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Advances in phage-host interaction prediction: in silico method enhances the development of phage therapies.
Nie, Wanchun; Qiu, Tianyi; Wei, Yiwen; Ding, Hao; Guo, Zhixiang; Qiu, Jingxuan.
Afiliación
  • Nie W; School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, 200093, China.
  • Qiu T; Institute of Clinical Science, Zhongshan Hospital; Intelligent Medicine Institute, Fudan University, Shanghai, 200032, China.
  • Wei Y; Shanghai Institute of Infectious Disease and Biosecurity, Fudan University, Shanghai, 200032, China.
  • Ding H; School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, 200093, China.
  • Guo Z; Institute of Clinical Science, Zhongshan Hospital; Intelligent Medicine Institute, Fudan University, Shanghai, 200032, China.
  • Qiu J; School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, 200093, China.
Brief Bioinform ; 25(3)2024 Mar 27.
Article en En | MEDLINE | ID: mdl-38555471
ABSTRACT
Phages can specifically recognize and kill bacteria, which lead to important application value of bacteriophage in bacterial identification and typing, livestock aquaculture and treatment of human bacterial infection. Considering the variety of human-infected bacteria and the continuous discovery of numerous pathogenic bacteria, screening suitable therapeutic phages that are capable of infecting pathogens from massive phage databases has been a principal step in phage therapy design. Experimental methods to identify phage-host interaction (PHI) are time-consuming and expensive; high-throughput computational method to predict PHI is therefore a potential substitute. Here, we systemically review bioinformatic methods for predicting PHI, introduce reference databases and in silico models applied in these methods and highlight the strengths and challenges of current tools. Finally, we discuss the application scope and future research direction of computational prediction methods, which contribute to the performance improvement of prediction models and the development of personalized phage therapy.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Bacteriófagos / Simulación por Computador / Biología Computacional / Terapia de Fagos Límite: Animals / Humans Idioma: En Revista: Brief Bioinform Asunto de la revista: BIOLOGIA / INFORMATICA MEDICA Año: 2024 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Bacteriófagos / Simulación por Computador / Biología Computacional / Terapia de Fagos Límite: Animals / Humans Idioma: En Revista: Brief Bioinform Asunto de la revista: BIOLOGIA / INFORMATICA MEDICA Año: 2024 Tipo del documento: Article País de afiliación: China