scholarly journals An in silico analysis of robust but fragile gene regulation links enhancer length to robustness

2019 ◽  
Vol 15 (11) ◽  
pp. e1007497 ◽  
Author(s):  
Kenneth Barr ◽  
John Reinitz ◽  
Ovidiu Radulescu
Keyword(s):  
Gene Regulation ◽  
In Silico ◽  
In Silico Analysis ◽  
Silico Analysis

In Silico Analysis of miRNA-Mediated Gene Regulation in OCA and OA Genes

2014 ◽  
Vol 70 (3) ◽  
pp. 1923-1932 ◽  
Author(s):  
Balu Kamaraj ◽  
Chandrasekhar Gopalakrishnan ◽  
Rituraj Purohit
Keyword(s):  
Gene Regulation ◽  
In Silico ◽  
In Silico Analysis ◽  
Silico Analysis

scholarly journals The role of mobile genetic elements in evolution of cyanobacteria

2011 ◽  
Vol 9 (4) ◽  
pp. 52-62
Author(s):  
Lidia E Mikheeva ◽  
Elena A Karbysheva ◽  
Sergey V Shestakov
Keyword(s):  
Gene Regulation ◽  
Significant Role ◽  
In Silico ◽  
In Silico Analysis ◽  
Whole Genome ◽  
Number Of Genes ◽  
Genes Encoding ◽  
Adaptation Processes ◽  
Silico Analysis

Possible pathways of cyanobacterial evolution are discussed on the basis of in silico analysis of fully sequenced genomes of 45 species/strains of cyanobacteria. The information on quantity and functions of different mobile elements (IS, MITE elements and group II introns) was reviewed. Positive correlation between whole genome sizes and number of genes, encoding transposases has been revealed. It is suggested that transpositions play significant role in genome rearrangements taking part in gene regulation and adaptation processes determining the directions of microevolution processes in cyanobacterial populations.

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
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