Using bioinformatics techniques for gene identification in drug discovery and development

Chen, Yi-Ping Phoebe and Chen, Feng 2008, Using bioinformatics techniques for gene identification in drug discovery and development, Current drug metabolism, vol. 9, no. 6, pp. 567-573, doi: 10.2174/138920008784892056.

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Title Using bioinformatics techniques for gene identification in drug discovery and development
Author(s) Chen, Yi-Ping Phoebe
Chen, Feng
Journal name Current drug metabolism
Volume number 9
Issue number 6
Start page 567
End page 573
Publisher Bentham Science Publishers Ltd.
Place of publication Hilversun, The Netherlands
Publication date 2008-07
ISSN 1389-2002
Summary As more and more evidence has become available, the link between gene and emergent disease has been made including cancer, heart disease and parkinsonism. Analyzing the diseases and designing drugs with respect to the gene and protein level obviously help to find the underlying causes of the diseases, and to improve their rate of cure. The development of modern molecular biology, biochemistry, data collection and analysis techniques provides the scientists with a large amount of gene data. To draw a link between genes and their relation to disease outcomes and drug discovery is a big challenge: How to analyze large datasets and extract useful knowledge? Combining bioinformatics with drug discovery is a promising method to tackle this issue. Most techniques of bioinformatics are used in the first two phases of drug discovery to extract interesting information and find important genes and/or proteins for speeding the process of drug discovery, enhancing the accuracy of analysis and reducing the cost. Gene identification is a very fundamental and important technique among them. In this paper, we have reviewed gene identification algorithms and discussed their usage, relationships and challenges in drug discovery and development.
Language eng
DOI 10.2174/138920008784892056
Field of Research 060102 Bioinformatics
HERDC Research category C1 Refereed article in a scholarly journal
HERDC collection year 2008
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