期刊
COMPUTERS IN BIOLOGY AND MEDICINE
卷 146, 期 -, 页码 -出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.compbiomed.2022.105577
关键词
AMP prediction; Ensemble learning; LightGBM; Logistic regression
类别
资金
- National Natural Science Foundation of China [62102030]
In this paper, a novel AMP prediction method called AMPpred-EL is proposed, which utilizes ensemble learning strategy combined with LightGBM and logistic regression. The experimental results demonstrate that AMPpred-EL outperforms several state-of-the-art methods and improves efficiency performance.
Antimicrobial peptides (AMPs) are important for the human immune system and are currently applied in clinical trials. AMPs have been received much attention for accurate recognition. Recently, several computational methods for identifying AMPs have been proposed. However, existing methods have difficulty in accurately predicting AMPs. In this paper, we propose a novel AMP prediction method called AMPpred-EL based on an ensemble learning strategy. AMPred-EL is constructed based on ensemble learning combined with LightGBM and logistic regression. Experimental results demonstrate that AMPpred-EL outperforms several state-of-the-art methods on the benchmark datasets and then improves the efficiency performance.
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