COVID-19Base v3: Update of the knowledgebase for drugs and biomedical entities linked to COVID-19
<div><p>COVID-19 has taken a huge toll on our lives over the last 3 years. Global initiatives put forward by all stakeholders are still in place to combat this pandemic and help us learn lessons for future ones. While the vaccine rollout was not able to curb the spread of the disease for...
محفوظ في:
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| مؤلفون آخرون: | , , , , , |
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2023
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إضافة وسم
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| _version_ | 1864513526452715520 |
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| author | Syed Abdullah Basit (18021787) |
| author2 | Rizwan Qureshi (15279193) Saleh Musleh (15279190) Reto Guler (368266) M. Sohel Rahman (12056885) Kabir H. Biswas (5705864) Tanvir Alam (638619) |
| author2_role | author author author author author author |
| author_facet | Syed Abdullah Basit (18021787) Rizwan Qureshi (15279193) Saleh Musleh (15279190) Reto Guler (368266) M. Sohel Rahman (12056885) Kabir H. Biswas (5705864) Tanvir Alam (638619) |
| author_role | author |
| dc.creator.none.fl_str_mv | Syed Abdullah Basit (18021787) Rizwan Qureshi (15279193) Saleh Musleh (15279190) Reto Guler (368266) M. Sohel Rahman (12056885) Kabir H. Biswas (5705864) Tanvir Alam (638619) |
| dc.date.none.fl_str_mv | 2023-03-06T03:00:00Z |
| dc.identifier.none.fl_str_mv | 10.3389/fpubh.2023.1125917 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/journal_contribution/COVID-19Base_v3_Update_of_the_knowledgebase_for_drugs_and_biomedical_entities_linked_to_COVID-19/25285078 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Health sciences Public health ORDS SARS-CoV-2 CORD-19 deep learning machine learning COVID - 19 |
| dc.title.none.fl_str_mv | COVID-19Base v3: Update of the knowledgebase for drugs and biomedical entities linked to COVID-19 |
| dc.type.none.fl_str_mv | Text Journal contribution info:eu-repo/semantics/publishedVersion text contribution to journal |
| description | <div><p>COVID-19 has taken a huge toll on our lives over the last 3 years. Global initiatives put forward by all stakeholders are still in place to combat this pandemic and help us learn lessons for future ones. While the vaccine rollout was not able to curb the spread of the disease for all strains, the research community is still trying to develop effective therapeutics for COVID-19. Although Paxlovid and remdesivir have been approved by the FDA against COVID-19, they are not free of side effects. Therefore, the search for a therapeutic solution with high efficacy continues in the research community. To support this effort, in this latest version (v3) of COVID-19Base, we have summarized the biomedical entities linked to COVID-19 that have been highlighted in the scientific literature after the vaccine rollout. Eight different topic-specific dictionaries, i.e., gene, miRNA, lncRNA, PDB entries, disease, alternative medicines registered under clinical trials, drugs, and the side effects of drugs, were used to build this knowledgebase. We have introduced a BLSTM-based deep-learning model to predict the drug-disease associations that outperforms the existing model for the same purpose proposed in the earlier version of COVID-19Base. For the very first time, we have incorporated disease-gene, disease-miRNA, disease-lncRNA, and drug-PDB associations covering the largest number of biomedical entities related to COVID-19. We have provided examples of and insights into different biomedical entities covered in COVID-19Base to support the research community by incorporating all of these entities under a single platform to provide evidence-based support from the literature. COVID-19Base v3 can be accessed from: https://covidbase-v3.vercel.app/. The GitHub repository for the source code and data dictionaries is available to the community from: https://github.com/91Abdullah/covidbasev3.0.</p><p> </p></div><h2>Other Information</h2> <p> Published in: Frontiers in Public Health<br> License: <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.3389/fpubh.2023.1125917" target="_blank">https://dx.doi.org/10.3389/fpubh.2023.1125917</a></p> |
