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Markus Reischl

Showing results (31-40 of 81) with videos related to

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Plos One|October 8, 2015
A Zebrafish Drug-Repurposing Screen Reveals sGC-Dependent and sGC-Independent Pro-Inflammatory Activities of Nitric OxideChristine Wittmann, Markus Reischl, Asmi H Shah, et al.
Bioengineered|June 11, 2016
Automated phenotype pattern recognition of zebrafish for high-throughput screeningMark Schutera, Thomas Dickmeis, Marina Mione, et al.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|December 12, 2023
AI<sup>2</sup>Seg: A Method and Tool for AI-based Annotation Inspection of Biomedical Instance Segmentation DatasetsMarcel P Schilling, Lukas Klinger, Ulrike Schumacher, et al.
Zebrafish|July 9, 2014
Automatic zebrafish heartbeat detection and analysis for zebrafish embryosChristian Pylatiuk, Daniela Sanchez, Ralf Mikut, et al.
Bioinformatics (Oxford, England)|October 19, 2013
Automated prior knowledge-based quantification of neuronal patterns in the spinal cord of zebrafishJohannes Stegmaier, Maryam Shahid, Masanari Takamiya, et al.
SLAS Technology|March 9, 2026
A method for the evaluation of automated solid dosing technologies for mid-scale dosing tasks in laboratory automationAziza El Hariry, Alexander Hirvell, Philipp Nöcker, et al.
Advanced Healthcare Materials|July 8, 2022
Droplet Microarray Based Screening Identifies Proteins for Maintaining Pluripotency of hiPSCsYanxi Liu, Sarah Bertels, Markus Reischl, et al.
Plos Computational Biology|December 20, 2019
Motion prediction enables simulated MR-imaging of freely moving model organismsMarkus Reischl, Mazin Jouda, Neil MacKinnon, et al.
Npj Computational Materials|September 25, 2025
Leveraging unlabeled SEM datasets with self-supervised learning for enhanced particle segmentationLuca Rettenberger, Nathan J Szymanski, Andrea Giunto, et al.
Bioinformatics (Oxford, England)|June 27, 2020
BeadNet: deep learning-based bead detection and counting in low-resolution microscopy imagesTim Scherr, Karolin Streule, Andreas Bartschat, et al.
Pageof 9

Showing results (31-40 of 81) with videos related to

Sort By:
Pageof 9
Plos One|October 8, 2015
A Zebrafish Drug-Repurposing Screen Reveals sGC-Dependent and sGC-Independent Pro-Inflammatory Activities of Nitric OxideChristine Wittmann, Markus Reischl, Asmi H Shah, et al.
Bioengineered|June 11, 2016
Automated phenotype pattern recognition of zebrafish for high-throughput screeningMark Schutera, Thomas Dickmeis, Marina Mione, et al.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|December 12, 2023
AI<sup>2</sup>Seg: A Method and Tool for AI-based Annotation Inspection of Biomedical Instance Segmentation DatasetsMarcel P Schilling, Lukas Klinger, Ulrike Schumacher, et al.
Zebrafish|July 9, 2014
Automatic zebrafish heartbeat detection and analysis for zebrafish embryosChristian Pylatiuk, Daniela Sanchez, Ralf Mikut, et al.
Bioinformatics (Oxford, England)|October 19, 2013
Automated prior knowledge-based quantification of neuronal patterns in the spinal cord of zebrafishJohannes Stegmaier, Maryam Shahid, Masanari Takamiya, et al.
SLAS Technology|March 9, 2026
A method for the evaluation of automated solid dosing technologies for mid-scale dosing tasks in laboratory automationAziza El Hariry, Alexander Hirvell, Philipp Nöcker, et al.
Advanced Healthcare Materials|July 8, 2022
Droplet Microarray Based Screening Identifies Proteins for Maintaining Pluripotency of hiPSCsYanxi Liu, Sarah Bertels, Markus Reischl, et al.
Plos Computational Biology|December 20, 2019
Motion prediction enables simulated MR-imaging of freely moving model organismsMarkus Reischl, Mazin Jouda, Neil MacKinnon, et al.
Npj Computational Materials|September 25, 2025
Leveraging unlabeled SEM datasets with self-supervised learning for enhanced particle segmentationLuca Rettenberger, Nathan J Szymanski, Andrea Giunto, et al.
Bioinformatics (Oxford, England)|June 27, 2020
BeadNet: deep learning-based bead detection and counting in low-resolution microscopy imagesTim Scherr, Karolin Streule, Andreas Bartschat, et al.
Pageof 9