Genetics

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

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Showing 274-294 of 10,326 articles
Leveraging protein language models for cross-variant CRISPR/Cas9 sgRNA activity prediction.

MOTIVATION: Accurate prediction of single-guide RNA (sgRNA) activity is crucial for optimizing the C...

Deep learning-enhanced development of innovative antioxidant liposomal drug delivery systems from natural herbs.

Free radical-mediated oxidative damage to biological macromolecules, such as DNA and proteins, signi...

Gene therapy and genome editing for lipoprotein disorders.

Genetic factors play a critical role in the development of lipoprotein disorders, which significantl...

Cross modality learning of cell painting and transcriptomics data improves mechanism of action clustering and bioactivity modelling.

In drug discovery, different data modalities (chemical structure, cell biology, quantum mechanics, e...

A deep learning model for diagnosis of inherited retinal diseases.

To evaluate the performance of a multi-input deep learning (DL) model in detecting two common inheri...

Unveiling diagnostic biomarkers and therapeutic targets in lung adenocarcinoma using bioinformatics and experimental validation.

Lung adenocarcinoma (LUAD) is a major challenge in oncology due to its complex molecular structure a...

Identification of exosome-related genes in NSCLC via integrated bioinformatics and machine learning analysis.

Exosomes are crucial in the development of non-small cell lung cancer (NSCLC), yet exosome-associate...

AI-driven genetic algorithm-optimized lung segmentation for precision in early lung cancer diagnosis.

Lung cancer remains the leading cause of cancer-related mortality worldwide, necessitating accurate ...

Integrating machine learning and bioinformatics approaches to identify novel diagnostic gene biomarkers for diabetic mice.

Diabetes is a complex metabolic disorder, and its pathogenesis involves the interplay of genetic, en...

RareNet: a deep learning model for rare cancer diagnosis.

Although significant advances have been made in the early detection of many cancers, challenges rema...

Comprehensive machine learning analysis of PANoptosis signatures in multiple myeloma identifies prognostic and immunotherapy biomarkers.

PANoptosis is closely associated with tumorigenesis and therapeutic response, yet its role in multip...

Management and prediction of river flood utilizing optimization approach of artificial intelligence evolutionary algorithms.

Flooding is a devastating natural disaster that causes fatalities and property damage worldwide. Eff...

Enhanced security for medical images using a new 5D hyper chaotic map and deep learning based segmentation.

Medical image encryption is important for maintaining the confidentiality of sensitive medical data ...

GAINSeq: glaucoma pre-symptomatic detection using machine learning models driven by next-generation sequencing data.

Congenital glaucoma, a complex and diverse condition, presents considerable difficulties in its iden...

Clustering cell nuclei on microgrooves for disease diagnosis using deep learning.

Various diseases including laminopathies and certain types of cancer are associated with abnormal nu...

A Machine Learning Approach to Molecular Initiating Event Prediction Using High-Throughput Transcriptomic Chemical Screening Data.

Improved scalability of high-throughput RNA-sequencing technologies has contributed to their propose...

Transforming heart transplantation care with multi-omics insights.

Heart transplantation (HTx) remains the definitive treatment for patients with end-stage heart disea...

Multi-dimensional annotation of porcine variants using genomic and epigenomic features in pigs.

BACKGROUND: Investigating the functional impact of genomic variants is essential to uncover the mole...

Chimeric mis-annotations of genes remain pervasive in eukaryotic non-model organisms.

BACKGROUND: Accurate annotation of protein-coding genes is critical for genome analysis in non-model...

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