Applications of artificial intelligence in bioinformatics: A review

Artificial intelligence (AT) has increasingly gained attention in bioinformatics research and computational molecular biology. With the availability of different types of AT algorithms, it has become common for the researchers to apply the off-shelf systems to classify and mine their databases. At present, with various intelligent methods available in the literature, researchers are facing difficulties in choosing the best method that could be applied to a specific data set. Researchers need tools, which present the data in a comprehensible fashion, annotated with context, estimates of accuracy and explanation. This article aims to review the use of AT in the areas of bioinformatics and computational molecular biology (DNA sequencing). These areas have risen from the needs of biologists to utilize and help interpret the vast amounts of data that are constantly being gathered in genomic research. The underlying motivation for many of the bioinformatics and DNA sequencing approaches is the evolution of organisms and the complexity of working with erroneous data. This article also describes the kind of software programs which were developed by the research community in order to (1) search, classify and mine different available biological databases; (2) simulate biological experiments with and without errors. (c) 2005 Elsevier Ltd. All rights reserved.