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Recent Development of Computational Predicting Bioluminescent Proteins.
Zhang, Dan; Guan, Zheng-Xing; Zhang, Zi-Mei; Li, Shi-Hao; Dao, Fu-Ying; Tang, Hua; Lin, Hao.
Afiliação
  • Zhang D; Key Laboratory for Neuro-Information of Ministry of Education, School of Life Science and Technology, Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu 610054, China.
  • Guan ZX; Key Laboratory for Neuro-Information of Ministry of Education, School of Life Science and Technology, Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu 610054, China.
  • Zhang ZM; Key Laboratory for Neuro-Information of Ministry of Education, School of Life Science and Technology, Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu 610054, China.
  • Li SH; Key Laboratory for Neuro-Information of Ministry of Education, School of Life Science and Technology, Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu 610054, China.
  • Dao FY; Key Laboratory for Neuro-Information of Ministry of Education, School of Life Science and Technology, Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu 610054, China.
  • Tang H; Department of Pathophysiology, Southwest Medical University, Luzhou 646000, China.
  • Lin H; Key Laboratory for Neuro-Information of Ministry of Education, School of Life Science and Technology, Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu 610054, China.
Curr Pharm Des ; 25(40): 4264-4273, 2019.
Article em En | MEDLINE | ID: mdl-31696804
ABSTRACT
Bioluminescent Proteins (BLPs) are widely distributed in many living organisms that act as a key role of light emission in bioluminescence. Bioluminescence serves various functions in finding food and protecting the organisms from predators. With the routine biotechnological application of bioluminescence, it is recognized to be essential for many medical, commercial and other general technological advances. Therefore, the prediction and characterization of BLPs are significant and can help to explore more secrets about bioluminescence and promote the development of application of bioluminescence. Since the experimental methods are money and time-consuming for BLPs identification, bioinformatics tools have played important role in fast and accurate prediction of BLPs by combining their sequences information with machine learning methods. In this review, we summarized and compared the application of machine learning methods in the prediction of BLPs from different aspects. We wish that this review will provide insights and inspirations for researches on BLPs.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Biologia Computacional / Aprendizado de Máquina / Proteínas Luminescentes Idioma: En Ano de publicação: 2019 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Biologia Computacional / Aprendizado de Máquina / Proteínas Luminescentes Idioma: En Ano de publicação: 2019 Tipo de documento: Article