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Application Microarray Technology in Infectious Diseases

Nazari Nodooshan, Khadijeh | 2009

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 39376 (02)
  4. University: Sharif University of Technology
  5. Department: Mathematical Sciences
  6. Advisor(s): Mahdavi-Amiri, Nezameddin; Karami, Ali
  7. Abstract:
  8. DNA microarrays consist of DNA microscopic points that are attached to a solid surface such as glass, plastic or silicon chip and formed as an array. The fixed pieces of DNA are considered as searchers. In an experiment, we can use thousands of searchers. Therefore, any microarray consists of the same number of genetic tests as the experiment performed on all of them in parallel. Whit this ability, arrays have speeded up the biological investigations. Microarray technology can be seen as a continued development of southern blotting. However, the most important stage in this technology, analysis of data, requires reliable bioinformatics tools achieving high reliabilities. Infectious diseases, from the beginning of human life, always have been with human beings and have caused major difficulties for them. One of the most important usages of microarray technology is the possibility of testing for the presence of thousands of micro-organism in environmental and clinical samples only in a single experiment, resulting in recognition of pathogens. Thereby, we can take an important step in curing the disease. As noted above, the most important stage in microarray technology is the data analysis. We present E-Predict algorithm and DetectiV package, for microarray based species identifications. We demonstrate the application of E-Predict and DetectiV to viral detection in a large, publicly available dataset and show that DetectiV performs better than E-Predict. DetectiV is implemented as a package for R, a powerful and open source software for statistical programming, containing visualization, normalization and significance testing functions
  9. Keywords:
  10. Microarray ; Microarray Data ; Microarray Data Analysis ; Infectious Diseases

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