Genetics

CV.eDNA: A hybrid approach to invertebrate biomonitoring using computer vision and DNA metabarcoding

Automated invertebrate classification using computer vision has shown significant potential to improve specimen processing efficiency. However, challenges such as invertebrate diversity and morphological similarity among taxa can make it difficult to infer fine-scale taxonomic classifications using computer vision. As a result, many invertebrate computer vision models are forced to make classifica...

Decoding the interconnected splicing patterns of hepatitis B virus and host using large language and deep learning models

Hepatitis B virus (HBV) infection causes approximately one million deaths annually and remains a major driver of hepatocellular carcinoma. Despite its compact 3.2-kb genome, HBV exhibits extensive alternative splicing. Functionally, HBV splice variants contribute to immune evasion and reduce the likelihood of achieving a functional cure. Here, we show that HBV splicing efficiency—quantified from 2...

Decoding Helicobacter pylori Resistance: Machine Learning–Enhanced Prediction of Antibiotic Susceptibility using Whole-Genome Sequencing

Helicobacter pylori is a significant risk factor for gastric cancer, peptic ulcers, and MALT lymphoma. Rising antibiotic resistance rates complicate t...

Extracellular Vesicle Gene Expression Enables Sensitive Detection of Colorectal Neoplasia

Extracellular vesicles (EVs), including exosomes, are emerging as promising carriers of disease-specific biomarkers due to their molecular cargo refle...

Toehold-VISTA: A machine learning approach to decipher programmable RNA sensor-target interactions

RNA-based biosensors have emerged as essential tools in synthetic biology and diagnostics, enabling precise and programmable responses to diverse RNA ...

A modular pipeline for evidence-integrated genome annotation across species: a case study on Schmidtea mediterranea

Despite advancements in genome annotation tools, challenges persist for non-classical model organisms with limited genomic resources, such as Schmidte...

Parabricks: GPU Accelerated Universal Pan-Instrument Genomics Analysis Software Suite

Next-generation sequencing (NGS) has transformed genomics, enabling breakthroughs in biotechnology, healthcare, and pharmaceuticals. However, exponent...

Improving polygenic risk prediction performance through integrating electronic health records by phenotype embedding

Large-scale biobanks provide comprehensive electronic health records (EHRs) that capture detailed clinical phenotypes, potentially enhancing disease r...

BOLD-GPCRs: A Transformer-Powered App for Predicting Ligand Bioactivity and Mutational Effects Across Class A GPCRs

G protein-coupled receptors (GPCRs) are important targets for drug discovery owing to their ability to respond to a broad range of stimuli and their i...

Tabula Sapiens reveals transcription factor expression, senescence effects, and sex-specific features in cell types from 28 human organs and tissues

The Tabula Sapiens is a reference human cell atlas containing single cell transcriptomic data from more than two dozen organs and tissues. Here we rep...

Benchmarking large language models for cell-free RNA diagnostic biomarker discovery

Large-language models (LLMs) can parse vast amounts of data and generate executable code, positioning them as promising tools for the development of b...

Deep Learning for Molecular and Genomic Characterization of Lung Cancer in Never-Smokers Using Hematoxylin and Eosin-Stained Images

Despite promising results in using deep learning to infer genetic features from histological whole-slide images (WSIs), no prior studies have specific...

Can large language models reliably extract human disease genes from full-text scientific literature?

Manual extraction of high-fidelity gene-disease-phenotype information from human genetics literature is a labor-intensive task that requires trained h...

Quality assessment of RNA 3D structure models using deep learning and intermediate 2D maps

Accurate quality assessment is critical for computational prediction and design of RNA three- dimensional (3D) structures. In this work, we introduce ...

The genetic architecture of the human bZIP interaction network

Generative biology holds the promise to transform our ability to design and understand living systems by creating novel proteins, pathways, and organi...

MultiAlloDriver: a multi-model method to predict and identify cancer driver mutations

A minority of driver mutations in cancer significantly alter protein structure and key functionalities, thereby driving cancer progression. Consequent...

Translating clinical gene sequencing into a foundational representation of tumor subtype

While gene sequencing is routine in cancer care, translating sequences into treatment decisions remains a challenge. Here we introduce MutationProject...

Interpretable Deep Learning Reveals Biologically Relevant Spatial Gene Expression Patterns in Lung Tumors and their Microenvironment

Lung adenocarcinoma (LUAD), the most common subtype of non–small cell lung cancer (NSCLC) exhibits profound histological and molecular heterogeneity, ...

Integrating computational protein structure predictions and genetic dependencies yields an atlas of human multi-protein complexes (AHMPC)

Knowledge of which proteins interact to form functional complexes in cells is essential for understanding molecular mechanisms in biology. Structure p...

Modanovo: A Unified Model for Post-Translational Modification-Aware de Novo Sequencing Using Experimental Spectra from In Vivo and Synthetic Peptides

Post-translational modifications (PTMs) play a central role in cellular regulation and are implicated in numerous diseases. Database searching remains...