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.
The paper introduces DipGenie, a scalable tool that jointly optimizes genotyping and phasing on pangenome graphs using a biologically motivated recombination budget, achieving significantly lower switch error rates and higher structural variant F1-scores compared to existing graph-based methods.
WSInsight is an open, cloud-native platform that enables scalable, agent-callable single-cell phenotyping of whole-slide H&E images from diverse storage sources, delivering validated, standards-compliant outputs for translational tumor microenvironment research.
LIVIA is a freely available, browser-based tool that locally computes local confidence metrics, identifies interface residues, and visualizes predicted protein-protein interactions across multiple platforms using an interactive 3D viewer and exportable scripts for ChimeraX and PyMOL.
This study develops a machine learning framework to impute cross-platform proteomic data between SomaScan and Olink, thereby resolving persistent non-replication issues, enabling the recovery of platform-exclusive signals, and establishing a protein fidelity index to enhance the reliability of epidemiological biomarker discovery.
This study utilizes a cross-dataset integrative transcriptomic analysis to identify oxidative stress and inflammation-related hub genes in Parkinson's disease and reveals how specific bioactive food compounds may modulate these gene networks through nutrigenomic interventions.
This paper introduces **bcrnnoise**, an open-source Python framework that unifies deterministic drift, Gaussian fluctuations, and additive sporadic jumps into a single stochastic differential equation model to efficiently generate accurate transcription traces with up to two orders of magnitude faster computational speed than exact stochastic sampling.
SaVanache is a multi-resolution visualization tool that enables efficient, real-time exploration and intuitive one-to-many comparison of complex pangenome variation graphs by preprocessing GFA files into optimized indexes and using specialized glyphs to highlight structural variations relative to a linear pivot genome.
This paper presents a statistical destriping method for 10x Genomics VisiumHD data that models bin counts using nuclei segmentation and a regularized generalized linear model to effectively remove multiplicative striping artifacts while preserving large-scale biological signals, outperforming existing normalization approaches.
The paper introduces SLiMNet, a deep learning model leveraging protein large language model embeddings and contrastive learning to predict functional similarities between short linear motifs (SLiMs), thereby enabling the functional annotation of previously uncharacterized motifs and providing comprehensive atlases of potential functional pairs for the research community.
ProtSpace is a privacy-preserving, browser-based web application that enables the interactive visualization and systematic exploration of protein language model embedding spaces, revealing complex functional and structural relationships beyond traditional sequence similarity through integrated 3D structure viewing and multi-label annotations.