Using Gene Expression Music Algorithms (GEMusicA) for the Characterization of Human Stem Cells
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Publisher
Springer US
Link
http://link.springer.com/content/pdf/10.1007/978-1-0716-1225-5_14
Reference10 articles.
1. Staege MS (2015) A short treatise concerning a musical approach for the interpretation of gene expression data. Sci Rep 5:15281
2. Staege MS (2016) Gene expression music algorithm-based characterization of the Ewing sarcoma stem cell signature. Stem Cells Int 2016:7674824
3. Mueller T, Hantsch C, Volkmer I, Staege MS (2018) Differentiation-dependent regulation of human endogenous retrovirus K sequences and neighboring genes in germ cell tumor cells. Front Microbiol 9:1253
4. Barrett T, Wilhite SE, Ledoux P et al (2013) NCBI GEO: archive for functional genomics data sets—update. Nucleic Acids Res 41(Database issue):D991–D995
5. Wang Z, Gearhart MD, Lee YW et al (2018) A non-canonical BCOR-PRC1.1 complex represses differentiation programs in human ESCs. Cell Stem Cell 22:235–251
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