Supersonic mib

Bilal Wajid, Ali Riza Ekti, Amina Noor, Erchin Serpedin, Muhammad Naeem Ayyaz, Hazem Nounou, Mohamed Nounou

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

A novel assembly pipeline, MiB, employs Minimum Description Length (MDL), de-Bruijn graphs and Bayesian estimation for reference assisted assembly of the novel genome. In a previous study MiB assembly was compared with nine other assembly algorithms showing significant improvement in results coupled with very large execution times. This correspondence introduces 'Supersonic MiB', an extension to our previous study MiB. Supersonic MiB aims to stimulate the assembly pipeline of MiB showing significant improvement in execution time compared to its predecessor.

Original languageEnglish
Title of host publication2013 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2013 - Proceedings
PublisherIEEE Computer Society
Pages86-87
Number of pages2
ISBN (Print)9781479934621
DOIs
Publication statusPublished - 1 Jan 2013
Event2013 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2013 - Houston, TX, United States
Duration: 17 Nov 201319 Nov 2013

Publication series

NameProceedings - IEEE International Workshop on Genomic Signal Processing and Statistics
ISSN (Print)2150-3001
ISSN (Electronic)2150-301X

Other

Other2013 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2013
CountryUnited States
CityHouston, TX
Period17/11/1319/11/13

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ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology (miscellaneous)
  • Computational Theory and Mathematics
  • Signal Processing
  • Biomedical Engineering

Cite this

Wajid, B., Ekti, A. R., Noor, A., Serpedin, E., Naeem Ayyaz, M., Nounou, H., & Nounou, M. (2013). Supersonic mib. In 2013 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2013 - Proceedings (pp. 86-87). [6735941] (Proceedings - IEEE International Workshop on Genomic Signal Processing and Statistics). IEEE Computer Society. https://doi.org/10.1109/GENSIPS.2013.6735941