scholarly journals Deep sequencing and in silico analysis of small RNA library reveals novel miRNA from leaf Persicaria minor transcriptome

3 Biotech ◽  
2018 ◽  
Vol 8 (3) ◽  
Author(s):  
Abdul Fatah A. Samad ◽  
Nazaruddin Nazaruddin ◽  
Abdul Munir Abdul Murad ◽  
Jaeyres Jani ◽  
Zamri Zainal ◽  
...  
Keyword(s):  
Deep Sequencing ◽  
Small Rna ◽  
In Silico ◽  
In Silico Analysis ◽  
Novel Mirna ◽  
Persicaria Minor ◽  
Silico Analysis ◽  
Small Rna Library

Identification of miRNA from Bouteloua gracilis, a drought tolerant grass, by deep sequencing and their in silico analysis

2017 ◽  
Vol 66 ◽  
pp. 26-35 ◽  
Author(s):  
Perla Lucía Ordóñez-Baquera ◽  
Everardo González-Rodríguez ◽  
Gerardo Armando Aguado-Santacruz ◽  
Quintín Rascón-Cruz ◽  
Ana Conesa ◽  
...  
Keyword(s):  
Deep Sequencing ◽  
In Silico ◽  
In Silico Analysis ◽  
Bouteloua Gracilis ◽  
Drought Tolerant ◽  
Silico Analysis

scholarly journals The Complexity of Posttranscriptional Small RNA Regulatory Networks Revealed by In Silico Analysis of Gossypium arboreum L. Leaf, Flower and Boll Small Regulatory RNAs

PLoS ONE ◽  
2015 ◽  
Vol 10 (6) ◽  
pp. e0127468 ◽  
Author(s):  
Hongtao Hu ◽  
Aaron M. Rashotte ◽  
Narendra K. Singh ◽  
David B. Weaver ◽  
Leslie R. Goertzen ◽  
...  
Keyword(s):  
Small Rna ◽  
In Silico ◽  
Regulatory Networks ◽  
In Silico Analysis ◽  
Gossypium Arboreum ◽  
Small Regulatory Rnas ◽  
Regulatory Rnas ◽  
Silico Analysis

scholarly journals In silico analysis of RNA and small RNA sequencing data from human BM-MSCs and differentiated osteocytes, chondrocytes and tenocytes

2021 ◽  
Vol 2 ◽  
pp. 19-30
Author(s):  
Srinivas V. Koduru ◽  
Irina A. Elcheva ◽  
Ashley N. Leberfinger ◽  
Dino J. Ravnic
Keyword(s):  
Rna Sequencing ◽  
Small Rna ◽  
In Silico ◽  
In Silico Analysis ◽  
Small Rna Sequencing ◽  
Sequencing Data ◽  
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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