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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...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2011
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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. |
format | Online Article Text |
id | pubmed-3185418 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
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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