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|Title:||Advanced in silico analysis of expressed sequence tag (EST) data for parasitic nematodes of major socio-economic importance - Fundamental insights toward biotechnological outcomes|
|Authors:||Ranganathan, S. |
|Citation:||Ranganathan, S., Menon, R., Gasser, R.B. (2009). Advanced in silico analysis of expressed sequence tag (EST) data for parasitic nematodes of major socio-economic importance - Fundamental insights toward biotechnological outcomes. Biotechnology Advances 27 (4) : 439-448. ScholarBank@NUS Repository. https://doi.org/10.1016/j.biotechadv.2009.03.005|
|Abstract:||Parasitic nematodes infect humans, other animals and plants, and impose a significant public health and economic burden worldwide due to the diseases that they cause. A better understanding of parasite genomes, host-parasite relationships and the molecular biology of parasites themselves will enable the rational development of diagnostic tests and/or safe anti-parasitic compounds, following the functional annotation of parasite genomic sequences. With only a few completely sequenced nematode genomes, expressed sequence tag (EST) datasets provide a low-cost alternative ("poor man's genome") to whole genome sequences and a glimpse of the transcriptome of an organism. EST data require a number of computational methods for their pre-processing, clustering, assembly and annotation to yield biologically relevant information. In this article, we review the steps involved in EST data analysis, the development of new semi-automated bioinformatic pipelines and their application to parasitic nematodes of major socio-economic significance, focused on identifying molecules involved in key biological processes or pathways that might serve as targets for new drugs or vaccines. © 2009 Elsevier Inc. All rights reserved.|
|Source Title:||Biotechnology Advances|
|Appears in Collections:||Staff Publications|
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