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Markus Wolfien

Showing results (21-30 of 64) with videos related to

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Frontiers in Artificial Intelligence|October 20, 2025
Phase-specific kidney graft failure prediction with machine learning modelAmankeldi A Salybekov, Markus Wolfien, Ainur Yerkos, et al.
JMIR Medical Informatics|August 3, 2023
Methods Used in the Development of Common Data Models for Health Data: Scoping ReviewNajia Ahmadi, Michele Zoch, Patricia Kelbert, et al.
Studies in Health Technology and Informatics|August 23, 2024
A Concept for Integrating AI-Based Support Systems into Clinical PracticeKatja Hoffmann, Richard Gebler, Sophia Grummt, et al.
Studies in Health Technology and Informatics|August 23, 2024
Synthetic Data Generation in Hematology - Paving the Way for OMOP and FHIR IntegrationWaldemar Hahn, Najia Ahmadi, Katja Hoffmann, et al.
Studies in Health Technology and Informatics|June 30, 2023
Context-Sensitive Common Data Models for Genetic Rare Diseases - A ConceptNajia Ahmadi, Michele Zoch, Brita Sedlmayr, et al.
Advanced Drug Delivery Reviews|October 22, 2017
Stem cells and heart disease - Brake or accelerator?Gustav Steinhoff, Julia Nesteruk, Markus Wolfien, et al.
Advanced Drug Delivery Reviews|September 17, 2017
(Re-)programming of subtype specific cardiomyocytesFrauke Hausburg, Julia Jeannine Jung, Matti Hoch, et al.
Journal of Biotechnology|July 6, 2017
Customized workflow development and data modularization concepts for RNA-Sequencing and metatranscriptome experimentsSteffen C Lott, Markus Wolfien, Konstantin Riege, et al.
BMC Bioinformatics|January 8, 2016
TRAPLINE: a standardized and automated pipeline for RNA sequencing data analysis, evaluation and annotationMarkus Wolfien, Christian Rimmbach, Ulf Schmitz, et al.
Cellular and Molecular Life Sciences : CMLS|August 24, 2021
Quality control in scRNA-Seq can discriminate pacemaker cells: the mtRNA biasAnne-Marie Galow, Sophie Kussauer, Markus Wolfien, et al.
Pageof 7

Showing results (21-30 of 64) with videos related to

Sort By:
Pageof 7
Frontiers in Artificial Intelligence|October 20, 2025
Phase-specific kidney graft failure prediction with machine learning modelAmankeldi A Salybekov, Markus Wolfien, Ainur Yerkos, et al.
JMIR Medical Informatics|August 3, 2023
Methods Used in the Development of Common Data Models for Health Data: Scoping ReviewNajia Ahmadi, Michele Zoch, Patricia Kelbert, et al.
Studies in Health Technology and Informatics|August 23, 2024
A Concept for Integrating AI-Based Support Systems into Clinical PracticeKatja Hoffmann, Richard Gebler, Sophia Grummt, et al.
Studies in Health Technology and Informatics|August 23, 2024
Synthetic Data Generation in Hematology - Paving the Way for OMOP and FHIR IntegrationWaldemar Hahn, Najia Ahmadi, Katja Hoffmann, et al.
Studies in Health Technology and Informatics|June 30, 2023
Context-Sensitive Common Data Models for Genetic Rare Diseases - A ConceptNajia Ahmadi, Michele Zoch, Brita Sedlmayr, et al.
Advanced Drug Delivery Reviews|October 22, 2017
Stem cells and heart disease - Brake or accelerator?Gustav Steinhoff, Julia Nesteruk, Markus Wolfien, et al.
Advanced Drug Delivery Reviews|September 17, 2017
(Re-)programming of subtype specific cardiomyocytesFrauke Hausburg, Julia Jeannine Jung, Matti Hoch, et al.
Journal of Biotechnology|July 6, 2017
Customized workflow development and data modularization concepts for RNA-Sequencing and metatranscriptome experimentsSteffen C Lott, Markus Wolfien, Konstantin Riege, et al.
BMC Bioinformatics|January 8, 2016
TRAPLINE: a standardized and automated pipeline for RNA sequencing data analysis, evaluation and annotationMarkus Wolfien, Christian Rimmbach, Ulf Schmitz, et al.
Cellular and Molecular Life Sciences : CMLS|August 24, 2021
Quality control in scRNA-Seq can discriminate pacemaker cells: the mtRNA biasAnne-Marie Galow, Sophie Kussauer, Markus Wolfien, et al.
Pageof 7