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Machine learning on multiple epigenetic features reveals H3K27Ac as a driver of gene expression prediction across patients with glioblastoma

Fig 5

Feature importance scores extracted from our cross-patient CIPHER model for GSC1 → GSC2.

The model identifies the H3K27Ac feature as the most important for the prediction of RNA-seq. The results visualized are the means over 10 experimental runs, with the error bars denoting the standard deviation.

Fig 5

doi: https://doi.org/10.1371/journal.pcbi.1012272.g005