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Tim Breitenbach

Showing results (1-10 of 14) with videos related to

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Frontiers in Bioinformatics|September 22, 2025
Adaptive sampling methods facilitate the determination of reliable dataset sizes for evidence-based modelingTim Breitenbach, Thomas Dandekar
Scientific Reports|June 6, 2026
DataXflowGen for GenAI-driven model generationSamantha A W Crouch, Tim Breitenbach
International Journal of Molecular Sciences|May 5, 2019
How to Steer and Control ERK and the ERK Signaling Cascade Exemplified by Looking at Cardiac InsufficiencyTim Breitenbach, Kristina Lorenz, Thomas Dandekar
Scientific Reports|August 10, 2021
An effective model of endogenous clocks and external stimuli determining circadian rhythmsTim Breitenbach, Charlotte Helfrich-Förster, Thomas Dandekar
Bioinformatics (Oxford, England)|July 9, 2022
Optimization of synthetic molecular reporters for a mesenchymal glioblastoma transcriptional program by integer programingTim Breitenbach, Matthias Jürgen Schmitt, Thomas Dandekar
Plos Computational Biology|July 17, 2019
Analyzing pharmacological intervention points: A method to calculate external stimuli to switch between steady states in regulatory networksTim Breitenbach, Chunguang Liang, Niklas Beyersdorf, et al.
Computational and Structural Biotechnology Journal|August 18, 2025
gSELECT: A novel pre-analysis machine-learning library enabling early hypothesis testing and predictive gene selection in single-cell dataDeniz Caliskan, Aylin Caliskan, Thomas Dandekar, et al.
Computational and Structural Biotechnology Journal|May 6, 2024
DataXflow: Synergizing data-driven modeling with best parameter fit and optimal control - An efficient data analysis for cancer researchSamantha A W Crouch, Jan Krause, Thomas Dandekar, et al.
Plos One|April 17, 2024
An orchestra of machine learning methods reveals landmarks in single-cell data exemplified with aging fibroblastsLauritz Rasbach, Aylin Caliskan, Fatemeh Saderi, et al.
Computational and Structural Biotechnology Journal|June 19, 2023
Optimized cell type signatures revealed from single-cell data by combining principal feature analysis, mutual information, and machine learningAylin Caliskan, Deniz Caliskan, Lauritz Rasbach, et al.
Pageof 2

Showing results (1-10 of 14) with videos related to

Sort By:
Pageof 2
Frontiers in Bioinformatics|September 22, 2025
Adaptive sampling methods facilitate the determination of reliable dataset sizes for evidence-based modelingTim Breitenbach, Thomas Dandekar
Scientific Reports|June 6, 2026
DataXflowGen for GenAI-driven model generationSamantha A W Crouch, Tim Breitenbach
International Journal of Molecular Sciences|May 5, 2019
How to Steer and Control ERK and the ERK Signaling Cascade Exemplified by Looking at Cardiac InsufficiencyTim Breitenbach, Kristina Lorenz, Thomas Dandekar
Scientific Reports|August 10, 2021
An effective model of endogenous clocks and external stimuli determining circadian rhythmsTim Breitenbach, Charlotte Helfrich-Förster, Thomas Dandekar
Bioinformatics (Oxford, England)|July 9, 2022
Optimization of synthetic molecular reporters for a mesenchymal glioblastoma transcriptional program by integer programingTim Breitenbach, Matthias Jürgen Schmitt, Thomas Dandekar
Plos Computational Biology|July 17, 2019
Analyzing pharmacological intervention points: A method to calculate external stimuli to switch between steady states in regulatory networksTim Breitenbach, Chunguang Liang, Niklas Beyersdorf, et al.
Computational and Structural Biotechnology Journal|August 18, 2025
gSELECT: A novel pre-analysis machine-learning library enabling early hypothesis testing and predictive gene selection in single-cell dataDeniz Caliskan, Aylin Caliskan, Thomas Dandekar, et al.
Computational and Structural Biotechnology Journal|May 6, 2024
DataXflow: Synergizing data-driven modeling with best parameter fit and optimal control - An efficient data analysis for cancer researchSamantha A W Crouch, Jan Krause, Thomas Dandekar, et al.
Plos One|April 17, 2024
An orchestra of machine learning methods reveals landmarks in single-cell data exemplified with aging fibroblastsLauritz Rasbach, Aylin Caliskan, Fatemeh Saderi, et al.
Computational and Structural Biotechnology Journal|June 19, 2023
Optimized cell type signatures revealed from single-cell data by combining principal feature analysis, mutual information, and machine learningAylin Caliskan, Deniz Caliskan, Lauritz Rasbach, et al.
Pageof 2