Abstract
Motif discovery is one of the most popular problems in molecular biology. There are many solutions provided by researchers. In this paper we have adopted the features of the Artificial beecolony algorithm (ABC) and designed a sequential algorithm to solve motif problem and named it MDABC. Artificial bee colony algorithm is a population based heuristic search technique used for optimization problem. We have performed experiments with the nucleotide sequences of homo sapiens (human) and mouse viz. CDRT4, MACF1, Zfa, TNFRSF19 and TICAM2. The ABC algorithm applied to the CDRT4, MACF1, Zfa, TNFRSF19 and TICAM2 DNA sequence for determining the motif of length 10, 20 and 30 using the maximum number of cycle (MCN) or the maximum number of generation is equal to 250, 500 and 1000. Our result shows a promising superior performance of the algorithm. As we will see, our results surpass the results obtained by other approaches proposed in the literature.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
