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Collection and Extraction of Saliva DNA for Next Generation Sequencing
Published on: August 27, 2014
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RepEx: A web server to extract sequence repeats from protein and DNA sequences.
Daliah Michael1, M Gurusaran1, R Santhosh1
1Department of Computational and Data Sciences, Indian Institute of Science, Bangalore, 560 012, India.
Computational Biology and Chemistry
|January 2, 2019
Summary
RepEx is a new web server that efficiently extracts various types of sequence repeats from DNA and protein data. This tool aids researchers in analyzing genetic material for disease research and understanding macromolecule function.
Area of Science:
- Bioinformatics
- Genomics
- Computational Biology
Background:
- Evolution generates genetic material through ordered patterns, including sequence repeats.
- Sequence repeats offer valuable insights into disease research and macromolecule function.
- Next-generation sequencing necessitates rapid and unbiased extraction of sequence repeats.
Purpose of the Study:
- To develop an accessible online tool for extracting all types of sequence repeats from DNA and protein sequences.
- To provide researchers with an efficient method for analyzing genetic and protein sequence data.
Main Methods:
- Development of a web-based computing server named RepEx.
- Implementation of algorithms to identify exact, degenerate, inverted, everted, and mirror repeats.
- Design of an intuitive interface with search filters and interactive visualizations.
Main Results:
- RepEx successfully extracts a comprehensive range of sequence repeats from both DNA and protein sequences.
- The server provides interactive graphs and detailed output files for user analysis.
- The tool is freely available online, facilitating broad accessibility for the scientific community.
Conclusions:
- RepEx addresses the need for efficient sequence repeat extraction in the era of next-generation sequencing.
- The server enhances the study of genetic variations, disease mechanisms, and macromolecule functions.
- RepEx offers a valuable, user-friendly resource for bioinformatics research.
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