Similarity Score Estimation and Gaps Trimming of Multiple Sequence Alignment for Phylogenetic Tree Analysis

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Kasikrit Damkliang Pichaya Tandayya Unisa Sangket Ekawat Pasomsub


Phylogenetic tree analysis is a process for finding the highest possible revolution tree history of an interested organism. The important step of the process is multiple sequences alignment (MSA) which is operated using any MSA tool that produces a result in blocks of the Phylip format. Bioinformaticians have to manually determine and trim gaps of the MSA blocks using relevant tools of a software package in the off-line mode. The data blocks need to be manually cut-and-pasted between these tools. This working steps tend to be error-prone and time consuming. In addition, improper algorithm selection for tree inferring without applying an MSA similarity score tends to generate the phylogenetic tree with low accuracy and also take much more time. In this work, we present a new practical approach for the phylogenetic tree analysis applying our enhancement for the similarity score estimation and gaps trimming of the MSA blocks. We propose \textit{in-silico} algorithms for automating the concerned similarity score estimation and gaps trimming, and deploy them as web services. We demonstrate the web services utilized by composing them into an integrated stateful WSDL workflow. Our case study datasets are a complete coding sequences (CDS) and sets of complete genome of Dengue Viruses - 2, fetched from the NCBI RefSeq nucleotide database. Our proposed algorithms have correctly returned results, verified and satisfied by our  bioinformaticians. Our distributions, user manuals and endpoints of the web services, and the open source programs are available at


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How to Cite
K. Damkliang, P. Tandayya, U. Sangket, and E. Pasomsub, “Similarity Score Estimation and Gaps Trimming of Multiple Sequence Alignment for Phylogenetic Tree Analysis”, ECTI Transactions on Computer and Information Technology (ECTI-CIT), vol. 11, no. 2, pp. 129-142, Nov. 2017.
Author Biographies

Kasikrit Damkliang, Prince of Songkla University

Kasikrit Damkliang received a BS degree in Computer Science in 2005 and an MEng degree in Computer Engineering in 2009 from Prince of Songkla University (PSU), Thailand. Currently, he is a lecturer in the Information and Communication Technology Programme (ICT), Faculty of Science, PSU and also a PhD student at the Department of Computer Engineering, Faculty of Engineering, PSU. His research interests include HPC, Web Service, Cloud Computing, Workflow Technology, and Bioinformatics.

Pichaya Tandayya, Prince of Songkla University

Pichaya Tandayya graduated in Electrical Engineering (Communications) from Prince of Songkla University (PSU) in Thailand in 1990. She obtained her Ph.D. in Computer Science in 2001 from the University of Manchester in the area of Distributed Interactive Simulation. Currently, she is an Assistant Professor working at the Department of Computer Engineering, PSU. Her current research works concern Parallel and Distributed Computing and Systems, and Assistive Technology.

Unisa Sangket, Prince of Songkla University

Unisa Sangket received the B.Sc., M.Sc. (Computer Science), and Ph.D. (Molecular Biology and Bioinformatics) degrees from Prince of Songkla University, Thailand, in 2002, 2006, and 2011, respectively. She is currently a lecturer at the Department of Molecular Biotechnology and Bioinformatics, Faculty of Science, Prince of Songkla University. Her main areas of research interest are variant, genome, and transcriptome analysis using bioinformatics tools.

Ekawat Pasomsub, Mahidol University

Ekawat Pasomsub graduated in Medical Technology in 2001 and obtained his Ph.D. in Clinical Pathology in 2010 from Mahidol University (MU), Thailand. Currently, he is a lecturer in Department of Pathology, Faculty of Medicine, Ramathibodi Hospital, MU. His current research works concern laboratory diagnosis for viruses, HIV drug resistance, genetic association study, and applications on next generation sequencing technology.


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