Name
Abstract | ||
|---|---|---|
Multiplex Polymerase Chain Reaction (PCR) experiments are used for amplifying several segments of the target DNA simultaneously and thereby to conserve template DNA, reduce the experimental time, and minimize the experimental expense. The success of the experiment is dependent on primer design. However, this can be a dreary task as there are many constrains such as melting temperatures, primer length, GC content and complementarity that need to be optimized to obtain a good PCR product. Motivated by the lack of primer design tools for multiplex PCR genotypic assay, we propose a multiplex PCR primer design tool using a genetic algorithm, which is a stochastic approach based on the concept of biological evolution, biological genetics and genetic operations on chromosomes, to find an optimal selection of primer pairs for multiplex PCR experiments. The presented experimental results indicate that the proposed algorithm is capable of finding a series of primer pairs that obeies the design properties in the same tube. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1145/1068009.1068087 | Genetic and Evolutionary Computation Conference |
Keywords | Field | DocType |
Polymerase Chain Reaction,Genetic Algorithm,Target Region,Prime Design,Mutation Operator | Genotype,Multiplex polymerase chain reaction,Computer science,Artificial intelligence,Computational biology,Genetic algorithm,In silico PCR,Polymerase chain reaction,Design tool,Primer (molecular biology),GC-content,Bioinformatics,Machine learning | Conference |
Volume | Issue | ISSN |
11 | 9 | 1432-7643 |
ISBN | Citations | PageRank |
1-59593-010-8 | 1 | 0.37 |
References | Authors | |
2 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Feng-Mao Lin | 1 | 237 | 15.34 |
| Hsien-Da Huang | 2 | 835 | 63.83 |
| His-Yuan Huang | 3 | 1 | 0.37 |
| Jorng-Tzong Horng | 4 | 541 | 67.78 |