Your browser doesn't support javascript.
Show: 20 | 50 | 100
Results 1 - 7 de 7
Filter
1.
2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022 ; : 2259-2265, 2022.
Article in English | Scopus | ID: covidwho-2233703

ABSTRACT

This paper proposes a novel and efficient method, called S-PDB, for the analysis and classification of Spike (S) protein structures of SARS-CoV-2 and other viruses/organisms in the Protein Data Bank (PDB). The method first finds and identifies protein structures in PDB that are similar to a protein structure of interest (SARS-CoV-2 S) via a protein structure comparison tool. The amino acid (AA) sequences of identified protein structures, downloaded from PDB, and their aligned amino acids (AAA) and secondary structure elements (ASSE), that are stored in three separate datasets, are then used for the reliable detection/classification of SARS-CoV-2 S protein structures. Three classifiers are used and their performance is compared by using six evaluation metrics. Obtained results show that two classifiers for text data (Multinomial Naive Bayes and Stochastic Gradient Descent) performed better and achieved high accuracy on the dataset that contains AAA of protein structures compared to the datasets for AA and ASSE, respectively. © 2022 IEEE.

2.
2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022 ; : 2259-2265, 2022.
Article in English | Scopus | ID: covidwho-2223084

ABSTRACT

This paper proposes a novel and efficient method, called S-PDB, for the analysis and classification of Spike (S) protein structures of SARS-CoV-2 and other viruses/organisms in the Protein Data Bank (PDB). The method first finds and identifies protein structures in PDB that are similar to a protein structure of interest (SARS-CoV-2 S) via a protein structure comparison tool. The amino acid (AA) sequences of identified protein structures, downloaded from PDB, and their aligned amino acids (AAA) and secondary structure elements (ASSE), that are stored in three separate datasets, are then used for the reliable detection/classification of SARS-CoV-2 S protein structures. Three classifiers are used and their performance is compared by using six evaluation metrics. Obtained results show that two classifiers for text data (Multinomial Naive Bayes and Stochastic Gradient Descent) performed better and achieved high accuracy on the dataset that contains AAA of protein structures compared to the datasets for AA and ASSE, respectively. © 2022 IEEE.

3.
International Journal of Enterprise Network Management ; 13(2):155-179, 2022.
Article in English | Scopus | ID: covidwho-2022012

ABSTRACT

The implementation of nationwide lockdown during this pandemic situation has resulted into huge impact on the living style of everyone and affected various industries and companies during this lockdown resulting into a boom for those who were already present in the market with their stronghold in the online market. Some of these were the digital payment method, streaming service providers, online study platform, etc. Some of these services even reported a boom in their profit and market shares. The goal of this study was to identify the major streaming service providers in India and assess whether they made a profit during the lockdown and increase in the number of subscriber, increase in the streaming time and increase in the customer satisfaction. The result of the study shows that there was increase in the number of subscribers not only in subscriber but also increase in the streaming time too. Copyright © 2022 Inderscience Enterprises Ltd.

4.
Journal of Information and Knowledge Management ; 2022.
Article in English | Scopus | ID: covidwho-1861662

ABSTRACT

Context: From the past few years, Application Programming Interface (API) is widely used for mobile- and web-based application developments. Software developers can integrate third-party services into their projects to achieve their development goals efficiently using APIs;however, with the rapid increase in the number of APIs, the manual selection of Mashup-oriented API is becoming more difficult for the developer. Objective: In the COVID-19 pandemic, everyone wants an update about the latest Standard Operating Procedures (SOPs) and the latest information on COVID-19. Additionally, a software developer wants to develop an application that provides the SOPs and latest information of COVID-19;a developer can add these functionalities into an application using COVID-19-based APIs. Moreover, the current work aims at proposing a COVID-19-based API recommendation system for the developers. Method: In this study, we propose a COVID-19-based API recommendation system for developers. The recommendation system takes a developer query as input and recommends top-3 APIs and supported features, which help the developer during software development. Furthermore, the proposed COVID-19-based API recommendation system ensures the maximum participation of the developers by validating the recommended APIs and recommendation system from the expert developers using research questionnaires. Results: Additionally, the proposed COVID-19-based API recommendation system's output is validated by expert developers and evaluated on 120 expert developers' queries. In addition, experiment results show that single value decomposition achieves better prediction. Conclusion: We conclude that it is significantly important to recommend APIs along with supported features to the developer for project development, and future work is needed to take more developer's queries also to build Integrated Development Environment for the developers. © 2022 World Scientific Publishing Co.

