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Updated: Mar 14, 2026

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER
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Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Published on: June 23, 2012

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ML-ExonCNV:一个强大的XGBoost多专家组合框架,用于在整个exome测序数据中检测罕见的exon CNV

Shuang-Hao Yang1,2,3, Hua He1, Shuyu Hou1

  • 1Department of Bioinformatics, Chigene (Beijing) Translational Medical Research Center Co., Ltd., Beijing Yizhuang Biomedical Park, 100176, China.

Briefings in bioinformatics
|March 12, 2026
PubMed
概括

ML-ExonCNV 改进了从整个外因组测序数据中检测出小外因子级副本数变异 (exCNV) 的检测. 这种新的机器学习方法提高了准确性,识别了与疾病相关的基因和表型.

关键词:
在WES CNVs中,可以找到WES CNV.在XGBoost中使用.在 exon 级别的 CNV.机器学习是机器学习.

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Sequencing of the human genome has opened up several best-kept secrets of the genome. Scientists have identified thousands of genome variations that exist within a population. These variations can be a single nucleotide or a larger chromosomal variation.
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