Abstract
Exponential growth of the biological data raises a fundamental problem for meaningful extraction of information from the huge GenBank databases. The Bioinformatics computational methods have been efficiently applied for extracting, searching, integrating and analyzing the biological data. In this paper, we propose an innovative extraction method, called Bio-BM, which uses the Boyer-Moore search algorithm to solve the problem of biological data selection and analysis. Experimental performance and evaluation process is utilized to compare the new Bio-BM method to the state-of-the-art biological search methods using the real benchmark datasets. The effectiveness and high-performance of the proposed method show more accurate results over the real biological datasets from GenBank.