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International Journal of Computational Bioinformatics and In Silico Modeling
2014: Volume-3 Issue-6
ISSN: 2320-0634

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International Journal of Computational Bioinformatics and In Silico Modeling 3(6) 2014: 538-542

Metadata-Driven Management, Analysis, and Visualization of GPCR data using NGS approach



Aman Chandra Kaushik and Shakti Sahi*

School of Biotechnology, Gautam Buddha University, Greater Noida, Uttar Pradesh, India

* Corresponding Author

ABSTRACT

Next generation sequencing (NGS) technology is better method for genome and transcriptome sequencing. NGS technologies are relatively easy and error free compared to the Sanger method. With the help of NGS we can identify gene structure as well as transcriptome sequencing. A typical metadata driven management, analysis and visualization of G-Protein coupled receptor (GPCR) dataset in different-different species is reported here. We considered the assignment of GPCR reads to gene families using BLAST for identification of genes and introduced a clustering method which reduces the complexity of metagenome dataset. We report that the clustering method is more accurate than the direct assignment for studies of the Homo sapiens GPCRs and other GPCRs in general. Along with the advent of next-generation sequencing platforms, several high-performance sequence analysis pipelines will be helpful for the detection of type 2 diabetes.

 


Copyright © 2014 | AIZEON publishers | All rights reserved

 

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Citation: Aman Chandra Kaushik et al. (2014). Metadata-Driven Management, Analysis, and Visualization of GPCR data using NGS approach. Int J Comput Bioinfo In Silico Model 3(6): 538-542

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