents to execute complex workflows from a laptop without managing local hardware or conflicting software dependencies.
This paper introduces Titra, an end-to-end deep learning workflow that automates the entire virus titration process—from well detection and plaque segmentation to PFU/mL estimation—demonstrating strong agreement with manual annotations across diverse viral species and plate formats.
This paper dissects the Boltz-1 co-folding model to reveal that structural information is organized across three distinct streams—single, intra-chain, and inter-chain representations—that follow a Mix-Compress-Refine trajectory, where intra-chain geometry is largely pre-conditioned while inter-chain arrangements are progressively constructed and reconciled by the diffusion module.
This study utilizes bulk RNA-Seq analysis of keloid and matched normal skin tissues to demonstrate that accounting for cell type heterogeneity reveals distinct differences in fibroblast and immune cell enrichment, their specific interactions, and key gene expression signatures underlying keloid disease.