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Updated: Jul 6, 2025

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使用基于机器学习的方法提高微阵列数据中的CNV检测性能

Chul Jun Goh1, Hyuk-Jung Kwon1,2, Yoonhee Kim1

  • 1Eone-Diagnomics Genome Center, Inc., 143, Gaetbeol-ro, Yeonsu-gu, Incheon 21999, Republic of Korea.

Diagnostics (Basel, Switzerland)
|January 11, 2024
PubMed
概括

这项研究引入了一种新的机器学习方法,可以准确检测新生儿的副本数变异 (CNV),从而改善遗传疾病和染色体残疾的诊断.

关键词:
在CNV中,CNV是NV.韩国新生儿韩国新生儿全基因组SNP阵列数组.基因组波浪是基因组的波浪.机器学习是机器学习.

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Microarrays are high-throughput and relatively inexpensive assays that can be automated to analyze large quantities of data at a time. They are used in genome-wide studies to compare gene or protein expression under two varied conditions, such as healthy and diseased states. Microarrays consist of glass or silica slides on which probe molecules are covalently attached through surface functionalization. Most commonly, the slides are prepared through the chemisorption of silanes to silica...
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