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International Multi-Conference on Artificial Intelligence Technology

M-CAIT 2013: Soft Computing Applications and Intelligent Systems pp 171–182Cite as

Detect Anchor Points by Using Shared Near Neighbors for Multiple Sequence Alignment

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 378))

Abstract

The Multiple sequence alignment (MSA) is a fundamental step for almost all aspects of biological sequence analysis. The reliability and accuracy of sequence analyses depend on the quality of MSA. Including anchor points into multiple sequence alignment to be aligned has been proved to be a good way to increase the quality of MSA. In this paper, we have applied Shared Near Neighbors method to construct the anchor points as partial alignment columns which will be aligned for final output. These anchor points can be used as guide with DIALIGN-TX method to overcome the limitation of DIALIGN-TX to increase the accuracy of final MSA. The results showed 4-8% improvement in the six reference sets in BAliBASE 3.0 benchmark regarding to CS score compared to DIALIGN-TX. In addition, it achieved the highest overall mean Q-score and CS score comparing to other MSA methods in IRMBASE 2.0 benchmark.

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Author information

Authors and Affiliations

  1. School of Computer Science, Universiti Sains Malaysia, Malaysia

    Aziz Nasser Boraik, Rosni Abdullah & Ibrahim Venkat

Authors
  1. Aziz Nasser Boraik
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  2. Rosni Abdullah
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  3. Ibrahim Venkat
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Editor information

Editors and Affiliations

  1. Faculty of Information Science & Technology, University Kebangsaan Malaysia, Bangi, Selangor, Malaysia

    Shahrul Azman Noah

  2. Center for Artificial Intelligence Technology (CAIT), Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia, 43600 UKM, Bangi, Selangor D. E, Malaysia

    Azizi Abdullah

  3. Universiti Kebangsaan Malaysia, 43600, Bangi, Selangor Darul Ehsan, Malaysia

    Haslina Arshad , Zulaiha Ali Othman  & Zalinda Othman ,  & 

  4. School of Computer Science, FTSM, Universiti Kebangsaan Malaysia, 43600, Bangi, Selangor Darul Ehsan, Malaysia

    Azuraliza Abu Bakar

  5. Pattern Recognition Research Group, CAIT, Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia, 43600, Bangi, Selangor, Malaysia

    Shahnorbanun Sahran

  6. Faculty of Information Science & IT, National University of Malaysia, 43600, Bangi, Selangor, Malaysia

    Nazlia Omar

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© 2013 Springer-Verlag Berlin Heidelberg

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Boraik, A.N., Abdullah, R., Venkat, I. (2013). Detect Anchor Points by Using Shared Near Neighbors for Multiple Sequence Alignment. In: Noah, S.A., et al. Soft Computing Applications and Intelligent Systems. M-CAIT 2013. Communications in Computer and Information Science, vol 378. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40567-9_15

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  • DOI: https://doi.org/10.1007/978-3-642-40567-9_15

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-40566-2

  • Online ISBN: 978-3-642-40567-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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