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i-Genome: a database to summarize oligonucleotide data in genomes.
Feng-Mao Lin1, Hsien-Da Huang, Yu-Chung Chang
1Department of Computer Science and Information Engineering National Central University, Chung-Li 320, Taiwan. meta@db.csie.ncu.edu.tw <meta@db.csie.ncu.edu.tw>
BMC Genomics
|October 12, 2004
Summary
This study introduces an efficient computational method and database for analyzing sequence features in complete genomes. It provides rapid access to oligonucleotide occurrences and repetitive elements, aiding genomic research.
Area of Science:
- Genomics
- Bioinformatics
- Computational Biology
Background:
- Genome sequence feature occurrence is vital for comparative genomics, evolutionary studies, and regulatory sequence analysis.
- Current methods for computing pattern frequencies in complete genomes are computationally intensive and time-consuming.
Purpose of the Study:
- To develop and implement an efficient computational approach for accumulating oligonucleotide occurrences in complete genomes.
- To establish a database for maintaining comprehensive sequence feature information.
Main Methods:
- Exhaustive computation of sequences from complete genomes.
- Integration of repetitive elements (LINEs, SINEs, Alu, LTR) from Repbase.
- Development of a database to store and query sequence feature data.
Main Results:
- A database containing sequence feature information for various genomes, including human, yeast, worm, and 128 microbial species.
- Information on oligonucleotide distributions, gene distributions, and repetitive element occurrences.
- Efficient retrieval of repetitive genomic features.
Conclusions:
- An efficient computational approach for analyzing oligonucleotide occurrences in complete genomes has been developed.
- A dedicated database facilitates access to genomic sequence features, including repetitive elements.
- The database enhances the efficiency and effectiveness of accessing repetitive genomic features for research.