Microsatellite Finder algorithm with High Memory Efficiency for Even Super Long Sequences

Abstract

An important issue in bioinformatics is to identify microsatellites that are a type of tandem repeats in genomic sequences. Changes in the number of repetitions of microsatellites can cause many diseases including Huntington’s and cancer. Therefore, identifying microsatellites in organisms’ genome in order to diagnose diseases and advise a treatment method is of the utmost importance. Many algorithms and tools have been developed to identify these sequences. Considering the importance of the application any improvement in accuracy, speed, and memory utilization can have a positive effect on the quality of human lives. The study proposes an algorithm that has a constant memory consumption that is independent of the input-size. Thus, its main memory consumption is significantly lower than the existing methods, while having a very high processing speed. In the end, this algorithm is implemented and the resulting tool which is named Memory Efficient Microsatellite Finder (MEMF) is compared to the state of the art tools available in terms of memory consumption and execution time. Its superiority is clear from the developed method and forms the comparison results.