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Dergiler / Middle East Journal of Science / 2021 / Cilt: 7 - Sayı: 2

THREE MSA TOOLS ANALYSIS in DNA and PROTEIN DATASETS

Fırat AŞIR
Tuğcan KORAK
Özgür ÖZTÜRK
Sayfa
89–99
DOI
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⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

Result show that for both protein and DNA dataset, MAFFT may be more useful among three of MSA tool used.

📌 3 Maddede Bu Makale

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Amaç & Hipotez:Multiple sequence alignment (MSA) is used to align three or more sequences of DNA, RNA and protein.
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Temel Bulgular & Veri:In this article three MSA tools; CLUSTALW, SAGA and MAFFT are used for five datasets BALiBASE_R9, DIRMBASE, SABmark and additionally constructed DNABali and ProteinBali for alignment.
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Sonuç & Katkı:Result show that for both protein and DNA dataset, MAFFT may be more useful among three of MSA tool used.
🔬Tür:Araştırma Makalesi
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:multiple sequence alignment · MAFFT · SAGA

Abstract

Multiple sequence alignment (MSA) is used to align three or more sequences of DNA, RNA and protein. It is prominent for constructing phylogenetic trees and evolutionary relationships between sequences with regard to similarities and dissimilarities. Variety of multiple sequence alignment tools are available online, each having different methods and parameters to align sequences. In this article three MSA tools; CLUSTALW, SAGA and MAFFT are used for five datasets BALiBASE_R9, DIRMBASE, SABmark and additionally constructed DNABali and ProteinBali for alignment. Result show that for both protein and DNA dataset, MAFFT may be more useful among three of MSA tool used.

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Bu Makaleye Atıf Yap

AŞIR, F., KORAK, T., ÖZTÜRK, Ö. (2021). THREE MSA TOOLS ANALYSIS in DNA and PROTEIN DATASETS. Middle East Journal of Science, Cilt: 7 - Sayı: 2, 89–99. https://ajindex.com/articles/401716

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Kaynakça (17)

  1. Notredame, C. “Recent Evolutions of Multiple Sequence Alignment Algorithms”, PLOS Computational Biology, 3(8), e123, 2007
  2. Edgar, R.C., Batzoglou, S. “Multiple sequence alignment”, Current opinion in structural biology, 16(3), 368-373, 2006
  3. Moretti, S., et al. “The M-Coffee web server: a meta-method for computing multiple sequence alignments by combining alternative alignment methods”, Nucleic Acids Research, 35(Web Server issue), W645-8, 2007
  4. Chowdhury, B., Garai, G. “A review on multiple sequence alignment from the perspective of genetic algorithm”, Genomics, 109(5), 419-431, 2017
  5. Edgar, R.C. “MUSCLE: a multiple sequence alignment method with reduced time and space complexity”, BMC Bioinformatics, 5, 113, 2004
  6. Kumar, S., Filipski, A. “Multiple sequence alignment: in pursuit of homologous DNA positions”, Genome Research, 17(2), 127-35, 2007
  7. Chatzou, M., et al. “Multiple sequence alignment modeling: methods and applications”, Briefings in Bioinformatics, 17(6), 1009-1023, 2016
  8. Bawono, P., et al. “Multiple Sequence Alignment”, Methods Mol Biol, 1525, 167-189, 2017
  9. Thompson, J.D. et al. “CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice”, Nucleic Acids Research, 22(22), 4673-80, 1994
  10. Notredame, C, Higgins, D.G. “SAGA: Sequence Alignment by Genetic Algorithm”, Nucleic Acids Research, 24(8), 1515-1524, 1996
  11. Katoh, K., et al. “MAFFT: a novel method for rapid multiple sequence alignment based on fast Fourier transform”, Nucleic Acids Research, 30(14), 3059-66, 2002
  12. Sievers, F., et al. “Fast, scalable generation of high-quality protein multiple sequence alignments using Clustal Omega”, Molecular Systems Biology, 7, 539, 2011
  13. Pei, J., Grishin, N.V. “MUMMALS: multiple sequence alignment improved by using hidden Markov models with local structural information”, Nucleic Acids Research, 34(16), 4364-4374, 2006
  14. Do, C.B., et al. “ProbCons: Probabilistic consistency-based multiple sequence alignment”, Genome Research, 15(2), 330-40, 2005
  15. Notredame, C., et al. “T-Coffee: A novel method for fast and accurate multiple sequence alignment”, Journal of Molecular Biology, 302(1), 205-17, 2000
  16. Morgenstern, B., et al. “DIALIGN: finding local similarities by multiple sequence alignment”, Bioinformatics, 14(3), 290-4, 1998
  17. Pei, J., et al. “PROMALS3D: a tool for multiple protein s