多组学数据整合与变异致病性估计的机器学习

2018 IEEE 14th International Conference on e-Science (e-Science) Pub Date : 2018-10-01 DOI:10.1109/eScience.2018.00062

Shuang Li, K. V. D. Velde, M. Swertz

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引用次数: 0

摘要

基因组研究的快速发展使得基因检测在今天的诊断实践中很常见[1]。下一代测序为研究人员提供了大量的基因组数据，但其解释仍处于起步阶段[5]。诊断率仍在30%左右[1,3,8]。需要分析基因组数据的解释工具。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Machine Learning for Multi-Omics Data Integration and Variant Pathogenicity Estimation

The rapid advances in the genomic study have made genetics testing common in today's diagnostic practices [1]. Next-generation sequencing provides researchers with a huge amount of genomic data, yet the interpretation still in its infancy [5].The diagnostics yield is still around 30% [1, 3, 8]. Interpretation tools for analyzing the genomic data is needed.

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2018 IEEE 14th International Conference on e-Science (e-Science)

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