Investigation and Prediction of Human Interactome Based on Quantitative Features
Protein is one of the most significant components of all living creatures. All significant and essential biological structures and functions relies on proteins and their respective biological functions. However, proteins cannot perform their unique biological significance independently. They have to...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2020-07-01
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| Series: | Frontiers in Bioengineering and Biotechnology |
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| Online Access: | https://www.frontiersin.org/article/10.3389/fbioe.2020.00730/full |
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| author | Xiaoyong Pan Xiaoyong Pan Tao Zeng Yu-Hang Zhang Lei Chen Kaiyan Feng Tao Huang Yu-Dong Cai |
| author_facet | Xiaoyong Pan Xiaoyong Pan Tao Zeng Yu-Hang Zhang Lei Chen Kaiyan Feng Tao Huang Yu-Dong Cai |
| author_sort | Xiaoyong Pan |
| collection | DOAJ |
| description | Protein is one of the most significant components of all living creatures. All significant and essential biological structures and functions relies on proteins and their respective biological functions. However, proteins cannot perform their unique biological significance independently. They have to interact with each other to realize the complicated biological processes in all living creatures including human beings. In other words, proteins depend on interactions (protein-protein interactions) to realize their significant effects. Thus, the significance comparison and quantitative contribution of candidate PPI features must be determined urgently. According to previous studies, 258 physical and chemical characteristics of proteins have been reported and confirmed to definitively affect the interaction efficiency of the related proteins. Among such features, essential physiochemical features of proteins like stoichiometric balance, protein abundance, molecular weight and charge distribution have been validated to be quite significant and irreplaceable for protein-protein interactions (PPIs). Therefore, in this study, we, on one hand, presented a novel computational framework to identify the key factors affecting PPIs with Boruta feature selection (BFS), Monte Carlo feature selection (MCFS), incremental feature selection (IFS), and on the other hand, built a quantitative decision-rule system to evaluate the potential PPIs under real conditions with random forest (RF) and RIPPER algorithms, thereby supplying several new insights into the detailed biological mechanisms of complicated PPIs. The main datasets and codes can be downloaded at https://github.com/xypan1232/Mass-PPI. |
| first_indexed | 2024-12-13T05:37:47Z |
| format | Article |
| id | doaj.art-329c5a60736f4fba945a0b53b89ff913 |
| institution | Directory Open Access Journal |
| issn | 2296-4185 |
| language | English |
| last_indexed | 2024-12-13T05:37:47Z |
| publishDate | 2020-07-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Bioengineering and Biotechnology |
| spelling | doaj.art-329c5a60736f4fba945a0b53b89ff9132022-12-21T23:57:53ZengFrontiers Media S.A.Frontiers in Bioengineering and Biotechnology2296-41852020-07-01810.3389/fbioe.2020.00730553527Investigation and Prediction of Human Interactome Based on Quantitative FeaturesXiaoyong Pan0Xiaoyong Pan1Tao Zeng2Yu-Hang Zhang3Lei Chen4Kaiyan Feng5Tao Huang6Yu-Dong Cai7School of Life Sciences, Shanghai University, Shanghai, ChinaKey Laboratory of System Control and Information Processing, Ministry of Education of China, Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai, ChinaKey Laboratory of Systems Biology, Institute of Biochemistry and Cell Biology, Chinese Academy of Sciences, Shanghai, ChinaShanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, ChinaCollege of Information Engineering, Shanghai Maritime University, Shanghai, ChinaDepartment of Computer Science, Guangdong AIB Polytechnic, Guangzhou, ChinaShanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, ChinaSchool of Life Sciences, Shanghai University, Shanghai, ChinaProtein is one of the most significant components of all living creatures. All significant and essential biological structures and functions relies on proteins and their respective biological functions. However, proteins cannot perform their unique biological significance independently. They have to interact with each other to realize the complicated biological processes in all living creatures including human beings. In other words, proteins depend on interactions (protein-protein interactions) to realize their significant effects. Thus, the significance comparison and quantitative contribution of candidate PPI features must be determined urgently. According to previous studies, 258 physical and chemical characteristics of proteins have been reported and confirmed to definitively affect the interaction efficiency of the related proteins. Among such features, essential physiochemical features of proteins like stoichiometric balance, protein abundance, molecular weight and charge distribution have been validated to be quite significant and irreplaceable for protein-protein interactions (PPIs). Therefore, in this study, we, on one hand, presented a novel computational framework to identify the key factors affecting PPIs with Boruta feature selection (BFS), Monte Carlo feature selection (MCFS), incremental feature selection (IFS), and on the other hand, built a quantitative decision-rule system to evaluate the potential PPIs under real conditions with random forest (RF) and RIPPER algorithms, thereby supplying several new insights into the detailed biological mechanisms of complicated PPIs. The main datasets and codes can be downloaded at https://github.com/xypan1232/Mass-PPI.https://www.frontiersin.org/article/10.3389/fbioe.2020.00730/fulldecision treehuman interactomepredictionprotein–protein interactionquantitative feature |
| spellingShingle | Xiaoyong Pan Xiaoyong Pan Tao Zeng Yu-Hang Zhang Lei Chen Kaiyan Feng Tao Huang Yu-Dong Cai Investigation and Prediction of Human Interactome Based on Quantitative Features Frontiers in Bioengineering and Biotechnology decision tree human interactome prediction protein–protein interaction quantitative feature |
| title | Investigation and Prediction of Human Interactome Based on Quantitative Features |
| title_full | Investigation and Prediction of Human Interactome Based on Quantitative Features |
| title_fullStr | Investigation and Prediction of Human Interactome Based on Quantitative Features |
| title_full_unstemmed | Investigation and Prediction of Human Interactome Based on Quantitative Features |
| title_short | Investigation and Prediction of Human Interactome Based on Quantitative Features |
| title_sort | investigation and prediction of human interactome based on quantitative features |
| topic | decision tree human interactome prediction protein–protein interaction quantitative feature |
| url | https://www.frontiersin.org/article/10.3389/fbioe.2020.00730/full |
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