Application of Machine Learning to Development of Copy Number Variation-based Prediction of Cancer Risk

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Copy number variation analysis based on AluScan sequences Feature co-localization landscape of the human genome Identifying Patients with Atrioventricular Septal Defect in Down Syndrome Populations by Using Self-Normalizing Neural Networks and Feature Selection.

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Application of Machine Learning to Development of Copy Number Variation-based Prediction of Cancer Risk

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Application of Machine Learnin ...... ased Prediction of Cancer Risk

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Application of Machine Learnin ...... ased Prediction of Cancer Risk

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Application of Machine Learnin ...... ased Prediction of Cancer Risk

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Application of Machine Learnin ...... ased Prediction of Cancer Risk

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Shui-Ying Tsang

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Siu-Kin Ng

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Xiaofan Ding

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Akt1 and Akt2: differentiating the aktion

Copy number variation at 1q21.1 associated with neuroblastoma

Oncogenic mutations of PIK3CA in human cancers

The Growing Importance of CNVs: New Insights for Detection and Clinical Interpretation

A pilot genome-wide association study shows genomic variants enriched in the non-tumor cells of patients with well-differentiated neuroendocrine tumors of the ileum

Genetic variations at loci involved in the immune response are risk factors for hepatocellular carcinoma

The landscape of somatic copy-number alteration across human cancers.

Circular binary segmentation for the analysis of array-based DNA copy number data

Continuing difficulties in interpreting CNV data: lessons from a genome-wide CNV association study of Australian HNPCC/lynch syndrome patients.

Optimization based tumor classification from microarray gene expression data.

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1-11

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scholarly article

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10.4137/GEI.S15002

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Hong Xue

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2014-06-26T00:00:00Z

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machine learning

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Application of Machine Learning to Development of Copy Number Variation-based Prediction of Cancer Risk

about

P2860

P2860

Application of Machine Learning to Development of Copy Number Variation-based Prediction of Cancer Risk

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