A NEW AUTOMATA BASED APPROXIMATE STRING MATCHING APPROACH AND WEB INTERFACE FOR BIOINFORMATICS ALGORITHMS

Abstract

In this study, we present a new web interface for major bioinformatics algorithms andintroduce a novel approximate string matching algorithm. Our web interface executes major algorithmson the field for the use of computational biologists, students or any other interested researchers. In theweb interface, algorithms come under three sections: Sequence alignment, pattern matching and motiffinding. In each section, we introduce algorithms in order to find best fitting one for specific dataset andproblem. The interface introduces execution time, memory usage and context specific results ofalgorithms such as alignment score. The interface utilizes emerging open source languages and tools. Inorder to develop light and user-friendly interface, all parts of the interface coded with Python language.On the other hand, Django is used for web interface. Second contribution of the study is novel A-BOMalgorithm, which is designed for approximate pattern matching problem. The algorithm is approximatematching variation of Backward Oracle Matching. We compare our algorithm with popular approximatestring matching algorithms. Results denote that A-BOM introduces %30 to %80 short runtimeimprovement when compared to current approximate pattern matching algorithms on long patterns.