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Michael Baudis

Researcher at Swiss Institute of Bioinformatics

Publications -  115
Citations -  4514

Michael Baudis is an academic researcher from Swiss Institute of Bioinformatics. The author has contributed to research in topics: Comparative genomic hybridization & Copy-number variation. The author has an hindex of 31, co-authored 105 publications receiving 3727 citations. Previous affiliations of Michael Baudis include RWTH Aachen University & Loyola University Chicago.

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Integrated Molecular Meta-Analysis of 1,000 Pediatric High-Grade and Diffuse Intrinsic Pontine Glioma

Alan Mackay, +66 more
- 09 Oct 2017 - 
TL;DR: Genomic aberrations increase with age, highlighting the infant population as biologically and clinically distinct, and co-segregating mutations in histone-mutant subgroups including loss of FBXW7 in H 3.3G34R/V, TOP3A rearrangements in H3.3K27M, and BCOR mutations in H2.1K 27M are identified.
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Analysis of genomic alterations in benign, atypical, and anaplastic meningiomas: toward a genetic model of meningioma progression.

TL;DR: A model for the genomic alterations associated with meningioma progression is proposed on the basis of the most common aberrations identified in the various malignancy grades.
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Progenetix.net: an online repository for molecular cytogenetic aberration data.

TL;DR: Progenetix.net is a new online repository for previously published chromosomal aberration data, allowing the addition of band-specific information about chromosomal imbalances to oncologic data analysis efforts.
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Translocations involving 8q24 in Burkitt lymphoma and other malignant lymphomas: a historical review of cytogenetics in the light of todays knowledge

TL;DR: The diagnosis of BL should be restricted to cases with expression of CD10 and BCL6, absence or very weak expression of BCL2 protein, a homogeneously very high proliferation index and a proven IG-MYC translocation without evidence of a chromosomal translocation typical for other lymphoma entities.
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Unequivocal Delineation of Clinicogenetic Subgroups and Development of a New Model for Improved Outcome Prediction in Neuroblastoma

TL;DR: A new regression model for improved patient outcome prediction is proposed, incorporating tumor stage, chromosome 17, and amplification/deletion status and may prove highly valuable with respect to more reliable risk assessment, evaluation of clinical results, and optimization of current treatment protocols.