scholarly journals Finding of regulatory codes in 5`-UTR of A. thaliana mRNAs by polysome profiling method

2020 ◽  
Author(s):  
K. V. Kabardaeva ◽  
O. N. Mustafaev ◽  
I. V. Deineko ◽  
A. V. Suhorukova ◽  
I. V. Goldenkova-Pavlova
Keyword(s):  
Rna Sequencing ◽  
In Silico ◽  
In Silico Analysis ◽  
Translational Efficiency ◽  
Mrna Pool ◽  
Polysome Profiling ◽  
Silico Analysis

The polysome profiling method was used to separate mRNAs depending on their loading by ribosomes into polysomal and monosomal fractions. Pools separation of such mRNAs and analysis of transcripts (mRNAs) which are associated with each mRNA pool due to RNA sequencing allowed to get an idea of the translational efficiency of individual mRNAs. Moreover, subsequent in silico analysis make possible searching of regulatory contexts in the 5'-UTR of plant A. thaliana, which may be potentially important for efficient translation of mRNA.

In Silico Analysis of Micro-RNA Sequencing Data

2021 ◽  
pp. 231-251
Author(s):  
Ernesto Aparicio-Puerta ◽  
Bastian Fromm ◽  
Michael Hackenberg ◽  
Marc K. Halushka
Keyword(s):  
Rna Sequencing ◽  
In Silico ◽  
In Silico Analysis ◽  
Micro Rna ◽  
Sequencing Data ◽  
Silico Analysis

scholarly journals In silico analysis of inner ear development using public whole embryonic body single-cell RNA-sequencing data

2021 ◽  
Vol 469 ◽  
pp. 160-171
Author(s):  
Ryosuke Yamamoto ◽  
Hiroe Ohnishi ◽  
Koichi Omori ◽  
Norio Yamamoto
Keyword(s):  
Single Cell ◽  
Inner Ear ◽  
Rna Sequencing ◽  
In Silico ◽  
In Silico Analysis ◽  
Sequencing Data ◽  
Ear Development ◽  
Inner Ear Development ◽  
Single Cell Rna Sequencing ◽  
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
Sign in / Sign up

Export Citation Format

Share Document