Intact cell mass spectrometry for revealing single gene changes in mammalian cells. Biostatistics and artificial intelligence data evaluation
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| Year of publication | 2020 |
| Type | Conference abstract |
| Citation | |
| Description | Changes in mass spectra profiles possibly reflecting changes in the inner cellular environment allowed discrimination using multivariate statistical methods or classification via self-learning approaches e.g. artificial neural networks (ANN). The mass spectra obtained from intact mammalian cells with or without TUSC3 silencing, were post-processed and evaluated using the R Studio or eMSTAT Solution. |
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