Data Compression Concepts and Algorithms and Their Applications to Bioinformatics
Data compression at its base is concerned with how information is organized in data. Understanding this organization can lead to efficient ways of representing the information and hence data compression. In this paper we review the ways in which ideas and approaches fundamental to the theory and pra...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2009-12-01
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| Series: | Entropy |
| Subjects: | |
| Online Access: | http://www.mdpi.com/1099-4300/12/1/34/ |
| _version_ | 1828118091804966912 |
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| author | Özkan U. Nalbantoglu David J. Russell Khalid Sayood |
| author_facet | Özkan U. Nalbantoglu David J. Russell Khalid Sayood |
| author_sort | Özkan U. Nalbantoglu |
| collection | DOAJ |
| description | Data compression at its base is concerned with how information is organized in data. Understanding this organization can lead to efficient ways of representing the information and hence data compression. In this paper we review the ways in which ideas and approaches fundamental to the theory and practice of data compression have been used in the area of bioinformatics. We look at how basic theoretical ideas from data compression, such as the notions of entropy, mutual information, and complexity have been used for analyzing biological sequences in order to discover hidden patterns, infer phylogenetic relationships between organisms and study viral populations. Finally, we look at how inferred grammars for biological sequences have been used to uncover structure in biological sequences. |
| first_indexed | 2024-04-11T13:25:43Z |
| format | Article |
| id | doaj.art-78edd3c5853b4cdc996ad1793bddaaac |
| institution | Directory Open Access Journal |
| issn | 1099-4300 |
| language | English |
| last_indexed | 2024-04-11T13:25:43Z |
| publishDate | 2009-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Entropy |
| spelling | doaj.art-78edd3c5853b4cdc996ad1793bddaaac2022-12-22T04:22:05ZengMDPI AGEntropy1099-43002009-12-01121345210.3390/e12010034Data Compression Concepts and Algorithms and Their Applications to BioinformaticsÖzkan U. NalbantogluDavid J. RussellKhalid SayoodData compression at its base is concerned with how information is organized in data. Understanding this organization can lead to efficient ways of representing the information and hence data compression. In this paper we review the ways in which ideas and approaches fundamental to the theory and practice of data compression have been used in the area of bioinformatics. We look at how basic theoretical ideas from data compression, such as the notions of entropy, mutual information, and complexity have been used for analyzing biological sequences in order to discover hidden patterns, infer phylogenetic relationships between organisms and study viral populations. Finally, we look at how inferred grammars for biological sequences have been used to uncover structure in biological sequences.http://www.mdpi.com/1099-4300/12/1/34/bioinformaticsdata compressioninformation theory |
| spellingShingle | Özkan U. Nalbantoglu David J. Russell Khalid Sayood Data Compression Concepts and Algorithms and Their Applications to Bioinformatics Entropy bioinformatics data compression information theory |
| title | Data Compression Concepts and Algorithms and Their Applications to Bioinformatics |
| title_full | Data Compression Concepts and Algorithms and Their Applications to Bioinformatics |
| title_fullStr | Data Compression Concepts and Algorithms and Their Applications to Bioinformatics |
| title_full_unstemmed | Data Compression Concepts and Algorithms and Their Applications to Bioinformatics |
| title_short | Data Compression Concepts and Algorithms and Their Applications to Bioinformatics |
| title_sort | data compression concepts and algorithms and their applications to bioinformatics |
| topic | bioinformatics data compression information theory |
| url | http://www.mdpi.com/1099-4300/12/1/34/ |
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