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Modified HuffBit Compress Algorithm - An Application of R.
Habib, Nahida; Ahmed, Kawsar; Jabin, Iffat; Rahman, Mohammad Motiur.
Afiliación
  • Habib N; Department of Computer Science and Engineering (CSE), Mawlana Bhashani Science and Technology University (MBSTU), Santosh, Tangail 1902, Bangladesh.
  • Ahmed K; Department of Information and Communication Technology (ICT), Mawlana Bhashani Science and Technology University (MBSTU), Tangail, Bangladesh.
  • Jabin I; Department of Computer Science and Engineering (CSE), Mawlana Bhashani Science and Technology University (MBSTU), Tangail, Bangladesh.
  • Rahman MM; Department of Computer Science and Engineering (CSE), Mawlana Bhashani Science and Technology University (MBSTU), Tangail, Bangladesh.
J Integr Bioinform ; 15(3)2018 Feb 22.
Article en En | MEDLINE | ID: mdl-29470175
ABSTRACT
The databases of genomic sequences are growing at an explicative rate because of the increasing growth of living organisms. Compressing deoxyribonucleic acid (DNA) sequences is a momentous task as the databases are getting closest to its threshold. Various compression algorithms are developed for DNA sequence compression. An efficient DNA compression algorithm that works on both repetitive and non-repetitive sequences known as "HuffBit Compress" is based on the concept of Extended Binary Tree. In this paper, here is proposed and developed a modified version of "HuffBit Compress" algorithm to compress and decompress DNA sequences using the R language which will always give the Best Case of the compression ratio but it uses extra 6 bits to compress than best case of "HuffBit Compress" algorithm and can be named as the "Modified HuffBit Compress Algorithm". The algorithm makes an extended binary tree based on the Huffman Codes and the maximum occurring bases (A, C, G, T). Experimenting with 6 sequences the proposed algorithm gives approximately 16.18 % improvement in compression ration over the "HuffBit Compress" algorithm and 11.12 % improvement in compression ration over the "2-Bits Encoding Method".
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Algoritmos / Programas Informáticos / Genoma Humano / Análisis de Secuencia de ADN / Compresión de Datos / Secuenciación de Nucleótidos de Alto Rendimiento Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: J Integr Bioinform Asunto de la revista: INFORMATICA MEDICA Año: 2018 Tipo del documento: Article País de afiliación: Bangladesh

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Algoritmos / Programas Informáticos / Genoma Humano / Análisis de Secuencia de ADN / Compresión de Datos / Secuenciación de Nucleótidos de Alto Rendimiento Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: J Integr Bioinform Asunto de la revista: INFORMATICA MEDICA Año: 2018 Tipo del documento: Article País de afiliación: Bangladesh