Identification of Under-Detected Periodicity in Time-Series Microarray Data by Using Empirical Mode Decomposition

Detecting periodicity signals from time-series microarray data is commonly used to facilitate the understanding of the critical roles and underlying mechanisms of regulatory transcriptomes. However, time-series microarray data are noisy. How the temporal data structure affects the performance of per...

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Detalles Bibliográficos
Autores principales: Chen, Chaang-Ray, Shu, Wun-Yi, Chang, Cheng-Wei, Hsu, Ian C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2014
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4221108/
https://www.ncbi.nlm.nih.gov/pubmed/25372711
http://dx.doi.org/10.1371/journal.pone.0111719

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4221108/
https://www.ncbi.nlm.nih.gov/pubmed/25372711
http://dx.doi.org/10.1371/journal.pone.0111719

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