AIMC Topic: DNA Copy Number Variations
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A machine-learning approach for accurate detection of copy number variants from exome sequencing.
Genome research
Jun 6, 2019
Copy number variants (CNVs) are a major cause of several genetic disorders, making their detection an essential component of genetic analysis pipelines. Current methods for detecting CNVs from exome-sequencing data are limited by high false-positive ...
Capsule Network Based Modeling of Multi-omics Data for Discovery of Breast Cancer-Related Genes.
IEEE/ACM transactions on computational biology and bioinformatics
Apr 9, 2019
Breast cancer is one of the most common cancers all over the world, which bring about more than 450,000 deaths each year. Although this malignancy has been extensively studied by a large number of researchers, its prognosis is still poor. Since thera...
Classifying Breast Cancer Subtypes Using Multiple Kernel Learning Based on Omics Data.
Genes
Mar 7, 2019
It is very significant to explore the intrinsic differences in breast cancer subtypes. These intrinsic differences are closely related to clinical diagnosis and designation of treatment plans. With the accumulation of biological and medicine datasets...
ClinTAD: a tool for copy number variant interpretation in the context of topologically associated domains.
Journal of human genetics
Feb 14, 2019
Standard clinical interpretation of DNA copy number variants (CNVs) identified by cytogenomic microarray involves examining protein-coding genes within the region and comparison to other CNVs. Emerging basic research suggests that CNVs can also exert...
Molecular and epigenetic profiles of BRCA1-like hormone-receptor-positive breast tumors identified with development and application of a copy-number-based classifier.
Breast cancer research : BCR
Jan 25, 2019
BACKGROUND: BRCA1-mutated cancers exhibit deficient homologous recombination (HR) DNA repair, resulting in extensive copy number alterations and genome instability. HR deficiency can also arise in tumors without a BRCA1 mutation. Compared with other ...
A Projection Neural Network for Identifying Copy Number Variants.
IEEE journal of biomedical and health informatics
Sep 20, 2018
The identification of copy number variations (CNVs) helps the diagnosis of many diseases. One major hurdle in the path of CNVs discovery is that the boundaries of normal and aberrant regions cannot be distinguished from the raw data, since various ty...
Cancer type prediction based on copy number aberration and chromatin 3D structure with convolutional neural networks.
BMC genomics
Aug 13, 2018
BACKGROUND: With the developments of DNA sequencing technology, large amounts of sequencing data have been produced that provides unprecedented opportunities for advanced association studies between somatic mutations and cancer types/subtypes which f...
Machine Learning for Better Prognostic Stratification and Driver Gene Identification Using Somatic Copy Number Variations in Anaplastic Oligodendroglioma.
The oncologist
Jul 17, 2018
BACKGROUND: 1p/19q-codeleted anaplastic gliomas have variable clinical behavior. We have recently shown that the common 9p21.3 allelic loss is an independent prognostic factor in this tumor type. The aim of this study is to identify less frequent gen...
Prognostic values of the integrated model incorporating the volume of metastatic regional cervical lymph node and pretreatment serum Epstein-Barr virus DNA copy number in predicting distant metastasis in patients with N1 nasopharyngeal carcinoma.
Chinese journal of cancer
Dec 29, 2017
BACKGROUND: According to the 7th edition of the American Joint Committee on Cancer (AJCC) staging system, over 50% of patients with nasopharyngeal carcinoma (NPC) have N1 disease at initial diagnosis. However, patients with N1 NPC are relatively unde...
EMcnv: enhancing CNV detection performance through ensemble strategies with heterogeneous meta-graph neural networks.
Briefings in bioinformatics
Mar 4, 2025
Copy number variation (CNV) is a crucial biomarker for many complex traits and diseases. Although numerous CNV detection tools are available, no single method consistently achieves optimal performance across diverse sequencing samples, as each tool h...
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