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Martin Pirkl

Showing results (1-10 of 23) with videos related to

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Bioinformatics (Oxford, England)|February 22, 2021
Inferring perturbation profiles of cancer samplesMartin Pirkl, Niko Beerenwinkel
Bioinformatics (Oxford, England)|November 14, 2018
Single cell network analysis with a mixture of Nested Effects ModelsMartin Pirkl, Niko Beerenwinkel
Frontiers in Immunology|January 21, 2025
Current methods for detecting and assessing HIV-1 antibody resistanceStanley Odidika, Martin Pirkl, Thomas Lengauer, et al.
Bioinformatics (Oxford, England)|November 20, 2015
Analyzing synergistic and non-synergistic interactions in signalling pathways using Boolean Nested Effect ModelsMartin Pirkl, Elisabeth Hand, Dieter Kube, et al.
Bioinformatics (Oxford, England)|December 20, 2021
Identifying cancer pathway dysregulations using differential causal effectsKim Philipp Jablonski, Martin Pirkl, Domagoj Ćevid, et al.
Plos Computational Biology|April 14, 2017
Inferring modulators of genetic interactions with epistatic nested effects modelsMartin Pirkl, Madeline Diekmann, Marlies van der Wees, et al.
Life Science Alliance|November 25, 2021
Hierarchy of TGFβ/SMAD, Hippo/YAP/TAZ, and Wnt/β-catenin signaling in melanoma phenotype switchingFabiana Lüönd, Martin Pirkl, Mizue Hisano, et al.
NAR Molecular Medicine|November 19, 2025
Geno2pheno: recombination detection for HIV-1 and HEV subtypesMartin Pirkl, Joachim Büch, Georg Friedrich, et al.
Metabolic Engineering|June 20, 2022
dCas9-mediated dysregulation of gene expression in human induced pluripotent stem cells during primitive streak differentiationViktor Haellman, Martin Pirkl, Arslan Akmammedov, et al.
The Journal of Infectious Diseases|July 30, 2022
Viral Load Dynamics in SARS-CoV-2 Omicron Breakthrough InfectionsFelix Dewald, Susanne Detmer, Martin Pirkl, et al.
Pageof 3

Showing results (1-10 of 23) with videos related to

Sort By:
Pageof 3
Bioinformatics (Oxford, England)|February 22, 2021
Inferring perturbation profiles of cancer samplesMartin Pirkl, Niko Beerenwinkel
Bioinformatics (Oxford, England)|November 14, 2018
Single cell network analysis with a mixture of Nested Effects ModelsMartin Pirkl, Niko Beerenwinkel
Frontiers in Immunology|January 21, 2025
Current methods for detecting and assessing HIV-1 antibody resistanceStanley Odidika, Martin Pirkl, Thomas Lengauer, et al.
Bioinformatics (Oxford, England)|November 20, 2015
Analyzing synergistic and non-synergistic interactions in signalling pathways using Boolean Nested Effect ModelsMartin Pirkl, Elisabeth Hand, Dieter Kube, et al.
Bioinformatics (Oxford, England)|December 20, 2021
Identifying cancer pathway dysregulations using differential causal effectsKim Philipp Jablonski, Martin Pirkl, Domagoj Ćevid, et al.
Plos Computational Biology|April 14, 2017
Inferring modulators of genetic interactions with epistatic nested effects modelsMartin Pirkl, Madeline Diekmann, Marlies van der Wees, et al.
Life Science Alliance|November 25, 2021
Hierarchy of TGFβ/SMAD, Hippo/YAP/TAZ, and Wnt/β-catenin signaling in melanoma phenotype switchingFabiana Lüönd, Martin Pirkl, Mizue Hisano, et al.
NAR Molecular Medicine|November 19, 2025
Geno2pheno: recombination detection for HIV-1 and HEV subtypesMartin Pirkl, Joachim Büch, Georg Friedrich, et al.
Metabolic Engineering|June 20, 2022
dCas9-mediated dysregulation of gene expression in human induced pluripotent stem cells during primitive streak differentiationViktor Haellman, Martin Pirkl, Arslan Akmammedov, et al.
The Journal of Infectious Diseases|July 30, 2022
Viral Load Dynamics in SARS-CoV-2 Omicron Breakthrough InfectionsFelix Dewald, Susanne Detmer, Martin Pirkl, et al.
Pageof 3