AIMC Topic: DNA Copy Number Variations

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Deep learning-driven survival prediction in pan-cancer studies by integrating multimodal histology-genomic data.

Briefings in bioinformatics Mar 4, 2025
Accurate cancer prognosis is essential for personalized clinical management, guiding treatment strategies and predicting patient survival. Conventional methods, which depend on the subjective evaluation of histopathological features, exhibit signific...
Deep Learning Genomics Humans DNA Copy Number Variations Prognosis Survival Analysis Neoplasms
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Constructing a Prognostic Model for Subtypes of Colorectal Cancer Based on Machine Learning and Immune Infiltration-Related Genes.

Journal of cellular and molecular medicine Feb 1, 2025
This study constructed a prognostic model combining machine learning-based immune infiltration-related genes in each CRC subtype. We used publicly accessible gene expression data and clinical information on colorectal cancer patients. Integrated bioi...
Gene Regulatory Networks Computational Biology Humans Gene Expression Regulation, Neoplastic Machine Learning DNA Copy Number Variations Algorithms Colorectal Neoplasms Male Biomarkers, Tumor Prognosis Gene Expression Profiling ROC Curve Female
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Building a Risk Scoring Model for ARDS in Lung Adenocarcinoma Patients Using Machine Learning Algorithms.

Journal of cellular and molecular medicine Dec 1, 2024
Lung adenocarcinoma (LUAD), the predominant form of non-small-cell lung cancer, is frequently complicated by acute respiratory distress syndrome (ARDS), which increases mortality risks. Investigating the prognostic implications of ARDS-related genes ...
Humans Machine Learning Algorithms Biomarkers, Tumor Male Risk Assessment Gene Expression Profiling Prognosis Female Risk Factors DNA Copy Number Variations Lung Neoplasms Mutation Gene Expression Regulation, Neoplastic Adenocarcinoma of Lung Respiratory Distress Syndrome
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Inferring tumor purity using multi-omics data based on a uniform machine learning framework MoTP.

Briefings in bioinformatics Nov 22, 2024
Existing algorithms for assessing tumor purity are limited to a single omics data, such as gene expression, somatic copy number variations, somatic mutations, and DNA methylation. Here we proposed the machine learning Multi-omics Tumor Purity predict...
DNA Methylation DNA Copy Number Variations Bayes Theorem Neural Networks, Computer Machine Learning Algorithms Computational Biology Multiomics Neoplasms Humans Genomics
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TransCell: In Silico Characterization of Genomic Landscape and Cellular Responses by Deep Transfer Learning.

Genomics, proteomics & bioinformatics Jul 3, 2024
Gene expression profiling of new or modified cell lines becomes routine today; however, obtaining comprehensive molecular characterization and cellular responses for a variety of cell lines, including those derived from underrepresented groups, is no...
Computational Biology DNA Copy Number Variations Deep Learning Cell Line, Tumor Genomics Neoplasms Gene Expression Profiling Humans Computer Simulation
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Identify gestational diabetes mellitus by deep learning model from cell-free DNA at the early gestation stage.

Briefings in bioinformatics Nov 22, 2023
Gestational diabetes mellitus (GDM) is a common complication of pregnancy, which has significant adverse effects on both the mother and fetus. The incidence of GDM is increasing globally, and early diagnosis is critical for timely treatment and reduc...
DNA Copy Number Variations Diabetes, Gestational beta-Defensins Deep Learning Humans Pregnancy Outcome Pregnancy Cell-Free Nucleic Acids Female
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The NHGRI-EBI GWAS Catalog: knowledgebase and deposition resource.

Nucleic acids research Jan 6, 2023
The NHGRI-EBI GWAS Catalog (www.ebi.ac.uk/gwas) is a FAIR knowledgebase providing detailed, structured, standardised and interoperable genome-wide association study (GWAS) data to >200 000 users per year from academic research, healthcare and industr...
Genome-Wide Association Study Mice Polymorphism, Single Nucleotide Knowledge Bases National Human Genome Research Institute (U.S.) United States DNA Copy Number Variations Software Phenotype Animals Humans
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DeepCNV: a deep learning approach for authenticating copy number variations.

Briefings in bioinformatics Sep 2, 2021
Copy number variations (CNVs) are an important class of variations contributing to the pathogenesis of many disease phenotypes. Detecting CNVs from genomic data remains difficult, and the most currently applied methods suffer from an unacceptably hig...
False Positive Reactions Disease Humans Area Under Curve Benchmarking Deep Learning Datasets as Topic ROC Curve Genome, Human DNA Copy Number Variations
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A novel machine learning approach (svmSomatic) to distinguish somatic and germline mutations using next-generation sequencing data.

Zoological research Mar 18, 2021
Somatic mutations are a large category of genetic variations, which play an essential role in tumorigenesis. Detection of somatic single nucleotide variants (SNVs) could facilitate downstream analysis of tumorigenesis. Many computational methods have...
Mutation High-Throughput Nucleotide Sequencing Animals Humans Computational Biology Machine Learning Algorithms Gene Expression Regulation, Neoplastic Neoplasms DNA Copy Number Variations
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Differentiation of rare brain tumors through unsupervised machine learning: Clinical significance of in-depth methylation and copy number profiling illustrated through an unusual case of IDH wildtype glioblastoma.

Clinical neuropathology Jan 1, 2021
Methylation profiling has become a mainstay in brain tumor diagnostics since the introduction of the first publicly available classification tool by the German Cancer Research Center in 2017. We demonstrate the capability of this system through an ex...
Unsupervised Machine Learning Glioblastoma Humans Brain Neoplasms Female DNA Methylation Adult DNA Copy Number Variations
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