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dc.contributor.authorWang, Xueweien_US
dc.contributor.authorWu, Mingen_US
dc.contributor.authorLi, Zhengen_US
dc.contributor.authorChan, Christinaen_US
dc.date.accessioned2012-01-11T00:37:41Z
dc.date.available2012-01-11T00:37:41Z
dc.date.copyright2008
dc.date.issued2008-7-7
dc.identifier.citationWang, Xuewei, Ming Wu, Zheng Li, Christina Chan. "Short time-series microarray analysis: Methods and challenges" BMC Systems Biology 2:58. (2008)
dc.identifier.issn1752-0509
dc.identifier.urihttps://hdl.handle.net/2144/3008
dc.description.abstractThe detection and analysis of steady-state gene expression has become routine. Time-series microarrays are of growing interest to systems biologists for deciphering the dynamic nature and complex regulation of biosystems. Most temporal microarray data only contain a limited number of time points, giving rise to short-time-series data, which imposes challenges for traditional methods of extracting meaningful information. To obtain useful information from the wealth of short-time series data requires addressing the problems that arise due to limited sampling. Current efforts have shown promise in improving the analysis of short time-series microarray data, although challenges remain. This commentary addresses recent advances in methods for short-time series analysis including simplification-based approaches and the integration of multi-source information. Nevertheless, further studies and development of computational methods are needed to provide practical solutions to fully exploit the potential of this data.en_US
dc.description.sponsorshipNational Institute of Health (IR01GM079688-01); National Science Foundation (BES 0425821); MSU Foundation on the Center for Systems Biologyen_US
dc.language.isoen
dc.publisherBioMed Centralen_US
dc.rightsCopyright 2008 Wang et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.en_US
dc.rights.urihttp://creativecommons.org/licenses/by/2.0
dc.titleShort Time-Series Microarray Analysis: Methods and Challengesen_US
dc.typeArticleen_US
dc.identifier.doi10.1186/1752-0509-2-58
dc.identifier.pmid18605994
dc.identifier.pmcid2474593


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Copyright 2008 Wang et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Except where otherwise noted, this item's license is described as Copyright 2008 Wang et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.