Identification of Key Molecules in Recurrent Miscarriage Based on Bioinformatics Analysis.

Wu, Haiwang; Ning, Yan; Yu, Qingying; Luo, Songping; Gao, Jie

Wu, Haiwang; Ning, Yan; Yu, Qingying; Luo, Songping; Gao, Jie.

Afiliação

Wu H; Department of Gynecology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou 510405, China.
Ning Y; Department of Chinese Medicine, Shenzhen Maternity & Child Healthcare Hospital, Shenzhen 518000, China.
Yu Q; Department of Gynecology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou 510405, China.
Luo S; Guangzhou University of Chinese Medicine, Guangzhou 510405, China.
Gao J; Department of Gynecology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou 510405, China.

Comb Chem High Throughput Screen ; 25(10): 1745-1755, 2022.

Article em En | MEDLINE | ID: mdl-34433394

Assuntos

Aborto Habitual; MicroRNAs; Aborto Habitual/genética; Biomarcadores; Biologia Computacional; Feminino; Perfilação da Expressão Gênica; Redes Reguladoras de Genes/genética; Humanos; MicroRNAs/genética; RNA Mensageiro/genética; RNA Mensageiro/metabolismo

Palavras-chave

Key molecules; bioinformatics analysis; gene; network; pathogenesis; recurrent miscarriage

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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Aborto Habitual / MicroRNAs Tipo de estudo: Diagnostic_studies Limite: Female / Humans Idioma: En Revista: Comb Chem High Throughput Screen Assunto da revista: BIOLOGIA MOLECULAR / QUIMICA Ano de publicação: 2022 Tipo de documento: Article País de afiliação: China

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