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Kowsalya, G.
- Sentimental Analysis for Social Media–A Review
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Authors
Affiliations
1 Department of Computer Engineering, NPA Polytechnic College, Kotagiri- 643217, IN
2 Department of Computer Science, Government Arts College, Udumalpet-642126, IN
1 Department of Computer Engineering, NPA Polytechnic College, Kotagiri- 643217, IN
2 Department of Computer Science, Government Arts College, Udumalpet-642126, IN
Source
International Journal of Advanced Networking and Applications, Vol 10, No 3 (2018), Pagination: 3860-3863Abstract
In recent times, Social media has emerged as a personal communication media, as well as, a media to convey reviews about items and benefits or even political and general occasions among its clients. By using web and the web 2.0 the information in Twitter, Facebook and Instagram are easily retrieved. Because of its use across the board and prevalence, there is a monstrous measure of client surveys or feelings delivered and shared day by day. Mining client sentiments from Social Media is definitely not a straight forward assignment; it can be proficient in various ways. Gathering client sentiments can be costly and tedious assignment utilizing traditional strategies. This paper examines the challenges in doing sentimental analysis for Social Media.Keywords
Data Mining, Internet, Social Media, Sentimental Analysis, Opinion Mining.Full Text
References
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- In silico Analysis of Flavanones capable of inhibiting covid19 RNA dependent RNA polymerase
Abstract Views :64 |
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Authors
Affiliations
1 Department of Chemistry, PSGR Krishnammal College for Women, Coimbatore, Tamil Nadu,, IN
2 Department of Chemistry, PSGR Krishnammal College for Women, Coimbatore, Tamil Nadu, IN
1 Department of Chemistry, PSGR Krishnammal College for Women, Coimbatore, Tamil Nadu,, IN
2 Department of Chemistry, PSGR Krishnammal College for Women, Coimbatore, Tamil Nadu, IN
Source
Asian Journal of Research in Pharmaceutical Sciences, Vol 12, No 02 (2022), Pagination: 97-101Abstract
Virtual screening of flavanone against RdRp of SARS-CoV-2 was carried out using AutoDock Vina and ligPlot. Out of 16 compounds screened, Eriodictyol, Naringin, Hesperidin Methylchalcone were found to have good affinity values for binding. While Eriodictyol binds to amino acids, R836, K849, R858, Naringin binds to S814, R836, R858 and Hesperidin Methylchalcone binds to amino acids D760, S814, R836 amino acids are present in RdRp of covid19. Since these amino acids bind to the primer RNA, binding of flavanones to these amino acids could destabilize the replication complex and may inhibit viral RNA replication. All the compounds pass ADMET test indicating their drug potential.Keywords
SARS-CoV-2, RNA Dependent RNA polymerase (RdRp), Flavanone, drug like properties.
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