1018 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 HARVEST, an agentic AI pipeline that autonomously extracts 3.36 million previously inaccessible bioactivity records from pharmaceutical patents, revealing significant generalization gaps in current AI models when evaluated on this newly recovered data.
The paper introduces PREMISE, a high-performance, quality-aware probabilistic framework that utilizes alignment-based Expectation-Maximization to overcome the limitations of k-mer methods, enabling accurate identification of viral subtypes, estimation of relative abundances, and detection of complex events like reassortment and recombination in Influenza A viruses from metagenomic sequencing data.
The paper introduces Zigo, a novel machine learning-based method that accurately and efficiently infers genetic sex from standard VCF files using a reference-free, threshold-free polynomial equation derived from X-chromosome genotype distributions, demonstrating robust performance across diverse genomic data types and limited variant sets.
This paper introduces a novel method for comparing pangenome diversity by interpolating and extrapolating node counts in colored compacted de Bruijn graphs, utilizing Hill numbers to adjust for varying genome numbers and mitigate the disproportionate influence of rare genomic sequences.
SpeciefAI is a transformer-based model that generates multi-species, mRNA-level antibody framework regions tailored to specific host species and input CDRs, ensuring both high sequence similarity to natural repertoires and optimized codon adaptation for in vivo therapeutic expression.
This paper introduces homology-based metrics to evaluate and compare pangenome graphs (specifically variation graphs and whole genome alignments), proposes transformations between these models, and provides a software package to implement these methods.
This paper introduces faster, space-efficient subset rank data structures requiring less than 3 bits per k-mer, which enable new Pareto-optimal k-mer lookup structures for genomic analysis at the low-memory end of the space-time spectrum.
This paper introduces 10-minimizers, a new class of constant-space sampling schemes that provably achieve lower density than random minimizers in the non-asymptotic regime and offer competitive k-mer retrieval speeds through a specific variant called "spacers."
The paper introduces scTimeBench, a modular benchmarking platform that evaluates nine state-of-the-art single-cell time-series methods across multiple datasets and tasks, revealing that while many achieve high forecast accuracy, they often fail to preserve biological signals and lineage fidelity compared to simple baselines.
MosaicTR is a computational tool that leverages haplotype-tagged long-read sequencing to accurately quantify per-locus somatic instability of tandem repeats, overcoming the limitations of short-read methods to serve as a biomarker for mismatch repair deficiency and a monitor of disease progression in repeat expansion disorders.