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Phage_UniR_LGBM: Phage Virion Proteins Classification with UniRep Features and LightGBM Model.
Bao, Wenzheng; Cui, Qingyu; Chen, Baitong; Yang, Bin.
Afiliação
  • Bao W; Xuzhou University of Technology, Xuzhou 221018, China.
  • Cui Q; University of Jinan, Jinan 250024, China.
  • Chen B; Xuzhou First People's Hospital, Xuzhou 221000, China.
  • Yang B; Zaozhuang University, Zaozhuang 277160, China.
Comput Math Methods Med ; 2022: 9470683, 2022.
Article em En | MEDLINE | ID: mdl-35465015
ABSTRACT
Phage, the most prevalent creature on the planet, serves a variety of critical roles. Phage's primary role is to facilitate gene-to-gene communication. The phage proteins can be defined as the virion proteins and the nonvirion ones. Nowadays, experimental identification is a difficult process that necessitates a significant amount of laboratory time and expense. Considering such situation, it is critical to design practical calculating techniques and develop well-performance tools. In this work, the Phage_UniR_LGBM has been proposed to classify the virion proteins. In detailed, such model utilizes the UniRep as the feature and the LightGBM algorithm as the classification model. And then, the training data train the model, and the testing data test the model with the cross-validation. The Phage_UniR_LGBM was compared with the several state-of-the-art features and classification algorithms. The performances of the Phage_UniR_LGBM are 88.51% in Sp,89.89% in Sn, 89.18% in Acc, 0.7873 in MCC, and 0.8925 in F1 score.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Bacteriófagos Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Bacteriófagos Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2022 Tipo de documento: Article