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Interpolation based consensus clustering for gene expression time series

BACKGROUND: Unsupervised analyses such as clustering are the essential tools required to interpret time-series expression data from microarrays. Several clustering algorithms have been developed to analyze gene expression data. Early methods such as k-means, hierarchical clustering, and self-organiz...

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Bibliographic Details
Published in:BMC Bioinformatics
Main Authors: Chiu, Tai-Yu, Hsu, Ting-Chieh, Yen, Chia-Cheng, Wang, Jia-Shung
Format: Artigo
Language:Inglês
Published: BioMed Central 2015
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Online Access:https://ncbi.nlm.nih.gov/pmc/articles/PMC4407314/
https://ncbi.nlm.nih.gov/pubmed/25888019
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s12859-015-0541-0
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