Modeling Microarray Data: Interpreting and communicating the biological results

Various statistical models have been proposed for detecting differential gene expression in data from microarray experiments. Given such detection, we are usually interested in describing the differential expression patterns. Due to the large number of genes that are typically analysed in microarray...

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Main Authors: Pittelkow Y. E., Wilson S. R.
Format: Article
Language:English
Published: De Gruyter 2006-12-01
Series:Journal of Integrative Bioinformatics
Online Access:https://doi.org/10.1515/jib-2006-29
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spelling doaj-90353cd0e96a4a0eb986a1f7f6ab91672021-09-06T19:40:30ZengDe GruyterJournal of Integrative Bioinformatics1613-45162006-12-0132778910.1515/jib-2006-29biecoll-jib-2006-29Modeling Microarray Data: Interpreting and communicating the biological resultsPittelkow Y. E.0Wilson S. R.1Centre for BioInformation Science, Mathematical Sciences Institute, Australian National University, Building 27, Canberra, ACT, AustraliaCentre for BioInformation Science, Mathematical Sciences Institute, Australian National University, Building 27, Canberra, ACT, AustraliaVarious statistical models have been proposed for detecting differential gene expression in data from microarray experiments. Given such detection, we are usually interested in describing the differential expression patterns. Due to the large number of genes that are typically analysed in microarray experiments, possibly more than ten thousand, the tasks of interpretation and communication of all the corresponding statistical models pose a considerable challenge, except perhaps in the simplest experiment involving only two groups. A further challenge is to find methods to summarize the resulting models. These challenges increase with experimental complexity.https://doi.org/10.1515/jib-2006-29
collection DOAJ
language English
format Article
sources DOAJ
author Pittelkow Y. E.
Wilson S. R.
spellingShingle Pittelkow Y. E.
Wilson S. R.
Modeling Microarray Data: Interpreting and communicating the biological results
Journal of Integrative Bioinformatics
author_facet Pittelkow Y. E.
Wilson S. R.
author_sort Pittelkow Y. E.
title Modeling Microarray Data: Interpreting and communicating the biological results
title_short Modeling Microarray Data: Interpreting and communicating the biological results
title_full Modeling Microarray Data: Interpreting and communicating the biological results
title_fullStr Modeling Microarray Data: Interpreting and communicating the biological results
title_full_unstemmed Modeling Microarray Data: Interpreting and communicating the biological results
title_sort modeling microarray data: interpreting and communicating the biological results
publisher De Gruyter
series Journal of Integrative Bioinformatics
issn 1613-4516
publishDate 2006-12-01
description Various statistical models have been proposed for detecting differential gene expression in data from microarray experiments. Given such detection, we are usually interested in describing the differential expression patterns. Due to the large number of genes that are typically analysed in microarray experiments, possibly more than ten thousand, the tasks of interpretation and communication of all the corresponding statistical models pose a considerable challenge, except perhaps in the simplest experiment involving only two groups. A further challenge is to find methods to summarize the resulting models. These challenges increase with experimental complexity.
url https://doi.org/10.1515/jib-2006-29
work_keys_str_mv AT pittelkowye modelingmicroarraydatainterpretingandcommunicatingthebiologicalresults
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