cACP-DeepGram: Classification of anticancer peptides via deep neural network and skip-gram-based word embedding model

作者：

Highlights：

• An Intelligent Computational model is developed for prediction of anticancer peptides.

• Word embedding features are utilized to numerically represent anticancer samples.

• DNN based learning approach is used to evaluate the model.

• Obtained quite promising results than existing methods

摘要

•An Intelligent Computational model is developed for prediction of anticancer peptides.•Word embedding features are utilized to numerically represent anticancer samples.•DNN based learning approach is used to evaluate the model.•Obtained quite promising results than existing methods

论文关键词：Deep neural network,Anticancer peptides,Word embedding,FastText,Classification

论文评审过程：Received 10 November 2021, Revised 24 May 2022, Accepted 4 July 2022, Available online 6 July 2022, Version of Record 8 July 2022.

论文官网地址：https://doi.org/10.1016/j.artmed.2022.102349