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Michael Altenbuchinger

Showing results (1-10 of 43) with videos related to

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Metabolites|August 30, 2018
Statistical Analysis of NMR Metabolic Fingerprints: Established Methods and Recent AdvancesHelena U Zacharias, Michael Altenbuchinger, Wolfram Gronwald
Studies in Health Technology and Informatics|May 23, 2026
Effects of Non-IID Distributions in Lung Cancer Data on Survival Prediction with Federated Ensemble LearningLinus Weber, Anne-Christin Hauschild, Michael Altenbuchinger, et al.
Plant Physiology and Biochemistry : PPB|December 19, 2020
Proteome profiling of repeated drought stress reveals genotype-specific responses and memory effects in maizeWaltraud X Schulze, Michael Altenbuchinger, Mingjie He, et al.
Bioinformatics (Oxford, England)|June 28, 2024
CODEX: COunterfactual Deep learning for the in silico EXploration of cancer cell line perturbationsStefan Schrod, Helena U Zacharias, Tim Beißbarth, et al.
Metabolites|August 6, 2021
Chronic Kidney Disease Cohort Studies: A Guide to Metabolome AnalysesUlla T Schultheiss, Robin Kosch, Fruzsina Kotsis, et al.
Biochimica Et Biophysica Acta. Gene Regulatory Mechanisms|October 23, 2019
Gaussian and Mixed Graphical Models as (multi-)omics data analysis toolsMichael Altenbuchinger, Antoine Weihs, John Quackenbush, et al.
Haematologica|July 17, 2025
Long non-coding RNA LINC00926 is a biomarker for naïve B-cells with prognostic value in advanced stage classic Hodgkin LymphomaIngram Iaccarino, Thomas Beder, Sarah Reinke, et al.
Journal of Computational Biology : a Journal of Computational Molecular Cell Biology|January 30, 2020
Loss-Function Learning for Digital Tissue DeconvolutionFranziska Görtler, Marian Schön, Jakob Simeth, et al.
Metabolites|August 6, 2021
An <i>R</i>-Package for the Deconvolution and Integration of 1D NMR Data: MetaboDecon1DMartina Häckl, Philipp Tauber, Frank Schweda, et al.
Bioinformatics (Oxford, England)|November 26, 2024
Virtual tissue expression analysisJakob Simeth, Paul Hüttl, Marian Schön, et al.
Pageof 5

Showing results (1-10 of 43) with videos related to

Sort By:
Pageof 5
Metabolites|August 30, 2018
Statistical Analysis of NMR Metabolic Fingerprints: Established Methods and Recent AdvancesHelena U Zacharias, Michael Altenbuchinger, Wolfram Gronwald
Studies in Health Technology and Informatics|May 23, 2026
Effects of Non-IID Distributions in Lung Cancer Data on Survival Prediction with Federated Ensemble LearningLinus Weber, Anne-Christin Hauschild, Michael Altenbuchinger, et al.
Plant Physiology and Biochemistry : PPB|December 19, 2020
Proteome profiling of repeated drought stress reveals genotype-specific responses and memory effects in maizeWaltraud X Schulze, Michael Altenbuchinger, Mingjie He, et al.
Bioinformatics (Oxford, England)|June 28, 2024
CODEX: COunterfactual Deep learning for the in silico EXploration of cancer cell line perturbationsStefan Schrod, Helena U Zacharias, Tim Beißbarth, et al.
Metabolites|August 6, 2021
Chronic Kidney Disease Cohort Studies: A Guide to Metabolome AnalysesUlla T Schultheiss, Robin Kosch, Fruzsina Kotsis, et al.
Biochimica Et Biophysica Acta. Gene Regulatory Mechanisms|October 23, 2019
Gaussian and Mixed Graphical Models as (multi-)omics data analysis toolsMichael Altenbuchinger, Antoine Weihs, John Quackenbush, et al.
Haematologica|July 17, 2025
Long non-coding RNA LINC00926 is a biomarker for naïve B-cells with prognostic value in advanced stage classic Hodgkin LymphomaIngram Iaccarino, Thomas Beder, Sarah Reinke, et al.
Journal of Computational Biology : a Journal of Computational Molecular Cell Biology|January 30, 2020
Loss-Function Learning for Digital Tissue DeconvolutionFranziska Görtler, Marian Schön, Jakob Simeth, et al.
Metabolites|August 6, 2021
An <i>R</i>-Package for the Deconvolution and Integration of 1D NMR Data: MetaboDecon1DMartina Häckl, Philipp Tauber, Frank Schweda, et al.
Bioinformatics (Oxford, England)|November 26, 2024
Virtual tissue expression analysisJakob Simeth, Paul Hüttl, Marian Schön, et al.
Pageof 5