Integrative missing value estimation for microarray data

BACKGROUND: Missing value estimation is an important preprocessing step in microarray analysis. Although several methods have been developed to solve this problem, their performance is unsatisfactory for datasets with high rates of missing data, high measurement noise, or limited numbers of samples....

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Detalles Bibliográficos
Autores principales: Hu, Jianjun, Li, Haifeng, Waterman, Michael S, Zhou, Xianghong Jasmine
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2006
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1622759/
https://www.ncbi.nlm.nih.gov/pubmed/17038176
http://dx.doi.org/10.1186/1471-2105-7-449

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1622759/
https://www.ncbi.nlm.nih.gov/pubmed/17038176
http://dx.doi.org/10.1186/1471-2105-7-449

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