Refine your search
Collections
Co-Authors
Journals
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z All
Kowsalya, G.
- Sentimental Analysis for Social Media–A Review
Abstract Views :175 |
PDF Views:0
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.References
- Pang, Bo, and Lillian Lee. "Opinion mining and sentiment analysis”. Foundations and Trends® in Information Retrieval, 2(1–2), 2008, 1-135.
- Das, Sanjiv, and Mike Chen. "Yahoo! for Amazon: Extracting market sentiment from stock message boards." Proc. of the Asia Pacific Finance Association Annual Conf. (APFA). 35, 2001,43.
- Tong, Richard M. "An operational system for detecting and tracking opinions in on-line discussion." In Working Notes of the ACM SIGIR 2001 Workshop on Operational Text Classification, 1(6), 2001.
- Kaplan, A.M. and Haenlein, M., “Users of the world, unite! The challenges and opportunities of Social Media”. Business Horizons, 53(1), 2010, 59-68.
- Kaschesky, M., Sobkowicz, P. and Bouchard, G.,. “Opinion mining in social media: modeling, simulating, and visualizing political opinion formation in the web”, Proc. 12st Annual Int. Digital Government Research Conf.: Digital Government Innovation in Challenging Times, 2011, 317-326.
- Chaovalit, P. and Zhou, L. “Movie review mining: A comparison between supervised and unsupervised classification approaches”, Proc. 38st Annual Hawaii International Conference on System Sciences (HICSS'05), 2005, 112c-112c.
- Kearns, Michael, Siddharth Suri, and Nick Montfort. "An experimental study of the coloring problem on human subject networks." Science, 313(5788), 2006, 824-827.
- Kleinberg, Jon. "Complex networks and decentralized search algorithms." Proc. Int. Congress of Mathematicians (ICM), 3, 2006, 1019-1044.
- Liben‐Nowell, David, and Jon Kleinberg. "The link‐prediction problem for social networks." Journal of the American society for information science and technology, 58(7),2007, 1019-1031.
- Koppel, M., and Schler, J. “The importance of neutral examples for learning sentiment”. Computational Intelligence, 22(2), 2006,100-109.
- Qu, Yan. "Exploring attitude and affect in text: Theories and applications." AAAI Spring Symposium, 2004.
- Pang, Bo, and Lillian Lee. "Using very simple statistics for review search: An exploration." Coling 2008: Companion volume: Posters ,2008, 75-78.
- Pang, B. and Lee, L. “Seeing stars: Exploiting class relationships for sentiment categorization with respect to rating scales”. Proc. 43rd Annual meeting on association for computational linguistics, 2005,115-124.
- Godbole, Namrata, Manja Srinivasaiah, and Steven Skiena. "Large-Scale Sentiment Analysis for News and Blogs.", Icwsm, 7(21), 2007, 219-222.
- Cortizo J, Carrero F, Gomez J, Monsalve B, Puertas E. “Introduction to Mining SM”. Proc. 1st Int. Workshop on Mining SM, 2009, 1-3.
- In silico Analysis of Flavanones capable of inhibiting covid19 RNA dependent RNA polymerase
Abstract Views :64 |
PDF Views:0
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.References
- Ahmad S. et al. Epidemiology, Risk, Myths, Pharmacotherapeutic Management and Socio- economic Burden due to Novel COVID-19: A Recent Update. Research Journal of Pharmacy and Technology. 2021; 14(4):2308-5. doi: 10.52711/0974-360X.2021.00408
- Dawood AA. SARS-CoV-2 is Originated from Bat Corona Virus. Research J. Science and Tech. 2021; 13(1):31-32. doi: 10.5958/2349-2988.2021.00005.
- Wang, Y et al. Unique epidemiological and clinical features of the emerging 2019 novel coronavirus pneumonia (COVID‐19) implicate special control measures. Journal of medical virology. 92; 2020: 568-576.
