Genetics

Latest AI and machine learning research in genetics for healthcare professionals.

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Deep learning-based image quantification of epithelial cell shapes and its application to polycystic kidney disease

Cell shape is a fundamental determinant of tissue architecture and organ function. In epithelial tis...

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 impro...

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 maj...

Extracellular Vesicle Gene Expression Enables Sensitive Detection of Colorectal Neoplasia

Extracellular vesicles (EVs), including exosomes, are emerging as promising carriers of disease-spec...

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 ...

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 organism...

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

Next-generation sequencing (NGS) has transformed genomics, enabling breakthroughs in biotechnology, ...

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 cl...

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 ...

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, positionin...

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-s...

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...

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- dimens...

The genetic architecture of the human bZIP interaction network

Generative biology holds the promise to transform our ability to design and understand living system...

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 functionaliti...

Translating clinical gene sequencing into a foundational representation of tumor subtype

While gene sequencing is routine in cancer care, translating sequences into treatment decisions rema...

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 p...

Impact of Data Quality on Deep Learning Prediction of Spatial Transcriptomics from Histology Images

Spatial transcriptomics technologies enable high-throughput quantification of gene expression at spe...

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