An evolution based biosensor receptor DNA sequence generation algorithm.
A biosensor is composed of a bioreceptor, an associated recognition molecule, and a signal transducer that can selectively detect target substances for analysis. DNA based biosensors utilize receptor molecules that allow hybridization with the target analyte. However, most DNA biosensor research uses oligonucleotides as the target analytes and does not address the potential problems of real samples. The identification of recognition molecules suitable for real target analyte samples is an important step towards further development of DNA biosensors. This study examines the characteristics of DNA used as bioreceptors and proposes a hybrid evolution-based DNA sequence generating algorithm, based on DNA computing, to identify suitable DNA bioreceptor recognition molecules for stable hybridization with real target substances. The Traveling Salesman Problem (TSP) approach is applied in the proposed algorithm to evaluate the safety and fitness of the generated DNA sequences. This approach improves efficiency and stability for enhanced and variable-length DNA sequence generation and allows extension to generation of variable-length DNA sequences with diverse receptor recognition requirements.
Advanced Graduate Education Center for Electronics of Jeonbuk and Information Technology-BK21, Jeonju, Jeonbuk, 561-756, Korea. rotnrwk@kongju.ac.kr
Eungyeong
E
Kim
Malrey
M
Lee
Thomas M
TM
Gatton
Jaewan
J
Lee
Yupeng
Y
Zang
D000465:Algorithms; D015374:Biosensing Techniques / Q000295:instrumentation*; D017076:Computer-Aided Design; D015342:DNA Probes / Q000032:analysis* / Q000235:genetics*; D004867:Equipment Design; D019544:Equipment Failure Analysis; D019143:Evolution, Molecular; D017422:Sequence Analysis, DNA / Q000295:instrumentation* / Q000379:methods*
D015342:DNA Probes