- Cascella M. et al. 2020. Features, evaluation and treatment coronavirus (COVID-19). In Statpearls [internet]. Stat Pearls Publishing
- Sanket S. Et al. Zika Virus: Infection, Virus, Development and Process of Vaccines. Research J. Pharm. and Tech 2018; 11(11): 5159-5162.
- Mankar SD. et al. Corona Viruses - Current Knowledge - A Review. Research J. Science and Tech. 2020; 12(2): 163-166. doi: 10.5958/2349-2988.2020.00021.2
- Rodríguez-Morales, AJ. Et al. Going global–Travel and the 2019 novel coronavirus. Travel medicine and infectious disease.2020;33:101578.
- Akshay R. et al. A Novel Approach for Treatment of COVID-19 with Convalescent Plasma. Res. J. Pharma. Dosage Forms and Tech. 2020; 12:227-230.
- Dipak Nalawade R. et al. Analytical Method Development and Validation of Ritonavir: A Review. Research J. Science and Tech. 2020;12: 157-162.
- Lu, H. Drug treatment options for the 2019-new coronavirus (2019-nCoV). Bioscience trends. 2020; 14:69-71
- Rokade M, and Khandagale P. Coronavirus Disease: A Review of a New Threat to Public Health. Asian J. Pharm. Res. 2020;10:241-244. doi: 10.5958/2231-5691.2020.00042.8
- Ali Adel Dawood. SARS-CoV-2 is Originated from Bat Corona Virus. Research J. Science and Tech. 2021; 13:31-32. doi: 10.5958/2349-2988.2021. 00005. X
- Rahate Snehal Kishor, Bombale Mayur Ramhari. Introduction to Covid-19. Research J. Science and Tech. 2020; 12(4):338-345. doi: 10.5958/2349-2988.2020.00051.0
- Ghogare Rajashree D., Navale Abhijit S., Shaikh Sahil B. Novel Corona Virus: One Biological Disaster of 2020. Research J. Science and Tech. 2020; 12(2): 147-156. doi: 10.5958/2349-2988.2020.00019.4
- Zhu W, Chen CZ, Gorshkov K, Xu M, Lo DC, Zheng W. RNA-Dependent RNA Polymerase as a Target for COVID-19 Drug Discovery. SLAS Discov. 2020;25(10):1141-1151. doi:10.1177/247255522094212
- Russo M, Moccia S, Spagnuolo C, Tedesco I, Russo GL. Roles of flavonoids against coronavirus infection. Chem Biol Interact. 2020;328(July):109211. doi:10.1016/j.cbi.2020.109211
- DeLano WL. Pymol: An open-source molecular graphics tool. CCP4. Newsletter on protein crystallography, 40; 2002: 82-92.
- Yang H, Sun L, Li W, Liu G, and Tang Y. In Silico Prediction of Chemical Toxicity for Drug Design Using Machine Learning Methods and Structural Alerts. Front Chem. 2018; 6: 129.
- Simoes L.R., Maciel G.M., Brandao G.C., Kroon E.G., Castilho R.O., Oliveira A.B. Antiviral activity of Disticella elongata (Vahl) Urb. (Bignoniaceae), a potentially useful source of anti-dengue drugs from the state of Minas Gerais, Brazil. Lett. Appl. Microbiol. 53; 2011:602–607.
- Manvar D., Mishra M., Kumar S., Pandey V.N. Identification and evaluation of anti hepatitis C virus phytochemicals from Eclipta alba. J. Ethnopharmacol. 144; 2012:545–554.
- Ji S., Li R., Wang Q., Miao W.J., Li Z.W., Si L.L., Qiao X., Yu S.W., Zhou D.M., Ye M. Anti-H1N1 virus, cytotoxic and Nrf2 activation activities of chemical constituents from Scutellaria baicalensis. J. Ethnopharmacol. 176; 2015:475–484.
