On predicting epithelial mesenchymal transition by integrating RNA-binding proteins and correlation data via L1/2-regularization method

作者：

Highlights：

• We proposed a model for identifying the important RBPs during epithelial-mesenchymal transition (EMT).

• L1/2-regularization model as a feature selector extends the model of LASSO.

• L1/2-regularization model is successfully applied for identifying significant RBPs in biological researches.

• The identified RBPs will facilitate biologists to study the underlying mechanism of EMT.

摘要

•We proposed a model for identifying the important RBPs during epithelial-mesenchymal transition (EMT).•L1/2-regularization model as a feature selector extends the model of LASSO.•L1/2-regularization model is successfully applied for identifying significant RBPs in biological researches.•The identified RBPs will facilitate biologists to study the underlying mechanism of EMT.

论文关键词：L1/2-regularization,Classification,RNA-binding proteins (RBPs),Epithelial-mesenchymal transition (EMT)

论文评审过程：Received 29 November 2017, Revised 20 September 2018, Accepted 30 September 2018, Available online 21 October 2018, Version of Record 20 March 2019.

论文官网地址：https://doi.org/10.1016/j.artmed.2018.09.005