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Tim Beissbarth

Showing results (1-10 of 127) with videos related to

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Methods in Enzymology|August 31, 2006
Interpreting experimental results using gene ontologiesTim Beissbarth
Bioinformatics (Oxford, England)|February 14, 2004
GOstat: find statistically overrepresented Gene Ontologies within a group of genesTim Beissbarth, Terence P Speed
BMC Bioinformatics|July 16, 2011
Reporting FDR analogous confidence intervals for the log fold change of differentially expressed genesKlaus Jung, Tim Friede, Tim Beissbarth
BMC Medicine|May 3, 2012
A new analysis approach of epidermal growth factor receptor pathway activation patterns provides insights into cetuximab resistance mechanisms in head and neck cancerSilvia von der Heyde, Tim Beissbarth
Biometrical Journal. Biometrische Zeitschrift|April 10, 2009
Nested effects models for learning signaling networks from perturbation dataHolger Fröhlich, Achim Tresch, Tim Beissbarth
BMC Bioinformatics|April 30, 2011
Sequential interim analyses of survival data in DNA microarray experimentsAndreas Leha, Tim Beissbarth, Klaus Jung
BMC Bioinformatics|May 24, 2007
GOSim--an R-package for computation of information theoretic GO similarities between terms and gene productsHolger Fröhlich, Nora Speer, Annemarie Poustka, et al.
Bioinformatics (Oxford, England)|April 1, 2011
pathClass: an R-package for integration of pathway knowledge into support vector machines for biomarker discoveryMarc Johannes, Holger Fröhlich, Holger Sültmann, et al.
Biometrical Journal. Biometrische Zeitschrift|February 18, 2011
Leveraging external knowledge on molecular interactions in classification methods for risk prediction of patientsChristine Porzelius, Marc Johannes, Harald Binder, et al.
Bioinformatics (Oxford, England)|March 29, 2011
Comparison of global tests for functional gene sets in two-group designs and selection of potentially effect-causing genesKlaus Jung, Benjamin Becker, Edgar Brunner, et al.
Pageof 13

Showing results (1-10 of 127) with videos related to

Sort By:
Pageof 13
Methods in Enzymology|August 31, 2006
Interpreting experimental results using gene ontologiesTim Beissbarth
Bioinformatics (Oxford, England)|February 14, 2004
GOstat: find statistically overrepresented Gene Ontologies within a group of genesTim Beissbarth, Terence P Speed
BMC Bioinformatics|July 16, 2011
Reporting FDR analogous confidence intervals for the log fold change of differentially expressed genesKlaus Jung, Tim Friede, Tim Beissbarth
BMC Medicine|May 3, 2012
A new analysis approach of epidermal growth factor receptor pathway activation patterns provides insights into cetuximab resistance mechanisms in head and neck cancerSilvia von der Heyde, Tim Beissbarth
Biometrical Journal. Biometrische Zeitschrift|April 10, 2009
Nested effects models for learning signaling networks from perturbation dataHolger Fröhlich, Achim Tresch, Tim Beissbarth
BMC Bioinformatics|April 30, 2011
Sequential interim analyses of survival data in DNA microarray experimentsAndreas Leha, Tim Beissbarth, Klaus Jung
BMC Bioinformatics|May 24, 2007
GOSim--an R-package for computation of information theoretic GO similarities between terms and gene productsHolger Fröhlich, Nora Speer, Annemarie Poustka, et al.
Bioinformatics (Oxford, England)|April 1, 2011
pathClass: an R-package for integration of pathway knowledge into support vector machines for biomarker discoveryMarc Johannes, Holger Fröhlich, Holger Sültmann, et al.
Biometrical Journal. Biometrische Zeitschrift|February 18, 2011
Leveraging external knowledge on molecular interactions in classification methods for risk prediction of patientsChristine Porzelius, Marc Johannes, Harald Binder, et al.
Bioinformatics (Oxford, England)|March 29, 2011
Comparison of global tests for functional gene sets in two-group designs and selection of potentially effect-causing genesKlaus Jung, Benjamin Becker, Edgar Brunner, et al.
Pageof 13