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Internal standard-based analysis of microarray data2—Analysis of functional associations between HVE-genes

In this work we apply the Internal Standard-based analytical approach that we described in an earlier communication and here we demonstrate experimental results on functional associations among the hypervariably-expressed genes (HVE-genes). Our working assumption was that those genetic components, w...

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Autores principales: Dozmorov, Igor M., Jarvis, James, Saban, Ricardo, Benbrook, Doris M., Wakeland, Edward, Aksentijevich, Ivona, Ryan, John, Chiorazzi, Nicholas, Guthridge, Joel M., Drewe, Elizabeth, Tighe, Patrick J., Centola, Michael, Lefkovits, Ivan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3185418/
https://www.ncbi.nlm.nih.gov/pubmed/21715372
http://dx.doi.org/10.1093/nar/gkr503
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author Dozmorov, Igor M.
Jarvis, James
Saban, Ricardo
Benbrook, Doris M.
Wakeland, Edward
Aksentijevich, Ivona
Ryan, John
Chiorazzi, Nicholas
Guthridge, Joel M.
Drewe, Elizabeth
Tighe, Patrick J.
Centola, Michael
Lefkovits, Ivan
author_facet Dozmorov, Igor M.
Jarvis, James
Saban, Ricardo
Benbrook, Doris M.
Wakeland, Edward
Aksentijevich, Ivona
Ryan, John
Chiorazzi, Nicholas
Guthridge, Joel M.
Drewe, Elizabeth
Tighe, Patrick J.
Centola, Michael
Lefkovits, Ivan
author_sort Dozmorov, Igor M.
collection PubMed
description In this work we apply the Internal Standard-based analytical approach that we described in an earlier communication and here we demonstrate experimental results on functional associations among the hypervariably-expressed genes (HVE-genes). Our working assumption was that those genetic components, which initiate the disease, involve HVE-genes for which the level of expression is undistinguishable among healthy individuals and individuals with pathology. We show that analysis of the functional associations of the HVE-genes is indeed suitable to revealing disease-specific differences. We show also that another possible exploit of HVE-genes for characterization of pathological alterations is by using multivariate classification methods. This in turn offers important clues on naturally occurring dynamic processes in the organism and is further used for dynamic discrimination of groups of compared samples. We conclude that our approach can uncover principally new collective differences that cannot be discerned by individual gene analysis.
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spelling pubmed-31854182011-10-04 Internal standard-based analysis of microarray data2—Analysis of functional associations between HVE-genes Dozmorov, Igor M. Jarvis, James Saban, Ricardo Benbrook, Doris M. Wakeland, Edward Aksentijevich, Ivona Ryan, John Chiorazzi, Nicholas Guthridge, Joel M. Drewe, Elizabeth Tighe, Patrick J. Centola, Michael Lefkovits, Ivan Nucleic Acids Res Computational Biology In this work we apply the Internal Standard-based analytical approach that we described in an earlier communication and here we demonstrate experimental results on functional associations among the hypervariably-expressed genes (HVE-genes). Our working assumption was that those genetic components, which initiate the disease, involve HVE-genes for which the level of expression is undistinguishable among healthy individuals and individuals with pathology. We show that analysis of the functional associations of the HVE-genes is indeed suitable to revealing disease-specific differences. We show also that another possible exploit of HVE-genes for characterization of pathological alterations is by using multivariate classification methods. This in turn offers important clues on naturally occurring dynamic processes in the organism and is further used for dynamic discrimination of groups of compared samples. We conclude that our approach can uncover principally new collective differences that cannot be discerned by individual gene analysis. Oxford University Press 2011-10 2011-06-28 /pmc/articles/PMC3185418/ /pubmed/21715372 http://dx.doi.org/10.1093/nar/gkr503 Text en © The Author(s) 2011. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/3.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Computational Biology
Dozmorov, Igor M.
Jarvis, James
Saban, Ricardo
Benbrook, Doris M.
Wakeland, Edward
Aksentijevich, Ivona
Ryan, John
Chiorazzi, Nicholas
Guthridge, Joel M.
Drewe, Elizabeth
Tighe, Patrick J.
Centola, Michael
Lefkovits, Ivan
Internal standard-based analysis of microarray data2—Analysis of functional associations between HVE-genes
title Internal standard-based analysis of microarray data2—Analysis of functional associations between HVE-genes
title_full Internal standard-based analysis of microarray data2—Analysis of functional associations between HVE-genes
title_fullStr Internal standard-based analysis of microarray data2—Analysis of functional associations between HVE-genes
title_full_unstemmed Internal standard-based analysis of microarray data2—Analysis of functional associations between HVE-genes
title_short Internal standard-based analysis of microarray data2—Analysis of functional associations between HVE-genes
title_sort internal standard-based analysis of microarray data2—analysis of functional associations between hve-genes
topic Computational Biology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3185418/
https://www.ncbi.nlm.nih.gov/pubmed/21715372
http://dx.doi.org/10.1093/nar/gkr503
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