Chromothripsis detection with multiple myeloma patients based on deep graph learning.

Yu, Jixiang; Chen, Nanjun; Zheng, Zetian; Gao, Ming; Liang, Ning; Wong, Ka-Chun

Yu, Jixiang; Chen, Nanjun; Zheng, Zetian; Gao, Ming; Liang, Ning; Wong, Ka-Chun.

Afiliação

Yu J; Department of Computer Science, City University of Hong Kong, Kowloon, 999077, Hong Kong.
Chen N; Department of Computer Science, City University of Hong Kong, Kowloon, 999077, Hong Kong.
Zheng Z; Department of Computer Science, City University of Hong Kong, Kowloon, 999077, Hong Kong.
Gao M; School of Management Science and Engineering, Dongbei University of Finance and Economics, Dalian 116025, China.
Liang N; University of Michigan, Ann Arbor, MI 48105, United States.
Wong KC; Department of Computer Science, City University of Hong Kong, Kowloon, 999077, Hong Kong.

Bioinformatics ; 39(7)2023 07 01.

Article em En | MEDLINE | ID: mdl-37399092

Assuntos

Cromotripsia; Mieloma Múltiplo; Humanos; Mieloma Múltiplo/diagnóstico; Mieloma Múltiplo/genética; Variações do Número de Cópias de DNA; Software; Redes Neurais de Computação

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Cromotripsia / Mieloma Múltiplo Tipo de estudo: Diagnostic_studies / Guideline / Prognostic_studies Limite: Humans Idioma: En Revista: Bioinformatics Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Hong Kong

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