949 papers
This paper introduces MHCXGraph, a scalable and interpretable graph-based computational tool that integrates structural information to identify conserved regions in peptide-MHC complexes, thereby overcoming the limitations of sequence-based methods for detecting T cell receptor cross-reactivity in therapeutic and vaccine development.
The paper introduces Synolog, a scalable bioinformatic toolkit that leverages synteny-based analysis to identify orthologs, synteny clusters, retrogenes, and segmental duplications across diverse genomes, demonstrating its utility in characterizing genome architecture, detecting local gene expansions, and reconstructing chromosome-level assemblies while highlighting the advantages of synteny over pure sequence similarity.
The paper introduces PERREO, a comprehensive and user-friendly pipeline that overcomes the limitations of standard RNA-seq tools by enabling sensitive, repeat-aware analysis of repetitive element expression across short- and long-read data to facilitate the study of the repeatome's role in cancer and other diseases.
The paper introduces Immunotype, a deep learning-based ensemble predictor that accurately determines HLA class I allotypes directly from complex mass spectrometry-based immunopeptidomics data, thereby enabling rapid and cost-effective HLA typing for large-scale immunotherapy research.
This study systematically benchmarks six ambient RNA removal tools across diverse single-cell platforms, revealing that while CellBender and SoupX offer reliable denoising, tools like scAR and CellClear critically fail by generating artificial counts and spurious cell types, thereby establishing count matrix integrity as a paramount criterion for tool selection.
The paper introduces OmniCleave, a scalable, structure-aware geometric graph learning framework that outperforms existing methods in modeling protease-substrate specificity by integrating multi-scale structural graphs and higher-order relational topology, thereby enabling the discovery of novel substrates and cleavage sites across diverse protease families.
This paper introduces a general-purpose computational model that leverages long-read sequencing data to accurately quantify genome-wide tandem repeat instability by characterizing read-to-consensus deviations, revealing that instability is primarily driven by repeat composition rather than length and enabling the detection of significant mosaicism in pathogenic expansions.
The paper introduces BrightEyes-FFS, an open-source Python-based platform featuring a user-friendly GUI and automated Jupyter Notebook integration to enable comprehensive analysis of high-dimensional fluorescence fluctuation spectroscopy data from small detector arrays.
This paper presents an open-source, statistically rigorous workflow for analyzing complex mass spectrometry imaging experiments, demonstrating through case studies and simulations how critical decisions regarding signal processing, region selection, and statistical modeling impact the detection of differentially abundant analytes.
TopicVI is a deep interpretable model that integrates prior biological knowledge with data-driven refinement via optimal transport to discover context-specific gene programs, outperforming existing methods in benchmarking and successfully revealing convergent tumor states in glioblastoma.
This paper extends contrastive principal component analysis by introducing kernel-weighted spatial (k-ρPCA) and functional (f-ρPCA) methods that unify spatial and functional data analysis within a single mathematical framework, demonstrated through applications in genomics.
DIANA is a multi-task neural network that leverages unitig abundances from ancient metagenomic data to accurately predict sample metadata and generalize to unseen categories, offering a robust, reference-free solution for quality control and discovery in the field.
By integrating human-virus protein-protein interaction maps with residue-resolved contact data, this study reveals that positive and negative selection signatures exhibit distinct spatial patterns across virus-targeted host proteins, with positively selected residues clustering more prominently on interfaces shared between viral and endogenous partners, thereby highlighting these "mimic-targeted" sites as focal points of adaptive evolution.
CoPhaser is a versatile, biologically informed variational autoencoder that disentangles context-dependent periodic trajectories from other sources of cellular variability in single-cell RNA sequencing data, enabling the accurate reconstruction and analysis of diverse biological cycles such as the cell cycle, circadian rhythms, and developmental clocks across various tissues and disease states.
This study reveals that AlphaFold's assembly of protein-protein complexes is primarily driven by monomer-level structural geometry and interface complementarity rather than inter-protein coevolution, identifying structural plasticity at immune interfaces as the main bottleneck for improving antigen-antibody prediction accuracy.
This paper introduces a GPU-accelerated quaternion Fourier transform framework that encodes DNA as a quaternion-valued signal to enable alignment-free genomic analysis, revealing universal structural periodicities like the helical repeat and species-specific features such as nucleosome positioning through multi-channel spectral fingerprints while achieving whole-genome processing speeds of under one second on commodity hardware.
This paper introduces MAG-E, a simulation-based framework for end-to-end evaluation of metagenome-assembled genome (MAG) pipelines, which reveals that while metaSPAdes and COMEBin generally outperform alternatives in the human gut microbiome, current tools struggle with prophages and shared contigs, and quality control metrics like CheckM2 often misestimate genome quality.
This study introduces the Germline VCF Annotator, a lightweight pipeline that converts raw VCF files into reproducible, human-readable tables with standardized annotations and read-evidence quality control, enabling robust analysis of germline variant burdens in normal colon crypts where no age-related trends in DNA damage response loci were observed.
PoolParty is a Python package that streamlines the design of complex DNA sequence libraries through a flexible, graph-based API featuring over 50 built-in operations and comprehensive design documentation.
The paper introduces the Inner Ear Knowledge Base (IEKB), an open-access resource that unifies curated gene-phenotype-disease associations, cochlear interactions, Bayesian candidate prioritization, explainable support relations, and a multi-entity scientific network to advance inner-ear genetics research through automated curation and interactive exploration tools.