AIMC Topic: DNA Copy Number Variations

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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...
Algorithms High-Throughput Nucleotide Sequencing Exome Sequencing Exome Deep Learning DNA Copy Number Variations Reproducibility of Results
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Multiclass Cancer Prediction Based on Copy Number Variation Using Deep Learning.

Computational intelligence and neuroscience Jun 9, 2022
DNA copy number variation (CNV) is the type of DNA variation which is associated with various human diseases. CNV ranges in size from 1 kilobase to several megabases on a chromosome. Most of the computational research for cancer classification is tra...
Humans Neural Networks, Computer Machine Learning DNA Copy Number Variations Neoplasms Deep Learning
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TADA-a machine learning tool for functional annotation-based prioritisation of pathogenic CNVs.

Genome biology Mar 1, 2022
Few methods have been developed to investigate copy number variants (CNVs) based on their predicted pathogenicity. We introduce TADA, a method to prioritise pathogenic CNVs through assisted manual filtering and automated classification, based on an e...
Genomics DNA Copy Number Variations Machine Learning
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A scalable artificial intelligence platform that automatically finds copy number variations (CNVs) in journal articles and transforms them into a database: CNV extraction, transformation, and loading AI (CNV-ETLAI).

Computers in biology and medicine Feb 24, 2022
BACKGROUND: Although copy number variations (CNVs) are infrequent, each anomaly is unique, and multiple CNVs can appear simultaneously. Growing evidence suggests that CNVs contribute to a wide range of diseases. When CNVs are detected, assessment of ...
DNA Copy Number Variations Humans Artificial Intelligence Databases, Factual Genomics Algorithms
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Investigating Deep Learning Based Breast Cancer Subtyping Using Pan-Cancer and Multi-Omic Data.

IEEE/ACM transactions on computational biology and bioinformatics Feb 3, 2022
Breast Cancer comprises multiple subtypes implicated in prognosis. Existing stratification methods rely on the expression quantification of small gene sets. Next Generation Sequencing promises large amounts of omic data in the next years. In this sce...
Humans Machine Learning Deep Learning DNA Copy Number Variations Supervised Machine Learning Female Breast Neoplasms
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MFmap: A semi-supervised generative model matching cell lines to tumours and cancer subtypes.

PloS one Dec 16, 2021
Translating in vitro results from experiments with cancer cell lines to clinical applications requires the selection of appropriate cell line models. Here we present MFmap (model fidelity map), a machine learning model to simultaneously predict the c...
DNA Copy Number Variations Glioblastoma Tumor Cells, Cultured Cell Proliferation Apoptosis Biomarkers, Tumor Antineoplastic Agents Computational Biology Gene Expression Regulation, Neoplastic Gene Expression Profiling Algorithms Female Breast Neoplasms Humans Machine Learning
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Machine learning modeling of genome-wide copy number alteration signatures reliably predicts IDH mutational status in adult diffuse glioma.

Acta neuropathologica communications Dec 4, 2021
Knowledge of 1p/19q-codeletion and IDH1/2 mutational status is necessary to interpret any investigational study of diffuse gliomas in the modern era. While DNA sequencing is the gold standard for determining IDH mutational status, genome-wide methyla...
Whole Genome Sequencing Isocitrate Dehydrogenase Machine Learning Biomarkers, Tumor Glioma DNA Copy Number Variations Brain Neoplasms Humans
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Deep learning prediction of attention-deficit hyperactivity disorder in African Americans by copy number variation.

Experimental biology and medicine (Maywood, N.J.) Jul 7, 2021
Current understanding of the underlying molecular network and mechanism for attention-deficit hyperactivity disorder (ADHD) is lacking and incomplete. Previous studies suggest that genomic structural variations play an important role in the pathogene...
Black or African American Attention Deficit Disorder with Hyperactivity DNA Copy Number Variations Whole Genome Sequencing Young Adult Male Reproducibility of Results Deep Learning Genetic Predisposition to Disease Case-Control Studies Humans Female
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CNAPE: A Machine Learning Method for Copy Number Alteration Prediction from Gene Expression.

IEEE/ACM transactions on computational biology and bioinformatics Feb 3, 2021
Detection of DNA copy number alteration in cancer cells is critical to understanding cancer initiation and progression. Widely used methods, such as DNA arrays and genomic DNA sequencing, are relatively expensive and require DNA samples at a microgra...
Machine Learning Neoplasms Humans DNA Copy Number Variations Transcriptome Computational Biology
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Sarcoma classification by DNA methylation profiling.

Nature communications Jan 21, 2021
Sarcomas are malignant soft tissue and bone tumours affecting adults, adolescents and children. They represent a morphologically heterogeneous class of tumours and some entities lack defining histopathological features. Therefore, the diagnosis of sa...
Sarcoma Soft Tissue Neoplasms Bone Neoplasms DNA Copy Number Variations Internet Cohort Studies DNA Methylation Algorithms Reproducibility of Results Sensitivity and Specificity Humans Machine Learning
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