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SSC-PPI: A Subspace Structure Consistency-Based Method for Protein-Protein Interactions Prediction

文献类型：期刊论文

作者Ma, Ziping3; Min, Weiqing4; Zhang, Huanpu1; Huang, Yulei5; Jiang, Shuqiang2
刊名IEEE TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS
出版日期2025-11-01
卷号22期号:6页码:2477-2490
关键词Proteins Feature extraction Drugs Diseases Amino acids Accuracy Predictive models Dimensionality reduction Data mining Databases Protein-protein interactions dimension reduction unsupervised feature selection latent representation learning
DOI10.1109/TCBBIO.2025.3592820
英文摘要Protein-protein interactions (PPIs) play an indispensable role in understanding disease-causing mechanisms, and the basic laws of food and drugs on life. Contemporary research on this issue, however, is incapable of guaranteeing structure consistency between extracted features and raw data, and fails to fully investigate the interconnection information of features. Thus, this paper proposes a subspace structure consistency-based method for protein-protein interactions prediction. SSC-PPI is not only capable of investigating the coherent relations between the encoded features generated from amino acid composition and conjoint triad numeric composition of F-vector, composition and transition descriptors, but also fully maintains the latent geometrical structure consistency between feature subspace and data space. Numerous comparative experiments demonstrate its excellent predictable performance with significant accuracies of 100%, 99.95%, 99.98%, 100% and 100% respectively on Helicobacter pylori, Human, Saccharomyces cerevisiae (core subset), Human-Bacillus Anthracis and Human-Yersinia pestis datasets, significantly outperforming the comparative models by average increases of 14.39%, 5.45%, 8.10%, 6.05% and 8.79% respectively. Additionally, SSC-PPI offers an efficient and reliable framework for large-scale prediction tasks such as drug-drug and drug-food interactions.
资助项目Basic Research Business of Central Universities of North Minzu University[2023ZRLG02] ; High School Scientific Research Project of Ningxia[NYG2024066] ; Beijing Natural Science Foundation[JQ240210] ; National Natural Science Foundation of China[62462001] ; Ningxia Natural Science Foundation[2024AAC03147] ; Ningxia Natural Science Foundation[2023AAC03264]
WOS研究方向Biochemistry & Molecular Biology ; Computer Science ; Mathematics
语种英语
WOS记录号WOS:001635805600012
出版者IEEE COMPUTER SOC
源URL[http://119.78.100.204/handle/2XEOYT63/42947]  
专题中国科学院计算技术研究所
通讯作者Ma, Ziping
作者单位1.North Minzu Univ, Sch Comp Sci & Engn, Yinchuan 750021, Peoples R China
2.Univ Chinese Acad Sci, Sch Comp Sci & Technol, Beijing 100190, Peoples R China
3.North Minzu Univ, Sch Math & Informat Sci, Yinchuan 750021, Peoples R China
4.Chinese Acad Sci, Inst Comp Technol, Beijing 100190, Peoples R China
5.Ningxia Univ, Sch Math & Stat, Yinchuan 750030, Peoples R China
推荐引用方式
GB/T 7714		 Ma, Ziping,Min, Weiqing,Zhang, Huanpu,et al. SSC-PPI: A Subspace Structure Consistency-Based Method for Protein-Protein Interactions Prediction[J]. IEEE TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS,2025,22(6):2477-2490.
APA Ma, Ziping,Min, Weiqing,Zhang, Huanpu,Huang, Yulei,&Jiang, Shuqiang.(2025).SSC-PPI: A Subspace Structure Consistency-Based Method for Protein-Protein Interactions Prediction.IEEE TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS,22(6),2477-2490.
MLA Ma, Ziping,et al."SSC-PPI: A Subspace Structure Consistency-Based Method for Protein-Protein Interactions Prediction".IEEE TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 22.6(2025):2477-2490.

入库方式： OAI收割

来源：计算技术研究所

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