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Gade, Stephan |
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One of the main goals in cancer studies including high-throughput microRNA (miRNA) and mRNA data is to find and assess prognostic signatures capable of predicting clinical outcome. Both mRNA and miRNA expression changes in cancer diseases are described to reflect clinical characteristics like staging and prognosis. Furthermore, miRNA abundance can directly affect target transcripts and translation in tumor cells. Prediction models are trained to identify either mRNA or miRNA signatures for patient stratification. With the increasing number of microarray studies collecting mRNA and miRNA fro... |
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Gade, Stephan aut, Graph based fusion of high-dimensional gene- and microRNA expression data vorgelegt von Stephan Gade, 2012, Online-Ressource (PDF-Datei: 1,7 MB), Text txt rdacontent, Computermedien c rdamedia, Online-Ressource cr rdacarrier, Göttingen, Univ., Diss., 2012, One of the main goals in cancer studies including high-throughput microRNA (miRNA) and mRNA data is to find and assess prognostic signatures capable of predicting clinical outcome. Both mRNA and miRNA expression changes in cancer diseases are described to reflect clinical characteristics like staging and prognosis. Furthermore, miRNA abundance can directly affect target transcripts and translation in tumor cells. Prediction models are trained to identify either mRNA or miRNA signatures for patient stratification. With the increasing number of microarray studies collecting mRNA and miRNA fro..., Hochschulschrift (DE-588)4113937-9 (DE-627)105825778 (DE-576)209480580 gnd-content, Beissbarth, Tim Betreuer oth, Beissbarth, Tim Gutachter oth, Waack, Stephan Gutachter oth, Göttingen uvp, Druckausg. Gade, Stephan Graph based fusion of high-dimensional gene- and microRNA expression data 2012 119 S. (DE-627)737346280, http://nbn-resolving.de/urn:nbn:de:gbv-7-11858/00-1735-0000-000D-F1B1-6-6 text/html Resolving-System jump-off Volltext, http://hdl.handle.net/11858/00-1735-0000-000D-F1B1-6 text/html Resolving-System jump-off kostenfrei Volltext, http://hdl.handle.net/11858/00-1735-0000-000D-F1B1-6 LFER, LFER 2019-07-15T00:00:00Z |
spellingShingle |
Gade, Stephan, Graph based fusion of high-dimensional gene- and microRNA expression data, One of the main goals in cancer studies including high-throughput microRNA (miRNA) and mRNA data is to find and assess prognostic signatures capable of predicting clinical outcome. Both mRNA and miRNA expression changes in cancer diseases are described to reflect clinical characteristics like staging and prognosis. Furthermore, miRNA abundance can directly affect target transcripts and translation in tumor cells. Prediction models are trained to identify either mRNA or miRNA signatures for patient stratification. With the increasing number of microarray studies collecting mRNA and miRNA fro..., Hochschulschrift |
swb_id_str |
9737346270 |
title |
Graph based fusion of high-dimensional gene- and microRNA expression data |
title_auth |
Graph based fusion of high-dimensional gene- and microRNA expression data |
title_full |
Graph based fusion of high-dimensional gene- and microRNA expression data vorgelegt von Stephan Gade |
title_fullStr |
Graph based fusion of high-dimensional gene- and microRNA expression data vorgelegt von Stephan Gade |
title_full_unstemmed |
Graph based fusion of high-dimensional gene- and microRNA expression data vorgelegt von Stephan Gade |
title_short |
Graph based fusion of high-dimensional gene- and microRNA expression data |
title_sort |
graph based fusion of high dimensional gene and microrna expression data |
topic |
Hochschulschrift |
topic_facet |
Hochschulschrift |
url |
http://nbn-resolving.de/urn:nbn:de:gbv-7-11858/00-1735-0000-000D-F1B1-6-6, http://hdl.handle.net/11858/00-1735-0000-000D-F1B1-6 |
urn |
urn:nbn:de:gbv:7-11858/00-1735-0000-000D-F1B1-6-3, urn:nbn:de:gbv-7-11858/00-1735-0000-000D-F1B1-6-6 |