991 papers
The paper introduces ChiMER, a novel graph-based framework that integrates chromatin architecture with splicing graphs to systematically detect low-abundance chimeric enhancer RNAs, demonstrating superior sensitivity over conventional methods and revealing their association with active regulatory environments and R-loop structures.
The paper introduces STpath, a framework that leverages cancer-specific XGBoost models to translate uninterpretable histopathology foundation model embeddings into biologically meaningful cellular and molecular features, thereby enabling their use in clinical outcome studies.
This study presents the largest harmonized single-cell transcriptomic atlas of *Macaca fascicularis*, integrating over 2.5 million cells across 43 organs and leveraging a human foundation model to enable scalable cross-species comparisons that improve target qualification, mechanistic toxicity interpretation, and the reduction of non-human primate use in preclinical research.
ProteinSage is a data-efficient protein language modeling framework that leverages explicit structural constraints, such as structure-guided masking and causal objectives, to learn transferable representations that outperform sequence-only models and successfully identify novel microbial rhodopsin homologs.
The paper introduces SNMF, a novel reference-free deconvolution method for spatial transcriptomics that leverages spatial correlations and GPU acceleration to achieve ultrafast, highly accurate cell-type composition analysis, outperforming existing state-of-the-art tools.
By integrating AlphaFold-3 modeling with molecular dynamics simulations, this study reveals how RHEB binding induces global structural and energetic remodeling of the mTORC1 complex to stabilize ATP coordination and preorganize the kinase for catalysis.
The paper introduces evedesign, a unified open-source framework and web interface that overcomes current limitations in protein engineering by enabling flexible, method-agnostic, and iterative multi-objective biosequence design workflows accessible to both experts and non-experts.
The paper introduces GAP-MS, an automated proteogenomic pipeline that utilizes mass spectrometry evidence to systematically validate and improve gene model predictions across nine major crop species, successfully filtering errors and identifying hundreds of previously missing protein-coding genes.
StrucTTY is a self-contained, terminal-native tool that enables real-time, interactive visualization and comparative analysis of protein structures directly within text-only environments, addressing a critical gap in terminal-based structural biology workflows.
This study presents a structure-guided workflow that successfully identified, classified, and standardized the nomenclature of 1,513 Cytochrome P450 deposits in the Protein Data Bank, resulting in the first rigorously curated, structure-linked registry of these enzymes.
The paper introduces SELFormerMM, a multimodal framework that integrates SELFIES, structural graphs, textual descriptions, and knowledge graph data to generate superior molecular representations for drug discovery, outperforming existing unimodal models across various property prediction tasks.
This paper introduces the Super Bloom Filter, a novel variant that combines minimizer-based super-k-mer grouping with the findere scheme to significantly improve cache locality, reduce memory transfers, and minimize false positives for streaming k-mer queries in bioinformatics applications.
STiLE is a robust, image-independent automated tool that assigns cells to their respective tissue cores in Tissue Microarrays using only centroid coordinates, thereby eliminating manual bottlenecks and ensuring high-accuracy dearraying across diverse spatial transcriptomics platforms.
This paper proposes a deep learning-based, semantic-aware anomaly detection method for smart capsule endoscopy that significantly reduces power and illumination requirements while maintaining high detection accuracy, thereby extending battery life by over 43%.
ABAG-Rank is a deep neural network based on the DeepSets architecture that significantly improves the selection of accurate antibody-antigen complex structures from AlphaFold ensembles by leveraging geometric descriptors and confidence scores to outperform existing internal and external scoring methods.
PhyloRNA is a curated meta-database that bridges RNA secondary structures with comprehensive phylogenetic annotations and structural descriptors, enabling large-scale comparative and evolutionary analyses of RNA molecules.
The paper introduces noHiC, a reference-guided scaffolding pipeline that utilizes a pangenome graph-based algorithm to generate personalized synthetic references, enabling the rapid and accurate assembly of plant genomes into highly contiguous structures without the need for costly Hi-C sequencing.
RiboBA is a novel bias-aware probabilistic framework that improves the robust identification of non-canonical open reading frames across diverse ribosome profiling protocols by explicitly modeling and correcting for protocol-induced artifacts, thereby achieving superior accuracy and sensitivity compared to existing methods.
ST-PARM is an inference-time alignment framework that utilizes a reward-calibrated, uncertainty-aware preference loss and smooth Tchebycheff scalarization to steer frozen protein language models toward generating diverse, Pareto-optimal candidates across competing objectives while robustly handling noisy evaluators.
This paper introduces G-VEP, a GPU-accelerated framework that utilizes custom CUDA kernels to perform massively parallel database lookups, thereby reducing the I/O-bound annotation bottleneck in clinical whole-genome sequencing pipelines by up to 17-fold while maintaining complete concordance with standard VEP outputs.