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

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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主要な著者: Thrun, Michael C., Mack, Elisabeth K. M., Neubauer, Andreas, Haferlach, Torsten, Frech, Miriam, Ultsch, Alfred, Brendel, Cornelia
フォーマット: 論文
言語:英語
出版事項: Philipps-Universität Marburg 2022
主題:
leukemia
gene expressions
Bayesian machine learning
cluster of differentiation genes
CD genes
Mathematik
Mathematics
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