AIMC Topic: Exome Sequencing

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Validation of an AI-enabled exome/transcriptome liquid biopsy platform for early detection, MRD, disease monitoring, and therapy selection for solid tumors.

Scientific reports Jul 1, 2025
Effective clinical management of patients with cancer requires highly accurate diagnosis, precise therapy selection, and highly sensitive monitoring of disease burden. Caris Assure is a multifunctional blood-based assay that couples whole exome and w...
Male Middle Aged Neoplasms Machine Learning Female Adult Liquid Biopsy Exome Sequencing Neoplasm, Residual Exome Gene Expression Profiling Transcriptome Early Detection of Cancer Humans Artificial Intelligence
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GNNMutation: a heterogeneous graph-based framework for cancer detection.

BMC bioinformatics Jun 4, 2025
BACKGROUND: When genes are translated into proteins, mutations in the gene sequence can lead to changes in protein structure and function as well as in the interactions between proteins. These changes can disrupt cell function and contribute to the d...
Neoplasms Computational Biology Mutation Humans Exome Sequencing Neural Networks, Computer Algorithms
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TET2 gene mutation status associated with poor prognosis of transition zone prostate cancer: a retrospective cohort study based on whole exome sequencing and machine learning models.

Frontiers in endocrinology Apr 14, 2025
BACKGROUND: Prostate cancer (PCa) in the transition zone (TZ) is uncommon and often poses challenges for early diagnosis, but its genomic determinants and therapeutic vulnerabilities remain poorly characterized.
Machine Learning Prognosis Retrospective Studies Humans Middle Aged Prostatic Neoplasms Mutation DNA-Binding Proteins Aged Biomarkers, Tumor Male Exome Sequencing Proto-Oncogene Proteins Dioxygenases
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Optimizing sequence data analysis using convolution neural network for the prediction of CNV bait positions.

BMC bioinformatics Dec 24, 2024
BACKGROUND: Accurate prediction of copy number variations (CNVs) from targeted capture next-generation sequencing (NGS) data relies on effective normalization of read coverage profiles. The normalization process is particularly challenging due to hid...
High-Throughput Nucleotide Sequencing Exome Sequencing Humans Neural Networks, Computer Data Analysis Algorithms Sequence Analysis, DNA DNA Copy Number Variations
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A deep learning model for prediction of autism status using whole-exome sequencing data.

PLoS computational biology Nov 8, 2024
Autism is a developmental disability. Research demonstrated that children with autism benefit from early diagnosis and early intervention. Genetic factors are considered major contributors to the development of autism. Machine learning (ML), includin...
Exome Sequencing Multifactorial Inheritance Exome Genetic Predisposition to Disease Computational Biology Autistic Disorder Deep Learning Child Humans Neural Networks, Computer
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Improving the Detection of Potential Cases of Familial Hypercholesterolemia: Could Machine Learning Be Part of the Solution?

Journal of the American Heart Association Jun 15, 2024
BACKGROUND: Familial hypercholesterolemia (FH), while highly prevalent, is a significantly underdiagnosed monogenic disorder. Improved detection could reduce the large number of cardiovascular events attributable to poor case finding. We aimed to ass...
United Kingdom Exome Sequencing Proprotein Convertase 9 Mutation Apolipoprotein B-100 Female Middle Aged Genetic Testing Receptors, LDL Adult Genetic Predisposition to Disease Humans Hyperlipoproteinemia Type II Male Predictive Value of Tests Machine Learning
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Exome sequence analysis identifies rare coding variants associated with a machine learning-based marker for coronary artery disease.

Nature genetics Jun 11, 2024
Coronary artery disease (CAD) exists on a spectrum of disease represented by a combination of risk factors and pathogenic processes. An in silico score for CAD built using machine learning and clinical data in electronic health records captures disea...
Genetic Variation Exome Sequencing Exome Genetic Predisposition to Disease Polymorphism, Single Nucleotide Coronary Artery Disease Machine Learning Female Humans Genome-Wide Association Study
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Polishing copy number variant calls on exome sequencing data via deep learning.

Genome research Jun 13, 2022
Accurate and efficient detection of copy number variants (CNVs) is of critical importance owing to their significant association with complex genetic diseases. Although algorithms that use whole-genome sequencing (WGS) data provide stable results wit...
DNA Copy Number Variations High-Throughput Nucleotide Sequencing Exome Sequencing Algorithms Exome Reproducibility of Results Deep Learning
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Recommendations for next generation sequencing data reanalysis of unsolved cases with suspected Mendelian disorders: A systematic review and meta-analysis.

Genetics in medicine : official journal of the American College of Medical Genetics May 14, 2022
PURPOSE: The study aimed to determine the diagnostic yield, optimal timing, and methodology of next generation sequencing data reanalysis in suspected Mendelian disorders.
Humans Artificial Intelligence High-Throughput Nucleotide Sequencing Exome Sequencing
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One Cell At a Time (OCAT): a unified framework to integrate and analyze single-cell RNA-seq data.

Genome biology Apr 20, 2022
Integrative analysis of large-scale single-cell RNA sequencing (scRNA-seq) datasets can aggregate complementary biological information from different datasets. However, most existing methods fail to efficiently integrate multiple large-scale scRNA-se...
Cluster Analysis Exome Sequencing Single-Cell Analysis Machine Learning RNA-Seq Algorithms Sequence Analysis, RNA Gene Expression Profiling
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