A Standardized Framework for Taxonomy Analysis in Bacterial Kingdom based on Protein Domain
Boqian Wang, Jianglin Zhou, Yuan Jin, Mingda Hu, Yunxiang Zhao, Xin Wang, Long Liang, Junjie Yue, Hongguang Ren
Abstract
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Boqian Wang, Jianglin Zhou, Yuan Jin, Mingda Hu, Yunxiang Zhao, Xin Wang, Long Liang, Junjie Yue, Hongguang Ren
Abstract
Open-access reader
Abstract The taxonomy research on the bacterial kingdom is important and can be usually conducted by the analysis on conserved genes, 16s rRNA, protein domain, and so on. Comparatively, the protein domains maintain a most direct relationship with phenotypes. In this paper, based on the protein domain, we propose a 3-step framework to standardize the classification process of bacteria. Different model candidates are involved and discussed in each step. By comparing the classification results with existing taxonomy, we select the most appropriate candidate to improve the framework, and furthermore, discuss their biological significance. Finally, we put forward taxonomy suggestions based on the best classification results. Importance We standardize a 3-step framework to carry out bacterial taxonomy research based on protein domain. Furthermore, we filter out the best solution in each step that can together generate the most appropriate classification result, and at the same time, we discuss the biological significant it indicates. Finally, we propose suggestions on NCBI bacterial taxonomy based on the classification results.
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Abstract The taxonomy research on the bacterial kingdom is important and can be usually conducted by the analysis on conserved genes, 16s rRNA, protein domain, and so on. Comparatively, the protein domains maintain a most direct relationship with phenotypes. In this paper, based on the protein domain, we propose a 3-step framework to standardize the classification process of bacteria. Different model candidates are involved and discussed in each step. By comparing the classification results with existing taxonomy, we select the most appropriate candidate to improve the framework, and furthermore, discuss their biological significance. Finally, we put forward taxonomy suggestions based on the best classification results. Importance We standardize a 3-step framework to carry out bacterial taxonomy research based on protein domain. Furthermore, we filter out the best solution in each step that can together generate the most appropriate classification result, and at the same time, we discuss the biological significant it indicates. Finally, we propose suggestions on NCBI bacterial taxonomy based on the classification results.
Key concepts: Taxonomy (biology), Bacterial taxonomy, Computer science, Domain (mathematical analysis), Computational biology, Data mining, Information retrieval, 16S ribosomal RNA