Computer-Aided DNA Base Calling from Forward and Reverse Electropherograms

Author(s):  
Valerio Freschi ◽  
Alessandro Bogliolo
Keyword(s):  
Dna Base ◽  
2013 ◽  
Vol 06 (02) ◽  
pp. 165-174 ◽  
Author(s):  
Omniyah G. Mohammed ◽  
Khaled T. Assaleh ◽  
Ghaleb A. Husseini ◽  
Amin F. Majdalawieh ◽  
Scott R. Woodward

2017 ◽  
Vol 2017 ◽  
pp. 1-7
Author(s):  
Safa A. Hameed ◽  
Raed I. Hamed

This paper presented the issues of true representation and a reliable measure for analyzing the DNA base calling is provided. The method implemented dealt with the data set quality in analyzing DNA sequencing, it is investigating solution of the problem of using Neurofuzzy techniques for predicting the confidence value for each base in DNA base calling regarding collecting the data for each base in DNA, and the simulation model of designing the ANFIS contains three subsystems and main system; obtain the three features from the subsystems and in the main system and use the three features to predict the confidence value for each base. This is achieving effective results with high performance in employment.


Author(s):  
Omniyah Gul M. Khan ◽  
Khaled T. Assaleh ◽  
Ghaleb A. Husseini ◽  
Amin F. Majdalawieh ◽  
Scott R. Woodward

2016 ◽  
Vol 2 (4) ◽  
pp. 424
Author(s):  
Raed Hamed ◽  
Safa A. Hameed

The paper proposes an efficient approach applied in DNA base calling, which concerns efficiency and sensitivity. We utilized the Neuro-Fuzzy model in the analysis issues to determine the confidence value prediction in DNA base calling, that is solved by several attempts applied in the MATLAB tool, the model is implemented for the collected data for each base in the DNA sequencing. The model is designed by using the ANFIS tool, which contains  three subsystems a main system. We obtain three features (peakness, height, and spacing) for each base from the three subsystems and in the main system use these three features as the input to predict the confidence value for each base in the DNA. This achieves a high accuracy in the obtained results with high-performance.


2000 ◽  
Vol 104 (1-3) ◽  
pp. 229-258 ◽  
Author(s):  
Manuela S. Pereira ◽  
Lucio Andrade ◽  
Sameh El Difrawy ◽  
Barry L. Karger ◽  
Elias S. Manolakos

Author(s):  
Omniyah G. Mohammed ◽  
Khaled T. Assaleh ◽  
Ghaleb A. Husseini ◽  
Amin F. Majdalawieh ◽  
Scott R. Woodward

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