Intact cell mass spectrometry for revealing single gene changes in mammalian cells. Biostatistics and artificial intelligence data evaluation

Authors

PEČINKA Lukáš MORÁŇ Lukáš VAŇHARA Petr HAVEL Josef

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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