DeepCellState: An autoencoder-based framework for predicting cell type specific transcriptional states induced by drug treatment

DeepCellState: An autoencoder-based framework for predicting cell type specific transcriptional states induced by drug treatment

Drug treatment induces cell type specific transcriptional programs, and as the number of combinations of drugs and cell types grows, the cost for exhaustive screens measuring the transcriptional drug response becomes intractable. We developed DeepCellState, a deep learning autoencoder-based framewor...

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Bibliographic Details
Main Authors: Arner, E. (Author), Li, Y. (Author), Umarov, R. (Author)
Format: Article
Language:English
Published: Public Library of Science 2021
Subjects:
antineoplastic agent
Antineoplastic Agents
Article
autoencoder
biology
cell function
cells by body anatomy
Computational Biology
correlational study
deep learning
Deep Learning
drug effect
drug response
drug therapy
gene knockdown
Gene Knockdown Techniques
genetics
Hep-G2 cell line
human
Humans
MCF-7 cell line
MCF-7 Cells
PC-3 Cells
prediction
procedures
THP-1 cell line
transcriptome
Transcriptome
unsupervised machine learning
Unsupervised Machine Learning
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