Intellectual Mining of Patient Data with Melanoma for Identification of Disease Markers and Critical Genes
- Autores: Chebanov D.K.1, Mikhailova I.N.2
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Afiliações:
- Russian State University for the Humanities
- Blokhin National Medical Research Center for Oncology, Ministry of Health of the Russian Federation
- Edição: Volume 53, Nº 5 (2019)
- Páginas: 283-287
- Seção: The Jsm Method of Automated Research Support and Its Application in Intelligent Systems for Medicine
- URL: https://journal-vniispk.ru/0005-1055/article/view/150334
- DOI: https://doi.org/10.3103/S0005105519050066
- ID: 150334
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Resumo
Genotypic (DNA mutations) and phenotyping data on patients with melanoma are analyzed to identify markers of early disease diagnosis and critical involved genes. An optimal mining method was chosen from those that are traditionally used in the field. This method allows one to analyze a set of terms. Automatic and interactive approaches were performed, which both allow a considerable reduction in the computational requirements. New melanoma-associated genes and candidate relapse markers were identified. Data mining was performed with the JSM method of automated support of scientific research (JSM ASSR).
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Sobre autores
D. Chebanov
Russian State University for the Humanities
Autor responsável pela correspondência
Email: chebanov.dk@gmail.com
Rússia, Moscow, 125993
I. Mikhailova
Blokhin National Medical Research Center for Oncology, Ministry of Health of the Russian Federation
Autor responsável pela correspondência
Email: irmikhaylova@gmail.com
Rússia, Moscow, 115478
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