Open Access Open Access  Restricted Access Subscription or Fee Access

Effective Digital Coding of Amino Acids in DNA Using LDPC

A. Suganya, A. Anand, R. Arunadevi, Dr. Senthil Kumar


The harmful disease diagnosed at early stage is the important role of the medical field. The presence of Single nucleotide polymorphism causes DNA sequence difference, affects protein changing the structure and function, which causes the human genetic disease. The technique proposed for digital coding of amino acids in DNA sequences is by combining Codons and LDPC algorithm. The existing system extract the INTRON and EXON of genome by band pass FIR filter. The past work only graphical representation that is not helpful to the medical field. Hence our work towards the digital code of DNA sequence is realizable and reliable. Innovatively, this digital code based on Codons. The Codons is useful for DNA sequence compression during the compression no noise added that is the main advantage of proposed system. This proposed work make use of information theory to set up a model of digital coding, for amino acids.. It transforms the symbolic DNA sequences into digital genetic signals. The proposed LDPC based digital coding most commonly used for error detection and correction that offer huge advantages in terms of coding gain, throughput and power dissipation. The results also provide insight into the pattern of the variations that may have a direct role in the targeted disease and can be used to improve diagnostic reliability for complex human genetic disorders. The design model is tested for several databases of Homo sapiens DNA sequence which have been downloaded from National Center for Biotechnology Information (NCBI) homepage.


LDPC, DNA Amino Codes, Codon.

Full Text:



Bin Wang, Qiang Zhang, Xiapeng Wei, “On the Lower Bounds of DNA Words Sets for DNA Computing”2011.

Hiroaki Uehare, Masakazu Jim, “A Positive Detecting Code and Its Decoding Algorithm for DNA Library Screening,” vol. 6,no.4,october-december 2009.

Hongzan Jiao, Yanfei Zhong, , and Liangpei Zhang, “Artificial DNA omputing-Based Spectral Encoding and Matching Algorithm for Hyperspectral Remote Sensing Data,” 2010

Inbamalar T M, Sivakumar R, “Filtering Approach To DNA Signal Processing,” 2012

A.R. Karmi, M. Ahmadian Attari, H.Tavakoli, “Multi Layer Perceptron Neural Networks Decoder for LDPC Codes,”2009.

Liwei Mu, Xingcheng Liu, Member, IEEE, and Chulong Liang, “Construction of Binary LDPC Convolutional CodesBased on Finite Fields,” 2010

Seung-Ho Kang, Mun-Ho Choi, In-Seon Jeong, “An Efficent Two-Phase Algorithm To Find Gene-Specific Probes for Large Genomes,” Frontiers in the Convergence of Bioscience and Information Technologies 2007

Sheng Li, Qingshan Jiang, Dan Wei, “ An Optimized Algorithm for finding Approximate Tandem Repeats in DNA sequences ,” 2010.

Sushmita Mitra, Ranajit Das, and Yoichi Hayashi, “Genetic Networks And Soft Computing,” 2011

Ting Wu, Haris Vikalo, “Maximum Likelihood DNA sequence detection via Sphere Decoding” 2011.

S.Barman(Mandal) Institute of Radiophysics and Electronics University of Calcutta, “Prediction of Protein Coding Regions of a DNA Sequence through Spectral Analysis”IEEE conference 2012.


  • There are currently no refbacks.

Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.