Distributed Bioinformatics Computing System for DNA Sequence Analysis

α
Chotan Sheel
Chotan Sheel
σ
Dr. Mohammad Ibrahim Khan
Dr. Mohammad Ibrahim Khan
ρ
Dr. Kaushik Deb
Dr. Kaushik Deb
α to ρ Chittagong University of Engineering & Technology

Send Message

To: Author

Distributed Bioinformatics Computing System for DNA Sequence Analysis

Article Fingerprint

ReserarchID

600DO

Distributed Bioinformatics Computing System for DNA Sequence Analysis Banner

AI TAKEAWAY

Connecting with the Eternal Ground
  • English
  • Afrikaans
  • Albanian
  • Amharic
  • Arabic
  • Armenian
  • Azerbaijani
  • Basque
  • Belarusian
  • Bengali
  • Bosnian
  • Bulgarian
  • Catalan
  • Cebuano
  • Chichewa
  • Chinese (Simplified)
  • Chinese (Traditional)
  • Corsican
  • Croatian
  • Czech
  • Danish
  • Dutch
  • Esperanto
  • Estonian
  • Filipino
  • Finnish
  • French
  • Frisian
  • Galician
  • Georgian
  • German
  • Greek
  • Gujarati
  • Haitian Creole
  • Hausa
  • Hawaiian
  • Hebrew
  • Hindi
  • Hmong
  • Hungarian
  • Icelandic
  • Igbo
  • Indonesian
  • Irish
  • Italian
  • Japanese
  • Javanese
  • Kannada
  • Kazakh
  • Khmer
  • Korean
  • Kurdish (Kurmanji)
  • Kyrgyz
  • Lao
  • Latin
  • Latvian
  • Lithuanian
  • Luxembourgish
  • Macedonian
  • Malagasy
  • Malay
  • Malayalam
  • Maltese
  • Maori
  • Marathi
  • Mongolian
  • Myanmar (Burmese)
  • Nepali
  • Norwegian
  • Pashto
  • Persian
  • Polish
  • Portuguese
  • Punjabi
  • Romanian
  • Russian
  • Samoan
  • Scots Gaelic
  • Serbian
  • Sesotho
  • Shona
  • Sindhi
  • Sinhala
  • Slovak
  • Slovenian
  • Somali
  • Spanish
  • Sundanese
  • Swahili
  • Swedish
  • Tajik
  • Tamil
  • Telugu
  • Thai
  • Turkish
  • Ukrainian
  • Urdu
  • Uzbek
  • Vietnamese
  • Welsh
  • Xhosa
  • Yiddish
  • Yoruba
  • Zulu

Abstract

This paper provides an effective design of computing technique of a distributed bioinformatics computing system for analysis of DNA sequences using OPTSDNA algorithm. This system could be used for disease detection, criminal forensic analysis, gene prediction, genetic system and protein analysis. Different types of distributed algorithms for the search and identification for DNA segments and repeat pattern in a given DNA sequence are developed. The search algorithm was developed to compute the number of DNA sequence which contains the same consecutive types of DNA segments. A distributed subsequence identifications algorithm was designed and implemented to detect the segment containing DNA sequences. Sequential and distributed implementation of these algorithms was executed with different length of search segments patterns and genetic sequences. OPTSDNA algorithm is used for storing various sizes of DNA sequence into database. DNA sequences of different lengths were tested by using this algorithm. These input DNA sequences varied in size from very small to very large. The performance of search technique distributed system is compared with sequential approach.

References

12 Cites in Article
  1. C Sheel,M Khan,M Sarker,T Alam (2013). Algorithm for Optimal Storage of a Distributed Bioinformatics System for Analysis of DNA Sequences.
  2. R Kumar,A Kumar,S Agarwal (2007). A Distributed bioinformatics Computing System for Analysis of DNA Sequences.
  3. Andreas Baxevanis,B Ouellette (2001). Bioinformatics: A Practical Guide to the Analysis of Genes and Proteins.
  4. Richard Durban,S Eddy,A Krogh,G Mitchison (1998). Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids.
  5. Dan Gusfield (1997). Algorithms On Strings, Trees, and Sequences: Computer Science and Computational Biology.
  6. E Petroutsos (2006). Mastering Visual Basic.
  7. R Mistry (2006). Microsoft SQL Server 2008 Management and Administration.
  8. Uzi Vishkin (1985). Optimal parallel pattern matching in strings.
  9. C Huang (2003). Parallel Pattern Identification in Biological Sequences on Clusters.
  10. Strumpen (1995). Coupling Hundreds of Workstations for Parallel Molecular Sequence Analysis.
  11. Chintalapati Janaki,Rajendra Joshi (2003). Accelerating Comparative Genomics Using Parallel Computing.
  12. Mohammad Khan,Chotan Sheel (2013). OPTSDNA: Performance evaluation of an efficient distributed bioinformatics system for DNA sequence analysis.

Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Chotan Sheel. 2014. \u201cDistributed Bioinformatics Computing System for DNA Sequence Analysis\u201d. Global Journal of Computer Science and Technology - A: Hardware & Computation GJCST-A Volume 14 (GJCST Volume 14 Issue A1): .

Download Citation

Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Version of record

v1.2

Issue date

May 18, 2014

Language
en
Experiance in AR

Explore published articles in an immersive Augmented Reality environment. Our platform converts research papers into interactive 3D books, allowing readers to view and interact with content using AR and VR compatible devices.

Read in 3D

Your published article is automatically converted into a realistic 3D book. Flip through pages and read research papers in a more engaging and interactive format.

Article Matrices
Total Views: 9177
Total Downloads: 2308
2026 Trends
Related Research

Published Article

This paper provides an effective design of computing technique of a distributed bioinformatics computing system for analysis of DNA sequences using OPTSDNA algorithm. This system could be used for disease detection, criminal forensic analysis, gene prediction, genetic system and protein analysis. Different types of distributed algorithms for the search and identification for DNA segments and repeat pattern in a given DNA sequence are developed. The search algorithm was developed to compute the number of DNA sequence which contains the same consecutive types of DNA segments. A distributed subsequence identifications algorithm was designed and implemented to detect the segment containing DNA sequences. Sequential and distributed implementation of these algorithms was executed with different length of search segments patterns and genetic sequences. OPTSDNA algorithm is used for storing various sizes of DNA sequence into database. DNA sequences of different lengths were tested by using this algorithm. These input DNA sequences varied in size from very small to very large. The performance of search technique distributed system is compared with sequential approach.

Our website is actively being updated, and changes may occur frequently. Please clear your browser cache if needed. For feedback or error reporting, please email [email protected]

Request Access

Please fill out the form below to request access to this research paper. Your request will be reviewed by the editorial or author team.
X

Quote and Order Details

Contact Person

Invoice Address

Notes or Comments

This is the heading

Lorem ipsum dolor sit amet, consectetur adipiscing elit. Ut elit tellus, luctus nec ullamcorper mattis, pulvinar dapibus leo.

High-quality academic research articles on global topics and journals.

Distributed Bioinformatics Computing System for DNA Sequence Analysis

Dr. Mohammad Ibrahim Khan
Dr. Mohammad Ibrahim Khan
Dr. Kaushik Deb
Dr. Kaushik Deb Chittagong University of Engineering & Technology
Chotan Sheel
Chotan Sheel Chittagong University of Engineering & Technology

Research Journals