994 papers
The paper proposes scRGCL, a neighbor-aware graph contrastive learning framework that enhances single-cell RNA sequencing clustering by integrating cluster-level guidance and a re-weighting strategy to preserve intra-cluster compactness, thereby outperforming state-of-the-art methods across multiple datasets.
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."
SpatialFusion is a lightweight multimodal foundation model that integrates histopathology, gene expression, and pathway activity to identify biologically coherent spatial niches, successfully uncovering pre-malignant and stage-predictive microenvironments in colorectal and lung cancers.
InSTaPath is a multimodal topic modeling framework that integrates spatial transcriptomics and histology images by converting image features into discrete "words" to jointly infer interpretable latent topics linking gene expression programs with tissue morphology, thereby improving spatial domain identification and revealing biologically meaningful structure-function relationships.
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.
This paper introduces PhyloCRISP, a software tool that employs fine-grained dissimilarity measures like quartet and transfer distances to compute median consensus trees, thereby improving resolution and accuracy over traditional majority-rule methods, particularly for large datasets with low to moderate phylogenetic signal.
The paper introduces drFrankenstein, an automated and robust pipeline designed to streamline the generation of accurate AMBER force field parameters for non-canonical amino acids, thereby overcoming existing bottlenecks in molecular dynamics simulations of modified proteins.
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.
This paper introduces MutationNetwork, a graph-based framework that integrates long-range intrachromosomal interactions with local genomic overlaps to construct mutation-centric networks, enabling the effective clustering of breast cancer subtypes and the prioritization of non-coding driver mutations through network-level impact analysis.
PalmaClust is a novel graph-fusion framework that leverages the tail-sensitive Palma ratio to construct complementary KNN graphs, enabling the robust and statistically grounded detection of ultra-rare cell populations in scRNA-seq data with significantly improved sensitivity and accuracy compared to existing methods.
VICAST is an integrated software toolkit designed to streamline viral passage studies by combining semi-automated genome annotation with manual curation and optimized low-frequency variant calling, offering superior speed and accuracy compared to existing tools for diverse viral families.
By integrating transcriptomic data from 1,558 lung tumors, this study constructs a unified molecular atlas that redefines lung cancer as a structured continuum of nine biologically distinct states transcending traditional histological classifications, thereby revealing novel subtypes and state-specific therapeutic vulnerabilities.
This paper introduces SLAB, an efficient sweep line algorithm based on PBWT that identifies width-maximal haplotype block cores to reveal population genetic insights and selection signals complementary to traditional IBD rate analyses.
The paper introduces IASO, a sequence-centric generative framework that enables the de novo design of diverse therapeutic antibodies and multi-specific engagers directly from antigen sequences, successfully overcoming drug resistance and demonstrating clinical-grade developability without relying on high-resolution structural data.
The paper introduces enCORE, a computational framework that utilizes enhancer-enhancer interaction networks to identify clustered open regulatory elements (COREs) from single-cell ATAC-seq data, thereby enabling the deciphering of context-dependent epigenetic programs and the discovery of disease-relevant regulators in processes like hematopoiesis and colorectal cancer.
This paper introduces a novel, linguistics-inspired algorithm that improves RNA-binding protein motif discovery by integrating sequence context information and applying lexical, syntactic, and semantic k-mer properties, demonstrating superior accuracy and ranking performance compared to existing methods.
ChromBERT is a BERT-based model pre-trained on diverse human chromatin annotations that successfully identifies biologically meaningful chromatin state motifs and achieves high performance in predicting gene expression, cell types, and 3D genome features.
The paper introduces K2Rmini, a Rust-based tool that utilizes minimizer-based sketching and SIMD acceleration to efficiently filter long sequencing reads against large sets of k-mers at high speeds without requiring exhaustive pre-indexing.
This study demonstrates that the evolutionary history of enzymatic folds is encoded within global metabolic networks, revealing that early metabolism was dominated by -proteins linked to cofactor utilization and that metabolic adaptation to oxygen was driven primarily by the reuse of existing folds rather than the emergence of new ones.