- Huang H.C., Tao M.H., Hung T.M., Chen J.C., Lin Z.J., Huang C. (-)-Epigallocatechin-3-gallate inhibits entry of hepatitis B virus into hepatocytes. Antivir. Res. 111; 2014:100–111.
- Rehman S., Ashfaq U.A., Ijaz B., Riazuddin S. Anti-hepatitis C virus activity and synergistic effect of Nymphaea alba extracts and bioactive constituents in liver infected cells. Microb. Pathog.121; 2018:198–209
- Lee L.J., Loe M.W., Lee R.C., Chu J.J. Antiviral activity of pinocembrin against Zika virus replication. Antivir. Res. 167; 2019:13–24.
- Bachmetov L., Gal-Tanamy M., Shapira A., Vorobeychik M., Giterman-Galam T., Sathiyamoorthy P., Golan-Goldhirsh A., Benhar I., Tur-Kaspa R., Zemel R. Suppression of hepatitis C virus by the flavonoid quercetin is mediated by inhibition of NS3 protease activity. J. Viral Hepat. 19; 2012:81–88.
- Choi H.J., Song J.H., Park K.S., Kwon D.H. Inhibitory effects of quercetin 3-rhamnoside on influenza A virus replication. Eur. J. Pharm. Sci. 37; 2009:329–333.
- Li S., Hattori T., Kodama E.N. Epigallocatechin gallate inhibits the HIV reverse transcription step. Antivir. Chem. Chemother.4; 2011:239–243.
- Moghaddam E., Teoh B.T., Sam S.S., Lani R., Hassandarvish P., Chik Z., Yueh A., Abubakar S., Zandi K. Baicalin, a metabolite of baicalein with antiviral activity against dengue virus. Sci. Rep. 5; 2014:5452–5459.
- Archana B. Chavhan, Pavan S. Jadhav, Satish Shelke. COVID 19: Outbreak, Structure and Current therapeutic strategies. Asian J. Pharm. Tech. 2021; 11(1):76-83. doi: 10.5958/2231-5713.2021.00013.1
- Bhavanisha Rithiga S, Shanmugasundaram S. Virtual Screening of Pentahydroxyflavone – A Potent COVID-19 Major Protease Inhibitor. Asian J. Res. Pharm.Sci.2021;11(1):7-14. doi: 10.5958/2231-5659.2021.00002.3
- Mayur S. Jain, Shashikant D. Barhate. Favipiravir has been investigated for the treatment of life-threatening pathogens such as Ebola virus, Lassa virus, and now COVID-19: A Review. 10.5958/2231-5691.2021.00008.3 doi:
- Ritika Gupta. The Management of Coronavius Pandemic 2019-2020. Asian J. Pharm. Res. 2020; 10(4):327-330. doi: 10.5958/2231-5691.2020.00056.8
- B. V. Naresh. A Review of the 2019 Novel Coronavirus (COVID-19) Pandemic. Asian J. Pharm. Res. 2020; 10(3):233-238. doi: 10.5958/2231-5691.2020.00040.4
- Nagaraja Sree Harsha, Juan Rivas-Santisteban, Roopashree T Satish, G S Kumar. Analysis of the Evolutionary pattern of SARS-CoV-2 and its implications in the spread of the disease. Research Journal of Pharmacy and Technology. 2021; 14(4):2229-2. doi: 10.52711/0974-360X.2021.00396
- Saxena Pranjal, Goswami Raksha, Pandey Haymanshu, Kumawat Deepak, Chandy Steffy Mary. Covid-19 Test Detection by Real Time RT-PCR. Res. J. Pharmacology and Pharmacodynamics.2021; 13(1):22-26. doi: 10.5958/2321-5836.2021.00005.7
- Yin W. et al. Structural basis for inhibition of the RNA-dependent RNA polymerase from SARS-CoV-2 by remdesivir. Science. 2020 ;368(6498):1499-1504. doi: 10.1126/science.abc1560. PMID: 32358203; PMCID: PMC7199908.