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.
This paper introduces the Complete Ancestral Reconstruction for Pangenomes (CARP) problem to bridge the gap between comparative genomics and pangenomics by overcoming the theoretical and practical limitations of existing rearrangement models when applied to complex pangenomic data.
This paper introduces two structure-free machine learning models that accurately predict pairwise preferences between compounds and targets by comparing chemical structures and protein sequences, achieving high accuracy in ranking without requiring conformational analysis or protein structure data.
The paper introduces PREpiBind, a dual-stream framework that systematically evaluates ten protein representations for pMHC-II binding prediction, revealing that while protein language models generally achieve the highest performance, the optimal representation choice depends on the specific prediction scenario and dataset characteristics.
The CalFluxTools R package is an automated pipeline designed to streamline the analysis of high-throughput calcium oscillation data from 384-well plates by generating quality control metrics, performing statistical tests, and predicting compound toxicity, thereby overcoming the challenges of manually processing over 60 kinetic parameters.
ProtPipe2 is a versatile, multi-platform downstream proteomics analysis framework available as both an R package and a web application that unifies quality control, statistical analysis, and visualization workflows for mass spectrometry, Olink, and SomaScan data to enhance reproducibility and flexibility.
OpenAntigens is a free, no-login database that streamlines antigen construct design for the human secreted and cell-surface proteome by integrating diverse structural, topological, and comparative data into a unified, interactive workflow to generate reproducible and cross-reactivity-aware design suggestions.
This paper argues that incomplete reference profiles render bulk deconvolution targets non-identifiable rather than merely difficult to estimate, demonstrating that standard point estimates often lack coverage and can reverse biological conclusions, while proposing a new framework that prioritizes certified precision, coverage, and false-certification metrics over simple shrinkage.
The paper introduces MESIC, a method that integrates curated gene knowledge into a semantic coordinate system to map single-cell expression data into interpretable components, enabling biologically meaningful clustering and annotation of cell types without relying on post-hoc interpretation.
The paper introduces LDDM, a unified 3D generative model that overcomes synthetic accessibility challenges in drug discovery by enabling the rapid design of novel, target-specific small molecules and peptides, which were experimentally validated to achieve high binding affinity and structural accuracy across five protein targets.
This study demonstrates that in virtual spatial transcriptomics, pretrained gene representations primarily enhance the prediction of a gene's mean expression across tissues rather than its spatial variation, revealing that cross-gene generalization is driven more by broad expression transfer than by the recovery of specific spatial patterns.