title: A comparative analysis of multiple sequence alignments for biological data.
abstract: Multiple sequence alignment plays a key role in the computational analysis of biological data. Different programs are developed to analyze the sequence similarity. This paper highlights the algorithmic techniques of the most popular multiple sequence alignment programs. These programs are then evaluated on the basis of execution time and scalability. The overall performance of these programs is assessed to highlight their strengths and weaknesses with reference to their algorithmic techniques. In terms of overall alignment quality, T-Coffee and Mafft attain the highest average scores, whereas K-align has the minimum computation time.
authors.affiliation: Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, Saudi Arabia.
authors.forename: Umar
authors.initials: U
authors.lastname: Manzoor
authors.affiliation: Department of Computer Science, National University of Computer and Emerging Sciences, Islamabad, Pakistan.
authors.forename: Sarosh
authors.initials: S
authors.lastname: Shahid
authors.affiliation: Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, Saudi Arabia.
authors.forename: Bassam
authors.initials: B
authors.lastname: Zafar
mesh_terms: D000465:Algorithms; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D016415:Sequence Alignment / Q000379:methods*; D017421:Sequence Analysis / Q000379:methods*; D012984:Software
keywords: Multiple sequence alignment; clustalW; k-align; mafft; muscle; progressive alignment; t-coffee