Computational analysis of <em>Entamoeba histolytica</em> genome- Exploring junk DNA for hidden messages - INRAE - Institut national de recherche pour l’agriculture, l’alimentation et l’environnement Access content directly
Master Thesis Year : 2006

Computational analysis of Entamoeba histolytica genome- Exploring junk DNA for hidden messages

Manish Kushwaha

Abstract

Increasingly large numbers of microRNAs are being discovered everyday and their role in gene regulation being better understood. A number of computational methods for the prediction of microRNAs are homology based and can miss out on any unique microRNA. A part of this work was dedicated to the development of an effective ab initio pipeline (CIDmiRNA) for microRNA prediction. This pipeline showed a sensitivity of 91.7% for Human microRNA prediction. Entamoeba histolytica is the causative agent of human invasive amoebiasis, a common health problem in developing countries. Despite a lot of available information about the biology of this organism, no microRNAs have yet been reported. In this work, 6 putative microRNA genes were discovered in E. histolytica using CIDmiRNA, a computational prediction pipeline. Also, the intergenic regions of E. histolytica were analysed, exploring for novel genes using computational methods. We were able to predict at least 2 highly likely candidates for being novel genes missed out in the current annotation.
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Dates and versions

hal-02824521 , version 1 (06-06-2020)

Identifiers

  • HAL Id : hal-02824521 , version 1
  • PRODINRA : 440864

Cite

Manish Kushwaha. Computational analysis of Entamoeba histolytica genome- Exploring junk DNA for hidden messages. Life Sciences [q-bio]. 2006. ⟨hal-02824521⟩

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