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Martin Sill

Showing results (131-140 of 149) with videos related to

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Cancer Cell|May 13, 2015
Molecular Classification of Ependymal Tumors across All CNS Compartments, Histopathological Grades, and Age GroupsKristian W Pajtler, Hendrik Witt, Martin Sill, et al.
Acta Neuropathologica|August 6, 2021
Recurrent fusions in PLAGL1 define a distinct subset of pediatric-type supratentorial neuroepithelial tumorsPhilipp Sievers, Sophie C Henneken, Christina Blume, et al.
Journal of Clinical Oncology : Official Journal of the American Society of Clinical Oncology|October 7, 2021
Integrated Molecular-Morphologic Meningioma Classification: A Multicenter Retrospective Analysis, Retrospectively and Prospectively ValidatedSybren L N Maas, Damian Stichel, Thomas Hielscher, et al.
Nature Medicine|October 24, 2023
Author Correction: Multiomic neuropathology improves diagnostic accuracy in pediatric neuro-oncologyDominik Sturm, David Capper, Felipe Andreiuolo, et al.
Acta Neuropathologica|August 21, 2021
PATZ1 fusions define a novel molecularly distinct neuroepithelial tumor entity with a broad histological spectrumKaram T Alhalabi, Damian Stichel, Philipp Sievers, et al.
Nature Medicine|March 17, 2023
Multiomic neuropathology improves diagnostic accuracy in pediatric neuro-oncologyDominik Sturm, David Capper, Felipe Andreiuolo, et al.
Acta Neuropathologica|July 19, 2018
Heterogeneity within the PF-EPN-B ependymoma subgroupFlorence M G Cavalli, Jens-Martin Hübner, Tanvi Sharma, et al.
Nature Communications|November 28, 2022
DNA methylation-based classification of sinonasal tumorsPhilipp Jurmeister, Stefanie Glöß, Renée Roller, et al.
Nature|December 6, 2019
The molecular landscape of ETMR at diagnosis and relapseSander Lambo, Susanne N Gröbner, Tobias Rausch, et al.
Nature Genetics|February 9, 2026
A microenvironment-determined risk continuum refines subtyping in meningioma and reveals determinants of machine learning-based tumor classificationSybren L N Maas, Yiheng Tang, Eric Stutheit-Zhao, et al.
Pageof 15

Showing results (131-140 of 149) with videos related to

Sort By:
Pageof 15
Cancer Cell|May 13, 2015
Molecular Classification of Ependymal Tumors across All CNS Compartments, Histopathological Grades, and Age GroupsKristian W Pajtler, Hendrik Witt, Martin Sill, et al.
Acta Neuropathologica|August 6, 2021
Recurrent fusions in PLAGL1 define a distinct subset of pediatric-type supratentorial neuroepithelial tumorsPhilipp Sievers, Sophie C Henneken, Christina Blume, et al.
Journal of Clinical Oncology : Official Journal of the American Society of Clinical Oncology|October 7, 2021
Integrated Molecular-Morphologic Meningioma Classification: A Multicenter Retrospective Analysis, Retrospectively and Prospectively ValidatedSybren L N Maas, Damian Stichel, Thomas Hielscher, et al.
Nature Medicine|October 24, 2023
Author Correction: Multiomic neuropathology improves diagnostic accuracy in pediatric neuro-oncologyDominik Sturm, David Capper, Felipe Andreiuolo, et al.
Acta Neuropathologica|August 21, 2021
PATZ1 fusions define a novel molecularly distinct neuroepithelial tumor entity with a broad histological spectrumKaram T Alhalabi, Damian Stichel, Philipp Sievers, et al.
Nature Medicine|March 17, 2023
Multiomic neuropathology improves diagnostic accuracy in pediatric neuro-oncologyDominik Sturm, David Capper, Felipe Andreiuolo, et al.
Acta Neuropathologica|July 19, 2018
Heterogeneity within the PF-EPN-B ependymoma subgroupFlorence M G Cavalli, Jens-Martin Hübner, Tanvi Sharma, et al.
Nature Communications|November 28, 2022
DNA methylation-based classification of sinonasal tumorsPhilipp Jurmeister, Stefanie Glöß, Renée Roller, et al.
Nature|December 6, 2019
The molecular landscape of ETMR at diagnosis and relapseSander Lambo, Susanne N Gröbner, Tobias Rausch, et al.
Nature Genetics|February 9, 2026
A microenvironment-determined risk continuum refines subtyping in meningioma and reveals determinants of machine learning-based tumor classificationSybren L N Maas, Yiheng Tang, Eric Stutheit-Zhao, et al.
Pageof 15