Click for new scientific resources and news about Corona[COVID-19]

Paper Information

Journal:   MODERN GENETICS JOURNAL (MGJ)   SPRING 2007 , Volume 2 , Number 1; Page(s) 47 To 54.
 
Paper: 

GENE FINDING USING HMM IN PROKARYOTIC GENOMES

 
 
Author(s):  MALEKSHAHI R., MEHRI DEHNAVI A., BEIGI M., POORHOSEIN M.
 
* 
 
Abstract: 

Development of bacterial databases is crucial and every year the number of prokaryotic genome is increasing. The problem of identifying genes in genomic DNA sequences by computational methods has attracted considerable research attention in recent years.
A Full automatic and self-train Gene finder is presented in this research. This system uses non-looped HMM to measure of statistical significance for Genes in prokaryotic genomes. Design of this software was done in three main programs and developed in C++. First program is presented for extraction the DATA (Long non-overlapping ORFs) to train the machine learning algorithm in a self-training method. Second program is related to the training stage. In this stage, HMM is trained with the data that obtained in the previous stage. We model standard 'text book genes' with an unbroken open reading frame. In the last program, The Long ORFs is scored with the trained system. Finally, Genes are selected on the base on their lengths and scores. Our Gene finder can predicts genes with Specifity
>96 and Sensetivity>84. The result shows that overall performance of our software matches other methods that are designed by others.

 
Keyword(s): GENE RECOGNITION, RIBOSOME BINDING SITE, HMM, GENE OVERLAPPING
 
References: 
  • ندارد
 
  Persian Abstract Yearly Visit 52
 
Latest on Blog
Enter SID Blog