Oral_voting_transfer: classification of oral microorganisms’ function proteins with voting transfer model
IntroductionThe oral microbial group typically represents the human body’s highly complex microbial group ecosystem. Oral microorganisms take part in human diseases, including Oral cavity inflammation, mucosal disease, periodontal disease, tooth decay, and oral cancer. On the other hand, oral microb...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2024-02-01
|
| Series: | Frontiers in Microbiology |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fmicb.2023.1277121/full |
| _version_ | 1797322359262150656 |
|---|---|
| author | Wenzheng Bao Yujun Liu Baitong Chen Baitong Chen |
| author_facet | Wenzheng Bao Yujun Liu Baitong Chen Baitong Chen |
| author_sort | Wenzheng Bao |
| collection | DOAJ |
| description | IntroductionThe oral microbial group typically represents the human body’s highly complex microbial group ecosystem. Oral microorganisms take part in human diseases, including Oral cavity inflammation, mucosal disease, periodontal disease, tooth decay, and oral cancer. On the other hand, oral microbes can also cause endocrine disorders, digestive function, and nerve function disorders, such as diabetes, digestive system diseases, and Alzheimer’s disease. It was noted that the proteins of oral microbes play significant roles in these serious diseases. Having a good knowledge of oral microbes can be helpful in analyzing the procession of related diseases. Moreover, the high-dimensional features and imbalanced data lead to the complexity of oral microbial issues, which can hardly be solved with traditional experimental methods.MethodsTo deal with these challenges, we proposed a novel method, which is oral_voting_transfer, to deal with such classification issues in the field of oral microorganisms. Such a method employed three features to classify the five oral microorganisms, including Streptococcus mutans, Staphylococcus aureus, abiotrophy adjacent, bifidobacterial, and Capnocytophaga. Firstly, we utilized the highly effective model, which successfully classifies the organelle’s proteins and transfers to deal with the oral microorganisms. And then, some classification methods can be treated as the local classifiers in this work. Finally, the results are voting from the transfer classifiers and the voting ones.Results and discussionThe proposed method achieved the well performances in the five oral microorganisms. The oral_voting_transfer is a standalone tool, and all its source codes are publicly available at https://github.com/baowz12345/voting_transfer. |
| first_indexed | 2024-03-08T05:12:10Z |
| format | Article |
| id | doaj.art-727601a3662f452588d2305dbec533d5 |
| institution | Directory Open Access Journal |
| issn | 1664-302X |
| language | English |
| last_indexed | 2024-03-08T05:12:10Z |
| publishDate | 2024-02-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Microbiology |
| spelling | doaj.art-727601a3662f452588d2305dbec533d52024-02-07T05:34:53ZengFrontiers Media S.A.Frontiers in Microbiology1664-302X2024-02-011410.3389/fmicb.2023.12771211277121Oral_voting_transfer: classification of oral microorganisms’ function proteins with voting transfer modelWenzheng Bao0Yujun Liu1Baitong Chen2Baitong Chen3School of Information Engineering, Xuzhou University of Technology, Xuzhou, ChinaSchool of Information Engineering, Xuzhou University of Technology, Xuzhou, ChinaThe Affiliated Xuzhou Municipal Hospital of Xuzhou Medical University, Xuzhou, ChinaDepartment of Stomatology, Xuzhou First People’s Hospital, Xuzhou, ChinaIntroductionThe oral microbial group typically represents the human body’s highly complex microbial group ecosystem. Oral microorganisms take part in human diseases, including Oral cavity inflammation, mucosal disease, periodontal disease, tooth decay, and oral cancer. On the other hand, oral microbes can also cause endocrine disorders, digestive function, and nerve function disorders, such as diabetes, digestive system diseases, and Alzheimer’s disease. It was noted that the proteins of oral microbes play significant roles in these serious diseases. Having a good knowledge of oral microbes can be helpful in analyzing the procession of related diseases. Moreover, the high-dimensional features and imbalanced data lead to the complexity of oral microbial issues, which can hardly be solved with traditional experimental methods.MethodsTo deal with these challenges, we proposed a novel method, which is oral_voting_transfer, to deal with such classification issues in the field of oral microorganisms. Such a method employed three features to classify the five oral microorganisms, including Streptococcus mutans, Staphylococcus aureus, abiotrophy adjacent, bifidobacterial, and Capnocytophaga. Firstly, we utilized the highly effective model, which successfully classifies the organelle’s proteins and transfers to deal with the oral microorganisms. And then, some classification methods can be treated as the local classifiers in this work. Finally, the results are voting from the transfer classifiers and the voting ones.Results and discussionThe proposed method achieved the well performances in the five oral microorganisms. The oral_voting_transfer is a standalone tool, and all its source codes are publicly available at https://github.com/baowz12345/voting_transfer.https://www.frontiersin.org/articles/10.3389/fmicb.2023.1277121/fulloral microorganisms proteinsvoting transfer modelbioinformaticsmachine learningclassification |
| spellingShingle | Wenzheng Bao Yujun Liu Baitong Chen Baitong Chen Oral_voting_transfer: classification of oral microorganisms’ function proteins with voting transfer model Frontiers in Microbiology oral microorganisms proteins voting transfer model bioinformatics machine learning classification |
| title | Oral_voting_transfer: classification of oral microorganisms’ function proteins with voting transfer model |
| title_full | Oral_voting_transfer: classification of oral microorganisms’ function proteins with voting transfer model |
| title_fullStr | Oral_voting_transfer: classification of oral microorganisms’ function proteins with voting transfer model |
| title_full_unstemmed | Oral_voting_transfer: classification of oral microorganisms’ function proteins with voting transfer model |
| title_short | Oral_voting_transfer: classification of oral microorganisms’ function proteins with voting transfer model |
| title_sort | oral voting transfer classification of oral microorganisms function proteins with voting transfer model |
| topic | oral microorganisms proteins voting transfer model bioinformatics machine learning classification |
| url | https://www.frontiersin.org/articles/10.3389/fmicb.2023.1277121/full |
| work_keys_str_mv | AT wenzhengbao oralvotingtransferclassificationoforalmicroorganismsfunctionproteinswithvotingtransfermodel AT yujunliu oralvotingtransferclassificationoforalmicroorganismsfunctionproteinswithvotingtransfermodel AT baitongchen oralvotingtransferclassificationoforalmicroorganismsfunctionproteinswithvotingtransfermodel AT baitongchen oralvotingtransferclassificationoforalmicroorganismsfunctionproteinswithvotingtransfermodel |