scholarly journals In silico analysis of AHJD ‐like viruses, Staphylococcus aureus phages S24‐1 and S13′, and study of phage S24‐1 adsorption

2014 ◽  
Vol 3 (2) ◽  
pp. 257-270 ◽  
Author(s):  
Jumpei Uchiyama ◽  
Iyo Takemura‐Uchiyama ◽  
Shin‐ichiro Kato ◽  
Miho Sato ◽  
Takako Ujihara ◽  
...  
Keyword(s):  
Staphylococcus Aureus ◽  
In Silico ◽  
In Silico Analysis ◽  
Silico Analysis

Design and in silico analysis of a whole‐cell biosensor able to kill methicillin‐resistant Staphylococcus aureus

2021 ◽  
Author(s):  
Diego Francisco Benítez‐Chao ◽  
Francisco de Jesús Balderas‐Cisneros ◽  
Angel León‐Buitimea ◽  
José Rubén Morones‐Ramírez
Keyword(s):  
Staphylococcus Aureus ◽  
In Silico ◽  
Methicillin Resistant Staphylococcus Aureus ◽  
In Silico Analysis ◽  
Whole Cell ◽  
Methicillin Resistant ◽  
Whole Cell Biosensor ◽  
Silico Analysis ◽  
Cell Biosensor

scholarly journals In silico analysis of ciprofloxacin analogs as inhibitors of DNA gyrase of Staphylococcus aureus

2021 ◽  
pp. 100748
Author(s):  
Md Rakhibul Hasan ◽  
Surid Mohammad Chowdhury ◽  
Md Abdul Aziz ◽  
Asif Shahriar ◽  
Hossain Ahmed ◽  
...  
Keyword(s):  
Staphylococcus Aureus ◽  
In Silico ◽  
In Silico Analysis ◽  
Dna Gyrase ◽  
Silico Analysis

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

In Silico Analysis of Single Nucleotide Polymorphism in Human Prothrombin Gene

2019 ◽  
Author(s):  
I. Farah ◽  
A. El-Mubark ◽  
M. Osman ◽  
A. Soliman ◽  
F. Ali ◽  
...  
Keyword(s):  
Single Nucleotide Polymorphism ◽  
In Silico ◽  
In Silico Analysis ◽  
Nucleotide Polymorphism ◽  
Single Nucleotide ◽  
Prothrombin Gene ◽  
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
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