5.
Gastroenterology ; 160(6):S-191-S-192, 2021.
Article in English | EMBASE | ID: covidwho-1591097

ABSTRACT

Background: SARS-Cov-2 infection (COVID-19) and associated gastrointestinal manifestations have been well documented during the pandemic. To date, several centers have reported isolated cases of COVID-19 and its effect on the pancreas. Here, we present a case series of 13 patients with acute pancreatitis (AP) due to COVID-19, which represents one of the larger case series to date. Methods: A retrospective review was performed from 3/1/2020 through 4/1/2020 at 4 NYC academic medical centers. Patients with a diagnosis of AP and COVID-19 were included. AP was diagnosed based on AGA criteria. COVID-19 infection was confirmed via nasopharyngeal viral PCR testing. All patients with a prior history of AP were excluded. Patients with apparent/suspected etiologies of AP (including gallstones, alcohol, hypertriglyceridemia, post ERCP, medication, and other viral etiologies) were excluded. 13 patients met our inclusion and exclusion criteria. Outcomes studied included mortality, ICU admission, length of stay, BISAP scores on admission and at 48 hours. Results: 7 of the 13 patients in this cohort were African American, 8 of 13 were men, and the median age was 51 years of age. The youngest patient was 18 years old and the oldest patient was 71 years old. Of the 13 patients, 5 patients died during their hospital course. Of those 5 who passed, 4 were African American, and all 5 were > 50 years of age. 6 of the 13 required ICU level of care. The mean length of stay for all patients was 23 days. On admission, 4 patients had BISAP scores > 3, at 48 hours 3 patients had BISAP scores > 3. Discussion: We report the characteristics of 13 patients with confirmed SARS-Cov-2 infection and AP without other common etiologies. We suspect that SARS-Cov-2 was a direct cause of AP in these patients. 5 patients died (38.5%) due to multiorgan failure from Acute Respiratory Distress Syndrome. Patients with COVID-19 and AP had a higher mortality rate than the overall mortality reported with COVID-19 during the same period. The mortality of patients in our series far exceeds the reported mortality in mild or moderate AP (less than 1%)1,2. Currently molecular theories suggest that viral attachment to ACE-2 receptors on pancreatic acinar cells leads to apoptosis, inhibition of nitric oxide production, and programmed cell death that ultimately leads to AP. Conclusion: This case series indicates a possible association between COVID-19 and AP and the increased mortality in this subset of patients. Further research is needed concerning the molecular mechanisms and clinical management of this entity. Larger studies are needed to confirm the worse outcomes with AP associated with COVID-19. Ref: 1. Russo MW et al. Digestive and liver diseases statistics, 2004. Gastroenterology. 2004;126:1448–53. 2. Triester SL et al. Prognostic factors in acute pancreatitis. J Clin Gastroenterol. 2002;34:167–76.

6.
34th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2021 ; 12798 LNAI:316-328, 2021.
Article in English | Scopus | ID: covidwho-1366301

ABSTRACT

Examining the genome sequences of the novel coronavirus (COVID-19) strains is critical to properly understand this disease and its functionalities. In bioinformatics, alignment-free (AF) sequence analysis methods offer a natural framework to investigate and understand the patterns and inherent properties of biological sequences. Thus, AF methods are used in this paper for the analysis and comparison of COVID-19 genome sequences. First, frequent patterns of nucleotide base(s) in COVID-19 genome sequences are extracted. Second, the similarity/dissimilarity between COVID-19 genome sequences are measured with different AF methods. This allows to compare sequences and evaluate the performance of various distance measures employed in AF methods. Lastly, the phylogeny for the COVID-19 genome sequences are constructed with various AF methods as well as the consensus tree that shows the level of support (agreement) among phylogenetic trees built by various AF methods. Obtained results show that AF methods can be used efficiently for the analysis of COVID-19 genome sequences. © 2021, Springer Nature Switzerland AG.

7.
Kybernetes ; 2020.
Article in English | Scopus | ID: covidwho-913408

ABSTRACT

Purpose: The novel Coronavirus (COVID-19) pandemic, which started in late December 2019, has spread to more than 200 countries. As no vaccine is yet available for this pandemic, government and health agencies are taking draconian steps to contain it. This pandemic is also trending on social media, particularly on Twitter. The purpose of this study is to explore and analyze the general public reactions to the COVID-19 outbreak on Twitter. Design/methodology/approach: This study conducts a thematic analysis of COVID-19 tweets through VOSviewer to examine people’s reactions related to the COVID-19 outbreak in the world. Moreover, sequential pattern mining (SPM) techniques are used to find frequent words/patterns and their relationship in tweets. Findings: Seven clusters (themes) were found through VOSviewer: Cluster 1 (green): public sentiments about COVID-19 in the USA. Cluster 2 (red): public sentiments about COVID-19 in Italy and Iran and a vaccine, Cluster 3 (purple): public sentiments about doomsday and science credibility. Cluster 4 (blue): public sentiments about COVID-19 in India. Cluster 5 (yellow): public sentiments about COVID-19’s emergence. Cluster 6 (light blue): public sentiments about COVID-19 in the Philippines. Cluster 7 (orange): Public sentiments about COVID-19 US Intelligence Report. The most frequent words/patterns discovered with SPM were “COVID-19,” “Coronavirus,” “Chinese virus” and the most frequent and high confidence sequential rules were related to “Coronavirus, testing, lockdown, China and Wuhan.” Research limitations/implications: The methodology can be used to analyze the opinions/thoughts of the general public on Twitter and to categorize them accordingly. Moreover, the categories (generated by VOSviewer) can be correlated with the results obtained with pattern mining techniques. Social implications: This study has a significant socio-economic impact as Twitter offers content posting and sharing to billions of users worldwide. Originality/value: According to the authors’ best knowledge, this may be the first study to carry out a thematic analysis of COVID-19 tweets at a glance and mining the tweets with SPM to investigate how people reacted to the COVID-19 outbreak on Twitter. © 2020, Emerald Publishing Limited.

SELECTION OF CITATIONS
SEARCH DETAIL