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A Path-based Method for Identification of Protein Phenotypic Annotations

文献类型： 外文期刊

作者： Gao, Jian 1 ; Hu, Bin 2 ; Chen, Lei 1 ;

作者机构： 1.Shanghai Maritime Univ, Coll Informat Engn, Shanghai 201306, Peoples R China

2.Guangdong Acad Agr Sci, Inst Anim Sci,Guangdong Publ Lab Anim Breeding &, State Key Lab Livestock & Poultry Breeding, Guangdong Prov Key Lab Anim Breeding & Nutr, Guangzhou 510640, Peoples R China

关键词： Protein; phenotype; heterogeneous network; protein-protein interaction; path; jackknife test

期刊名称：CURRENT BIOINFORMATICS （ 影响因子：3.543； 五年影响因子：2.048 ）

ISSN： 1574-8936

年卷期： 2021 年 16 卷 9 期

页码：

收录情况： SCI

摘要： Background: Identification of protein phenotypic annotations is an essential and challenging problem in modern genetics. Such problem is related to some serious diseases, including cancers, HIV and so on. The factors of genotype and environment increase the difficulties in determining the phenotype of proteins. The experiment methods to achieve such a goal are always timeconsuming and expensive. Objective: The aim of this study was to design a quick and cheap method for determining the phenotypes of proteins. Methods: In this study, we proposed a network computational method to identify novel phenotypic annotations of proteins. To execute such method, a heterogeneous network was constructed, which contained three sub-networks: protein network, phenotypic type network, and protein-phenotypic type network. The method tried to find out all paths with limited length, which connected one protein and one phenotypic type. A scoring scheme was adopted to count obtained paths and induced a score to indicate the associations between them. Results and Conclusion: The ROC and PR curve analyses were done to evaluate the performance of the method, indicating the utility of the method. Our method was superior to other network methods, which incorporated popular network algorithms.

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