Integrative analysis of chemical properties and functions of drugs for adverse drug reaction prediction based on multi-label deep neural network
The prediction of adverse drug reactions (ADR) is an important step of drug discovery and design process. Different drug properties have been employed for ADR prediction but the prediction capability of drug properties and drug functions in integrated manner is yet to be explored. In the present wor...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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De Gruyter
2022-05-01
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| Series: | Journal of Integrative Bioinformatics |
| Subjects: | |
| Online Access: | https://doi.org/10.1515/jib-2022-0007 |
| _version_ | 1828304284187361280 |
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| author | Das Pranab Yogita Pal Vipin |
| author_facet | Das Pranab Yogita Pal Vipin |
| author_sort | Das Pranab |
| collection | DOAJ |
| description | The prediction of adverse drug reactions (ADR) is an important step of drug discovery and design process. Different drug properties have been employed for ADR prediction but the prediction capability of drug properties and drug functions in integrated manner is yet to be explored. In the present work, a multi-label deep neural network and MLSMOTE based methodology has been proposed for ADR prediction. The proposed methodology has been applied on SMILES Strings data of drugs, 17 molecular descriptors data of drugs and drug functions data individually and in integrated manner for ADR prediction. The experimental results shows that the SMILES Strings + drug functions has outperformed other types of data with regards to ADR prediction capability. |
| first_indexed | 2024-04-13T14:09:04Z |
| format | Article |
| id | doaj.art-a05ac54a3dba47208c98b4f5183455c7 |
| institution | Directory Open Access Journal |
| issn | 1613-4516 |
| language | English |
| last_indexed | 2024-04-13T14:09:04Z |
| publishDate | 2022-05-01 |
| publisher | De Gruyter |
| record_format | Article |
| series | Journal of Integrative Bioinformatics |
| spelling | doaj.art-a05ac54a3dba47208c98b4f5183455c72022-12-22T02:43:50ZengDe GruyterJournal of Integrative Bioinformatics1613-45162022-05-011931255910.1515/jib-2022-0007Integrative analysis of chemical properties and functions of drugs for adverse drug reaction prediction based on multi-label deep neural networkDas Pranab0Yogita1Pal Vipin2National Institute of Technology Meghalaya, Shillong, IndiaNational Institute of Technology Meghalaya, Shillong, IndiaNational Institute of Technology Meghalaya, Shillong, IndiaThe prediction of adverse drug reactions (ADR) is an important step of drug discovery and design process. Different drug properties have been employed for ADR prediction but the prediction capability of drug properties and drug functions in integrated manner is yet to be explored. In the present work, a multi-label deep neural network and MLSMOTE based methodology has been proposed for ADR prediction. The proposed methodology has been applied on SMILES Strings data of drugs, 17 molecular descriptors data of drugs and drug functions data individually and in integrated manner for ADR prediction. The experimental results shows that the SMILES Strings + drug functions has outperformed other types of data with regards to ADR prediction capability.https://doi.org/10.1515/jib-2022-0007adverse drug reactionschemical properties of drugsdeep neural networkdrug functions |
| spellingShingle | Das Pranab Yogita Pal Vipin Integrative analysis of chemical properties and functions of drugs for adverse drug reaction prediction based on multi-label deep neural network Journal of Integrative Bioinformatics adverse drug reactions chemical properties of drugs deep neural network drug functions |
| title | Integrative analysis of chemical properties and functions of drugs for adverse drug reaction prediction based on multi-label deep neural network |
| title_full | Integrative analysis of chemical properties and functions of drugs for adverse drug reaction prediction based on multi-label deep neural network |
| title_fullStr | Integrative analysis of chemical properties and functions of drugs for adverse drug reaction prediction based on multi-label deep neural network |
| title_full_unstemmed | Integrative analysis of chemical properties and functions of drugs for adverse drug reaction prediction based on multi-label deep neural network |
| title_short | Integrative analysis of chemical properties and functions of drugs for adverse drug reaction prediction based on multi-label deep neural network |
| title_sort | integrative analysis of chemical properties and functions of drugs for adverse drug reaction prediction based on multi label deep neural network |
| topic | adverse drug reactions chemical properties of drugs deep neural network drug functions |
| url | https://doi.org/10.1515/jib-2022-0007 |
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