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A Bioinformatics View on Acute Myeloid Leukemia Surface Molecules by Combined Bayesian and ABC Analysis

“Big omics data” provoke the challenge of extracting meaningful information with clinical benefit. Here, we propose a two-step approach, an initial unsupervised inspection of the structure of the high dimensional data followed by supervised analysis of gene expression levels, to reconstruct the surf...

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Main Authors: Thrun, Michael C., Mack, Elisabeth K. M., Neubauer, Andreas, Haferlach, Torsten, Frech, Miriam, Ultsch, Alfred, Brendel, Cornelia
Format: Article
Language:English
Published: Philipps-Universität Marburg 2022
Subjects:
CD genes
leukemia
cluster of differentiation genes
gene expressions
Bayesian machine learning
Mathematik
Mathematics
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Call Number: urn:nbn:de:hebis:04-es2023-01445
Publication Date: 2023-10-04
Source: Erstveröffentlichung: Thrun, M.C.; Mack, E.K.M.; Neubauer, A.; Haferlach, T.; Frech, M.; Ultsch, A.; Brendel, C. A Bioinformatics View on Acute Myeloid Leukemia Surface Molecules by Combined Bayesian and ABC Analysis. Bioengineering 2022, 9, 642. https://doi.org/10.3390/bioengineering9110642
Downloads: 34 (2025), 130 (2024), 35 (2023)
License: https://creativecommons.org/licenses/by/4.0
Access URL: https://archiv.ub.uni-marburg.de/es/2023/0144
https://doi.org/10.3390/bioengineering9110642

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