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Cancerous/Disease DNA Prediction Using Fixed Length Motifs/Frequent Patterns Matching


Adnan Ferdous Ashrafi, Shah S Mahin, Tarikuzzaman Emon
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In the radical field of bioinformatics, one very interesting and rather concerning area of research is predicting cancer infected gene from a set of samples of species DNA. This field is quite a challenging one considering the limited knowledge on how cancers affect gene of species and the pattern of mutation are not always the same. Gene prediction can be effectively done through several techniques like frequent pattern mining, neural networks or sequence alignment. These traditional approaches were able to predict to a very small limit. In this paper a new method using frequent patterns/motifs is shown that can be a new strategy for prediction of gene in a DNA. As the motifs in a DNA are the conserved region, so it's more appropriate to be used for gene predication and alignment. The new method proposed in this paper includes the sampling of fixed length motifs from a sequence of reference genome and finally other samples are aligned against the more frequent motifs to establish their relevancy to the reference genome.

Adnan Ferdous Ashrafi, Shah S Mahin, Tarikuzzaman Emon

Gene Prediction; Cancer Cell Prediction; Motifs; Hash Table; Frequent Pattern Matching;

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Publication Details

Published in : Volume 2 | Issue 5 | September-October - 2016
Date of Publication Print ISSN Online ISSN
2016-10-30 2395-1990 2394-4099
Page(s) Manuscript Number   Publisher
15-22 IJSRSET16253   Technoscience Academy

Cite This Article

Adnan Ferdous Ashrafi, Shah S Mahin, Tarikuzzaman Emon, "Cancerous/Disease DNA Prediction Using Fixed Length Motifs/Frequent Patterns Matching", International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 2, Issue 5, pp.15-22, September-October-2016.
URL : http://ijsrset.com/IJSRSET16253.php

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