Molecule generation toward target protein (SARS-CoV-2) using reinforcement learning-based graph neural network via knowledge graph Article Swipe
Amit Ranjan
,
Hritik Kumar
,
Deepshikha Kumari
,
Archit Anand
,
Rajiv Misra
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1007/s13721-023-00409-2
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1007/s13721-023-00409-2
Related Topics
Concepts
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1007/s13721-023-00409-2
- https://link.springer.com/content/pdf/10.1007/s13721-023-00409-2.pdf
- OA Status
- bronze
- Cited By
- 8
- References
- 30
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4313595375
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4313595375Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1007/s13721-023-00409-2Digital Object Identifier
- Title
-
Molecule generation toward target protein (SARS-CoV-2) using reinforcement learning-based graph neural network via knowledge graphWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-01-06Full publication date if available
- Authors
-
Amit Ranjan, Hritik Kumar, Deepshikha Kumari, Archit Anand, Rajiv MisraList of authors in order
- Landing page
-
https://doi.org/10.1007/s13721-023-00409-2Publisher landing page
- PDF URL
-
https://link.springer.com/content/pdf/10.1007/s13721-023-00409-2.pdfDirect link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
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bronzeOpen access status per OpenAlex
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https://link.springer.com/content/pdf/10.1007/s13721-023-00409-2.pdfDirect OA link when available
- Concepts
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Chemical space, Graph, Computer science, Reinforcement learning, Artificial intelligence, Drug discovery, Artificial neural network, Generative model, Computational biology, Machine learning, Generative grammar, Chemistry, Theoretical computer science, Biology, BiochemistryTop concepts (fields/topics) attached by OpenAlex
- Cited by
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8Total citation count in OpenAlex
- Citations by year (recent)
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2024: 5, 2023: 3Per-year citation counts (last 5 years)
- References (count)
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30Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| best_oa_location.raw_type | journal-article |
| best_oa_location.license_id | |
| best_oa_location.is_accepted | True |
| best_oa_location.is_published | True |
| best_oa_location.raw_source_name | Network Modeling Analysis in Health Informatics and Bioinformatics |
| best_oa_location.landing_page_url | https://doi.org/10.1007/s13721-023-00409-2 |
| primary_location.id | doi:10.1007/s13721-023-00409-2 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S4210178532 |
| primary_location.source.issn | 2192-6662, 2192-6670 |
| primary_location.source.type | journal |
| primary_location.source.is_oa | False |
| primary_location.source.issn_l | 2192-6662 |
| primary_location.source.is_core | True |
| primary_location.source.is_in_doaj | False |
| primary_location.source.display_name | Network Modeling Analysis in Health Informatics and Bioinformatics |
| primary_location.source.host_organization | https://openalex.org/P4310321666 |
| primary_location.source.host_organization_name | Springer Vienna |
| primary_location.source.host_organization_lineage | https://openalex.org/P4310321666, https://openalex.org/P4310319965 |
| primary_location.source.host_organization_lineage_names | Springer Vienna, Springer Nature |
| primary_location.license | |
| primary_location.pdf_url | https://link.springer.com/content/pdf/10.1007/s13721-023-00409-2.pdf |
| primary_location.version | publishedVersion |
| primary_location.raw_type | journal-article |
| primary_location.license_id | |
| primary_location.is_accepted | True |
| primary_location.is_published | True |
| primary_location.raw_source_name | Network Modeling Analysis in Health Informatics and Bioinformatics |
| primary_location.landing_page_url | https://doi.org/10.1007/s13721-023-00409-2 |
| publication_date | 2023-01-06 |
| publication_year | 2023 |
| referenced_works | https://openalex.org/W2925830236, https://openalex.org/W4247555443, https://openalex.org/W2085663480, https://openalex.org/W2086286404, https://openalex.org/W1995089537, https://openalex.org/W3008047170, https://openalex.org/W3032123378, https://openalex.org/W2963028280, https://openalex.org/W3003322996, https://openalex.org/W2801253218, https://openalex.org/W2145339207, https://openalex.org/W3096561213, https://openalex.org/W3175786839, https://openalex.org/W2610148085, https://openalex.org/W2785947426, https://openalex.org/W3116865743, https://openalex.org/W2805002767, https://openalex.org/W3215007095, https://openalex.org/W2951433247, https://openalex.org/W1981276685, https://openalex.org/W2116341502, https://openalex.org/W2978484973, https://openalex.org/W2860192827, https://openalex.org/W2153838454, https://openalex.org/W3011072970, https://openalex.org/W2971227267, https://openalex.org/W639708223, https://openalex.org/W3104956673, https://openalex.org/W4200534198, https://openalex.org/W3007386177 |
| referenced_works_count | 30 |
| abstract_inverted_index | |
| cited_by_percentile_year.max | 98 |
| cited_by_percentile_year.min | 96 |
| corresponding_author_ids | https://openalex.org/A5075138847 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 5 |
| corresponding_institution_ids | https://openalex.org/I132153292 |
| citation_normalized_percentile.value | 0.87151294 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |