T4SE-XGB: Interpretable Sequence-Based Prediction of Type IV Secreted Effectors Using eXtreme Gradient Boosting Algorithm

T4SE-XGB: Interpretable Sequence-Based Prediction of Type IV Secreted Effectors Using eXtreme Gradient Boosting Algorithm

Type IV secreted effectors (T4SEs) can be translocated into the cytosol of host cells via type IV secretion system (T4SS) and cause diseases. However, experimental approaches to identify T4SEs are time- and resource-consuming, and the existing computational tools based on machine learning techniques...

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Bibliographic Details
Main Authors: Tianhang Chen, Xiangeng Wang, Yanyi Chu, Yanjing Wang, Mingming Jiang, Dong-Qing Wei, Yi Xiong
Format: Article
Language:English
Published: Frontiers Media S.A. 2020-09-01
Series:Frontiers in Microbiology
Subjects:
type IV secreted effector
feature secelction
extreme gradient boosting
interpretable analysis
SHAP (SHapley additive exPlanations)
Online Access:https://www.frontiersin.org/article/10.3389/fmicb.2020.580382/full

Internet

https://www.frontiersin.org/article/10.3389/fmicb.2020.580382/full

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