Predicting the Influence of MicroRNAs on Drug Therapeutic Effects by Random Walking
The emergence of drug resistance is one of the main reasons for the failure of disease treatment. More and more studies have shown that miRNAs are associated with the resistance or sensitivity of certain therapeutic drugs by regulating target genes. However, only a few associations have been reporte...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2020-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9123338/ |
| _version_ | 1818618515557449728 |
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| author | Peng Xu Qian Wu Yongsheng Rao Zheng Kou Gang Fang Wenbin Liu Henry Han |
| author_facet | Peng Xu Qian Wu Yongsheng Rao Zheng Kou Gang Fang Wenbin Liu Henry Han |
| author_sort | Peng Xu |
| collection | DOAJ |
| description | The emergence of drug resistance is one of the main reasons for the failure of disease treatment. More and more studies have shown that miRNAs are associated with the resistance or sensitivity of certain therapeutic drugs by regulating target genes. However, only a few associations have been reported between miRNAs and drug resistance or sensitivity. In this study, we first constructed a heterogeneous network by integrating the miRNA similarity network, drug similarity network and miRNA-drug effect associations network. Subsequently, we predicted the potential miRNA-drug effect associations by the Bi-Random walk (BiRW) algorithm. The cross-validation and De novo validation methods were applied to verify the prediction performance. Results show that the proposed method can effectively predict potential miRNA-drug effect associations. This study will enhance our understanding of the important roles of miRNAs in drug therapeutic effects and provide a valuable resource for designing effective therapeutic strategies. |
| first_indexed | 2024-12-16T17:22:49Z |
| format | Article |
| id | doaj.art-8661ee9ca7e3454db533f20f3aebef05 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-16T17:22:49Z |
| publishDate | 2020-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-8661ee9ca7e3454db533f20f3aebef052022-12-21T22:23:08ZengIEEEIEEE Access2169-35362020-01-01811734711735310.1109/ACCESS.2020.30045129123338Predicting the Influence of MicroRNAs on Drug Therapeutic Effects by Random WalkingPeng Xu0https://orcid.org/0000-0001-7028-9987Qian Wu1https://orcid.org/0000-0002-7835-535XYongsheng Rao2https://orcid.org/0000-0001-9615-3658Zheng Kou3https://orcid.org/0000-0003-4758-2872Gang Fang4https://orcid.org/0000-0001-9847-114XWenbin Liu5https://orcid.org/0000-0001-9091-3177Henry Han6https://orcid.org/0000-0003-0273-6719Institute of Computational Science and Technology, Guangzhou University, Guangzhou, ChinaCollege of Computer Science and Artificial Intelligence, Wenzhou University, Wenzhou, ChinaInstitute of Computational Science and Technology, Guangzhou University, Guangzhou, ChinaInstitute of Computational Science and Technology, Guangzhou University, Guangzhou, ChinaInstitute of Computational Science and Technology, Guangzhou University, Guangzhou, ChinaInstitute of Computational Science and Technology, Guangzhou University, Guangzhou, ChinaDepartment of Computer and Information Science, Fordham University, New York, NY, USAThe emergence of drug resistance is one of the main reasons for the failure of disease treatment. More and more studies have shown that miRNAs are associated with the resistance or sensitivity of certain therapeutic drugs by regulating target genes. However, only a few associations have been reported between miRNAs and drug resistance or sensitivity. In this study, we first constructed a heterogeneous network by integrating the miRNA similarity network, drug similarity network and miRNA-drug effect associations network. Subsequently, we predicted the potential miRNA-drug effect associations by the Bi-Random walk (BiRW) algorithm. The cross-validation and De novo validation methods were applied to verify the prediction performance. Results show that the proposed method can effectively predict potential miRNA-drug effect associations. This study will enhance our understanding of the important roles of miRNAs in drug therapeutic effects and provide a valuable resource for designing effective therapeutic strategies.https://ieeexplore.ieee.org/document/9123338/Drug therapeutic effectmiRNAsrandom walk |
| spellingShingle | Peng Xu Qian Wu Yongsheng Rao Zheng Kou Gang Fang Wenbin Liu Henry Han Predicting the Influence of MicroRNAs on Drug Therapeutic Effects by Random Walking IEEE Access Drug therapeutic effect miRNAs random walk |
| title | Predicting the Influence of MicroRNAs on Drug Therapeutic Effects by Random Walking |
| title_full | Predicting the Influence of MicroRNAs on Drug Therapeutic Effects by Random Walking |
| title_fullStr | Predicting the Influence of MicroRNAs on Drug Therapeutic Effects by Random Walking |
| title_full_unstemmed | Predicting the Influence of MicroRNAs on Drug Therapeutic Effects by Random Walking |
| title_short | Predicting the Influence of MicroRNAs on Drug Therapeutic Effects by Random Walking |
| title_sort | predicting the influence of micrornas on drug therapeutic effects by random walking |
| topic | Drug therapeutic effect miRNAs random walk |
| url | https://ieeexplore.ieee.org/document/9123338/ |
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