Machine learning techniques for pathogenicity prediction of non-synonymous single nucleotide polymorphisms in human body
Author:
Publisher
Springer Science and Business Media LLC
Subject
General Computer Science
Link
https://link.springer.com/content/pdf/10.1007/s12652-021-03581-3.pdf
Reference33 articles.
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4. Fredman D et al (2004) HGVbase: a curated resource describing human DNA variation and phenotype relationships. Nucleic Acids Res 32(suppl_1):516–519
5. González-Pérez A, López-Bigas N (2011) Improving the assessment of the outcome of nonsynonymous SNVs with a consensus deleteriousness score, Condel. Am J Hum Genet 88(4):440–449
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1. Correction to: Machine learning techniques for pathogenicity prediction of non-synonymous single nucleotide polymorphisms in human body;Journal of Ambient Intelligence and Humanized Computing;2022-01-22
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