ProJect: a powerful mixed-model missing value imputation method.

Kong, Weijia; Wong, Bertrand Jern Han; Hui, Harvard Wai Hann; Lim, Kai Peng; Wang, Yulan; Wong, Limsoon; Goh, Wilson Wen Bin

Kong, Weijia; Wong, Bertrand Jern Han; Hui, Harvard Wai Hann; Lim, Kai Peng; Wang, Yulan; Wong, Limsoon; Goh, Wilson Wen Bin.

Afiliación

Kong W; School of Biological Sciences, Nanyang Technological University, Singapore.
Wong BJH; Department of Computer Science, National University of Singapore, Singapore.
Hui HWH; Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore.
Lim KP; School of Biological Sciences, Nanyang Technological University, Singapore.
Wang Y; School of Biological Sciences, Nanyang Technological University, Singapore.
Wong L; School of Biological Sciences, Nanyang Technological University, Singapore.
Goh WWB; Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore.

Brief Bioinform ; 24(4)2023 07 20.

Article en En | MEDLINE | ID: mdl-37419612

Asunto(s)

Algoritmos; Genómica; Teorema de Bayes; Análisis de Secuencia por Matrices de Oligonucleótidos/métodos; Espectrometría de Masas/métodos

Palabras clave

bioinformatics; missing at random (MAR); missing not at random (MNAR); missing value imputation (MVI); statistics

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Algoritmos / Genómica Tipo de estudio: Prognostic_studies Idioma: En Revista: Brief Bioinform Asunto de la revista: BIOLOGIA / INFORMATICA MEDICA Año: 2023 Tipo del documento: Article País de afiliación: Singapur Pais de publicación: Reino Unido

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