Abstract
Motivation: Textual data compression, and the associatedtechniques coming from information theory, are often perceived asbeing of interest for data communication and storage. However, theyare also deeply related to classification and data mining and analysis.In recent years, a substantial effort has been made for the applicationof textual data compression techniques to various computationalbiology tasks, ranging from storage and indexing of large datasetsto comparison and reverse engineering of biological networks.Results: The main focus of this review is on a systematicpresentation of the key areas of bioinformatics and computationalbiology where compression has been used. When possible, aunifying organization of the main ideas and techniques is alsoprovided.Availability: It goes without saying that most of the researchresults reviewed here offer software prototypes to the bioinformaticscommunity. The Supplementary Material provides pointers tosoftware and benchmark datasets for a range of applications ofbroad interest. In addition to provide reference to software, theSupplementary Material also gives a brief presentation of somefundamental results and techniques related to this paper. It is at:http://www.math.unipa.it/~raffaele/suppMaterial/compReview/
Lingua originale | English |
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pagine (da-a) | 1575-1586 |
Numero di pagine | 12 |
Rivista | Bioinformatics |
Volume | 2009 |
Stato di pubblicazione | Published - 2009 |
All Science Journal Classification (ASJC) codes
- ???subjectarea.asjc.2600.2613???
- ???subjectarea.asjc.1300.1303???
- ???subjectarea.asjc.1300.1312???
- ???subjectarea.asjc.1700.1706???
- ???subjectarea.asjc.1700.1703???
- ???subjectarea.asjc.2600.2605???