scholarly journals Summary of the Available Molecular Methods for Detection of SARS-CoV-2 during the Ongoing Pandemic

2021 ◽  
Vol 22 (3) ◽  
pp. 1298
Author(s):  
Fabio Arena ◽  
Simona Pollini ◽  
Gian Maria Rossolini ◽  
Maurizio Margaglione
Keyword(s):  
Genetic Variability ◽  
Viral Genome ◽  
Molecular Detection ◽  
In Silico Analysis ◽  
Laboratory Diagnosis ◽  
Mortality Rates ◽  
Genomic Evolution ◽  
Review Of The Literature ◽  
The Uk ◽  
Silico Analysis

Since early 2020, the COVID-19 pandemic has caused an excess in morbidity and mortality rates worldwide. Containment strategies rely firstly on rapid and sensitive laboratory diagnosis, with molecular detection of the viral genome in respiratory samples being the gold standard. The reliability of diagnostic protocols could be affected by SARS-CoV-2 genetic variability. In fact, mutations occurring during SARS-CoV-2 genomic evolution can involve the regions targeted by the diagnostic probes. Following a review of the literature and an in silico analysis of the most recently described virus variants (including the UK B 1.1.7 and the South Africa 501Y.V2 variants), we conclude that the described genetic variability should have minimal or no effect on the sensitivity of existing diagnostic protocols for SARS-CoV-2 genome detection. However, given the continuous emergence of new variants, the situation should be monitored in the future, and protocols including multiple targets should be preferred.

scholarly journals Summarize of the Available Molecular Methods for Detection of Sars-Cov-2 During the Ongoing Pandemic

2021 ◽  
Author(s):  
Fabio Arena ◽  
Simona Pollini ◽  
Gian Maria Rossolini ◽  
Maurizio Margaglione
Keyword(s):  
Genetic Variability ◽  
Gold Standard ◽  
Viral Genome ◽  
Molecular Detection ◽  
In Silico Analysis ◽  
Laboratory Diagnosis ◽  
Genomic Evolution ◽  
Review Of The Literature ◽  
The Uk ◽  
Silico Analysis

Starting from early 2020, the COVID-19 pandemic has caused a morbidity and mortality excess worldwide. Containment strategies rely firstly on rapid and sensitive laboratory diagnosis with molecular detection of the viral genome in respiratory samples being the gold standard. Reliability of diagnostic protocols could be affected by SARS-CoV-2 genetic variability. In fact, mutations occurring during SARS-CoV-2 genomic evolution can involve the regions targeted by the diagnostic probes. Following a review of the literature and an in silico analysis of the most recently described virus variants (including the UK B 1.1.7 and the South Africa 501Y.V2 variants), we conclude that the described genetic variability should have minimal or no effect on the sensitivity of existing diagnostic protocols for SARS-CoV-2 genome detection. However, given the continuous emergence of new variants, the situation should be monitored in the future, and protocols including multiple targets should be preferred.

scholarly journals An in-silico analysis of information sharing systems for adaptable resources management: a case study of oyster farmers

2019 ◽  
Vol 1 ◽  
pp. 16166
Author(s):  
Nicolas Paget ◽  
Bruno Bonté ◽  
Olivier Barreteau ◽  
Gabriella Pigozzi ◽  
Pierre Maurel
Keyword(s):  
Decision Making ◽  
Information Sharing ◽  
In Silico Analysis ◽  
Mortality Rates ◽  
Agent Based ◽  
Resources Management ◽  
Agent Based Modelling ◽  
Share Information ◽  
Silico Analysis

Information sharing systems are often viewed as a potential way of increasing scrutiny by actors of their interactions with natural resources. Scrutiny is then seen as encouraging sustainable and adaptable management of the resource. We tackle this claim by using an agent-based model to focus on the specific issue of oyster farmers dealing with the deadly OsHV-1 virus by sharing information about their own experience (practices and outcomes) via their social network and/or an information sharing system. We followed closely what access to such information sharing means for the environment (production), agents (beliefs) and interactions between the environment and agents (practices). In the model, introducing information sharing leads to a decrease in mortality rates and a convergence in agents’ beliefs. Agents stop changing their practices earlier when they share information, but heterogeneity in agent decision-making models leads to wider exploration of possible strategies and increased production. Agent-based modelling proved a suitable method for studying the impacts of information sharing.

A systematic review with in silico analysis on transcriptomic profile of gallbladder carcinoma

2020 ◽  
Vol 47 (6) ◽  
pp. 398-408
Author(s):  
Sonam Tulsyan ◽  
Showket Hussain ◽  
Balraj Mittal ◽  
Sundeep Singh Saluja ◽  
Pranay Tanwar ◽  
...  
Keyword(s):  
Systematic Review ◽  
Gallbladder Carcinoma ◽  
In Silico ◽  
In Silico Analysis ◽  
Transcriptomic Profile ◽  
Silico Analysis

Enalos Suite of Tools: Enhancing Cheminformatics and Nanoinfor - matics through KNIME

2020 ◽  
Vol 27 (38) ◽  
pp. 6523-6535 ◽  
Author(s):  
Antreas Afantitis ◽  
Andreas Tsoumanis ◽  
Georgia Melagraki
Keyword(s):  
Data Analysis ◽  
Virtual Screening ◽  
In Silico ◽  
Model Development ◽  
In Silico Analysis ◽  
Material Design ◽  
Efficient Solutions ◽  
Biological Data ◽  
Cost Efficient ◽  
Silico Analysis

Drug discovery as well as (nano)material design projects demand the in silico analysis of large datasets of compounds with their corresponding properties/activities, as well as the retrieval and virtual screening of more structures in an effort to identify new potent hits. This is a demanding procedure for which various tools must be combined with different input and output formats. To automate the data analysis required we have developed the necessary tools to facilitate a variety of important tasks to construct workflows that will simplify the handling, processing and modeling of cheminformatics data and will provide time and cost efficient solutions, reproducible and easier to maintain. We therefore develop and present a toolbox of >25 processing modules, Enalos+ nodes, that provide very useful operations within KNIME platform for users interested in the nanoinformatics and cheminformatics analysis of chemical and biological data. With a user-friendly interface, Enalos+ Nodes provide a broad range of important functionalities including data mining and retrieval from large available databases and tools for robust and predictive model development and validation. Enalos+ Nodes are available through KNIME as add-ins and offer valuable tools for extracting useful information and analyzing experimental and virtual screening results in a chem- or nano- informatics framework. On top of that, in an effort to: (i) allow big data analysis through Enalos+ KNIME nodes, (ii) accelerate time demanding computations performed within Enalos+ KNIME nodes and (iii) propose new time and cost efficient nodes integrated within Enalos+ toolbox we have investigated and verified the advantage of GPU calculations within the Enalos+ nodes. Demonstration data sets, tutorial and educational videos allow the user to easily apprehend the functions of the nodes that can be applied for in silico analysis of data.

In-Silico Analysis of Chromone Containing Sulfonamide Derivatives as Human Carbonic Anhydrase Inhibitors

2013 ◽  
Vol 9 (4) ◽  
pp. 608-616 ◽  
Author(s):  
Zaheer Ul-Haq ◽  
Saman Usmani ◽  
Uzma Mahmood ◽  
Mariya al-Rashida ◽  
Ghulam Abbas
Keyword(s):  
Carbonic Anhydrase ◽  
In Silico ◽  
In Silico Analysis ◽  
Carbonic Anhydrase Inhibitors ◽  
Human Carbonic Anhydrase ◽  
Silico Analysis
Sign in / Sign up

Export Citation Format

Share Document