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dc.contributor.authorZhao, Wei
dc.contributor.authorDauwels, Justin H. G.
dc.contributor.authorNiles, Jacquin
dc.contributor.authorCao, Jianshu
dc.date.accessioned2012-07-19T20:38:20Z
dc.date.available2012-07-19T20:38:20Z
dc.date.issued2012-06
dc.date.submitted2011-11
dc.identifier.issn1477-5956
dc.identifier.urihttp://hdl.handle.net/1721.1/71716
dc.descriptionFrom IEEE International Conference on Bioinformatics and Biomedicine 2011 Atlanta, GA, USA. 12-15 November 2011en_US
dc.description.abstractBackground Microarrays are widely used to investigate the blood stage of Plasmodium falciparum infection. Starting with synchronized cells, gene expression levels are continually measured over the 48-hour intra-erythrocytic cycle (IDC). However, the cell population gradually loses synchrony during the experiment. As a result, the microarray measurements are blurred. In this paper, we propose a generalized deconvolution approach to reconstruct the intrinsic expression pattern, and apply it to P. falciparum IDC microarray data. Methods We develop a statistical model for the decay of synchrony among cells, and reconstruct the expression pattern through statistical inference. The proposed method can handle microarray measurements with noise and missing data. The original gene expression patterns become more apparent in the reconstructed profiles, making it easier to analyze and interpret the data. We hypothesize that reconstructed gene expression patterns represent better temporally resolved expression profiles that can be probabilistically modeled to match changes in expression level to IDC transitions. In particular, we identify transcriptionally regulated protein kinases putatively involved in regulating the P. falciparum IDC. Results By analyzing publicly available microarray data sets for the P. falciparum IDC, protein kinases are ranked in terms of their likelihood to be involved in regulating transitions between the ring, trophozoite and schizont developmental stages of the P. falciparum IDC. In our theoretical framework, a few protein kinases have high probability rankings, and could potentially be involved in regulating these developmental transitions. Conclusions This study proposes a new methodology for extracting intrinsic expression patterns from microarray data. By applying this method to P. falciparum microarray data, several protein kinases are predicted to play a significant role in the P. falciparum IDC. Earlier experiments have indeed confirmed that several of these kinases are involved in this process. Overall, these results indicate that further functional analysis of these additional putative protein kinases may reveal new insights into how the P. falciparum IDC is regulated.en_US
dc.description.sponsorshipUnited States. Dept. of Defense (ARO (Grant Number W911NF-09-1-0480)en_US
dc.description.sponsorshipSingapore-MIT Alliance for Research and Technology (Graduate Fellowship)en_US
dc.publisherBioMed Central Ltden_US
dc.relation.isversionofhttp://dx.doi.org/10.1186/1477-5956-10-S1-S10en_US
dc.rightsCreative Commons Attributionen_US
dc.rights.urihttp://creativecommons.org/licenses/by/2.0en_US
dc.sourceBioMed Central Ltden_US
dc.titleComputational synchronization of microarray data with application to Plasmodium falciparumen_US
dc.typeArticleen_US
dc.identifier.citationZhao, Wei et al. “Computational Synchronization of Microarray Data with Application to Plasmodium Falciparum.” Proteome Science 10.Suppl 1 (2012): S10. Web.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Biological Engineeringen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Chemistryen_US
dc.contributor.departmentSingapore-MIT Alliance in Research and Technology (SMART)en_US
dc.contributor.mitauthorZhao, Wei
dc.contributor.mitauthorDauwels, Justin H. G.
dc.contributor.mitauthorNiles, Jacquin
dc.contributor.mitauthorCao, Jianshu
dc.relation.journalProteome Scienceen_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dc.date.updated2012-06-21T11:08:28Z
dc.language.rfc3066en
dc.rights.holderWei Zhao et al.; licensee BioMed Central Ltd.
dspace.orderedauthorsZhao, Wei; Dauwels, Justin; Niles, Jacquin C; Cao, Jianshuen
dc.identifier.orcidhttps://orcid.org/0000-0001-7616-7809
dc.identifier.orcidhttps://orcid.org/0000-0002-6250-8796
mit.licensePUBLISHER_CCen_US
mit.metadata.statusComplete


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