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

Year: 2018

Type: conference-paper

Abstract: 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.

Source: IEEE International Conference on eScience

DOI: 10.1109/escience.2018.00062

Authors: Shuang Li, K. Joeri van der Velde, Morris A. Swertz

Institutions: University Medical Center Groningen, University of Groningen

Language: English

Topic: Genomics and Rare Diseases

Subfield: Genetics

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

SDG: Good health and well-being

Open Access status: green

OpenAlex ID: W2906964573

FWCI:

Cites: 11

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Related to: 10