| eu_rights_str_mv | openAccess |
| id | Manara2_235a1532d6e4dfc75f34b76d272dfa8c |
| identifier_str_mv | 10.3389/fpubh.2023.1125917 |
| network_acronym_str | Manara2 |
| network_name_str | Manara2 |
| oai_identifier_str | oai:figshare.com:article/25285078 |
| publishDate | 2023 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | COVID-19Base v3: Update of the knowledgebase for drugs and biomedical entities linked to COVID-19Syed Abdullah Basit (18021787)Rizwan Qureshi (15279193)Saleh Musleh (15279190)Reto Guler (368266)M. Sohel Rahman (12056885)Kabir H. Biswas (5705864)Tanvir Alam (638619)Health sciencesPublic healthORDS SARS-CoV-2CORD-19deep learningmachine learningCOVID - 19<div><p>COVID-19 has taken a huge toll on our lives over the last 3 years. Global initiatives put forward by all stakeholders are still in place to combat this pandemic and help us learn lessons for future ones. While the vaccine rollout was not able to curb the spread of the disease for all strains, the research community is still trying to develop effective therapeutics for COVID-19. Although Paxlovid and remdesivir have been approved by the FDA against COVID-19, they are not free of side effects. Therefore, the search for a therapeutic solution with high efficacy continues in the research community. To support this effort, in this latest version (v3) of COVID-19Base, we have summarized the biomedical entities linked to COVID-19 that have been highlighted in the scientific literature after the vaccine rollout. Eight different topic-specific dictionaries, i.e., gene, miRNA, lncRNA, PDB entries, disease, alternative medicines registered under clinical trials, drugs, and the side effects of drugs, were used to build this knowledgebase. We have introduced a BLSTM-based deep-learning model to predict the drug-disease associations that outperforms the existing model for the same purpose proposed in the earlier version of COVID-19Base. For the very first time, we have incorporated disease-gene, disease-miRNA, disease-lncRNA, and drug-PDB associations covering the largest number of biomedical entities related to COVID-19. We have provided examples of and insights into different biomedical entities covered in COVID-19Base to support the research community by incorporating all of these entities under a single platform to provide evidence-based support from the literature. COVID-19Base v3 can be accessed from: https://covidbase-v3.vercel.app/. The GitHub repository for the source code and data dictionaries is available to the community from: https://github.com/91Abdullah/covidbasev3.0.</p><p> </p></div><h2>Other Information</h2> <p> Published in: Frontiers in Public Health<br> License: <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.3389/fpubh.2023.1125917" target="_blank">https://dx.doi.org/10.3389/fpubh.2023.1125917</a></p>2023-03-06T03:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.3389/fpubh.2023.1125917https://figshare.com/articles/journal_contribution/COVID-19Base_v3_Update_of_the_knowledgebase_for_drugs_and_biomedical_entities_linked_to_COVID-19/25285078CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/252850782023-03-06T03:00:00Z |
| spellingShingle | COVID-19Base v3: Update of the knowledgebase for drugs and biomedical entities linked to COVID-19 Syed Abdullah Basit (18021787) Health sciences Public health ORDS SARS-CoV-2 CORD-19 deep learning machine learning COVID - 19 |
| status_str | publishedVersion |
| title | COVID-19Base v3: Update of the knowledgebase for drugs and biomedical entities linked to COVID-19 |
| title_full | COVID-19Base v3: Update of the knowledgebase for drugs and biomedical entities linked to COVID-19 |
| title_fullStr | COVID-19Base v3: Update of the knowledgebase for drugs and biomedical entities linked to COVID-19 |
| title_full_unstemmed | COVID-19Base v3: Update of the knowledgebase for drugs and biomedical entities linked to COVID-19 |
| title_short | COVID-19Base v3: Update of the knowledgebase for drugs and biomedical entities linked to COVID-19 |
| title_sort | COVID-19Base v3: Update of the knowledgebase for drugs and biomedical entities linked to COVID-19 |
| topic | Health sciences Public health ORDS SARS-CoV-2 CORD-19 deep learning machine learning COVID - 19 |