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Stefan Solbrig

Showing results (1-10 of 7) with videos related to

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Bioinformatics (Oxford, England)|June 29, 2019
Modelling cancer progression using Mutual Hazard NetworksRudolf Schill, Stefan Solbrig, Tilo Wettig, 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.
Journal of Computational Biology : a Journal of Computational Molecular Cell Biology|January 30, 2020
DTD: An R Package for Digital Tissue DeconvolutionMarian Schön, Jakob Simeth, Paul Heinrich, et al.
Scientific Reports|September 29, 2019
A multi-source data integration approach reveals novel associations between metabolites and renal outcomes in the German Chronic Kidney Disease studyMichael Altenbuchinger, Helena U Zacharias, Stefan Solbrig, et al.
Genome Research|September 4, 2024
Spatial Cellular Networks from omics data with SpaCeNetStefan Schrod, Niklas Lück, Robert Lohmayer, et al.
Genome Research|November 18, 2025
Integration of high-throughput proteomic data and complementary omics layers with PriOmicsRobin Kosch, Katharina Limm, Annette M Staiger, et al.
Cell Systems|August 24, 2018
Principles of Systems Biology, No. 31Hyunghoon Cho, Bonnie Berger, Jian Peng, et al.
Pageof 1

Showing results (1-10 of 7) with videos related to

Sort By:
Pageof 1
Bioinformatics (Oxford, England)|June 29, 2019
Modelling cancer progression using Mutual Hazard NetworksRudolf Schill, Stefan Solbrig, Tilo Wettig, 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.
Journal of Computational Biology : a Journal of Computational Molecular Cell Biology|January 30, 2020
DTD: An R Package for Digital Tissue DeconvolutionMarian Schön, Jakob Simeth, Paul Heinrich, et al.
Scientific Reports|September 29, 2019
A multi-source data integration approach reveals novel associations between metabolites and renal outcomes in the German Chronic Kidney Disease studyMichael Altenbuchinger, Helena U Zacharias, Stefan Solbrig, et al.
Genome Research|September 4, 2024
Spatial Cellular Networks from omics data with SpaCeNetStefan Schrod, Niklas Lück, Robert Lohmayer, et al.
Genome Research|November 18, 2025
Integration of high-throughput proteomic data and complementary omics layers with PriOmicsRobin Kosch, Katharina Limm, Annette M Staiger, et al.
Cell Systems|August 24, 2018
Principles of Systems Biology, No. 31Hyunghoon Cho, Bonnie Berger, Jian Peng, et al.
Pageof 1