Paper Info
Title
Using Genetic Algorithm And Maximum Clique To Design Multiplex Pcr Primers For Sequential Deletion Applications
Abstract
Sequential deletion method is generally used to locate the functional domain of a protein. In contrast to the general Multiplex Polymerase Chain Reaction (MPCR) that requires multiple pairs of forward and reverse primers to extract the desired products, the MPCR for sequential deletion also needs multiple forward primers, which are clustered into several groups, but only a single compatible reverse primer in each corresponding group. In this study, a Genetic-Maximum-Clique (GMC) algorithm which combines the genetic algorithm for solving maximum clique problem is proposed to design the primers of MPCR. This algorithm obtains near-optimal primers that can be clustered in as few multiplex primer groups as possible for one PCR experiment. The results show that the algorithm can provide fewer groups for longer sequences. It is useful in assisting the researchers to design the primers for multiplex PCR experiments specific to sequential deletion applications. Furthermore, primers designed by the proposed GMC method has also been confirmed to be capable of covering the primers designed manually in previous investigations.
Year
DOI
Venue
2016
10.1504/IJDMB.2016.074686
INTERNATIONAL JOURNAL OF DATA MINING AND BIOINFORMATICS
Keywords
Field
DocType
multiplex PCR, polymerase chain reaction, sequential deletion applications, truncated mutant, genetic algorithm, maximum clique, PCR primer design, web service
In silico PCR,Polymerase chain reaction,Clique,Multiplex polymerase chain reaction,Computer science,Multiplex,Primer (molecular biology),Bioinformatics,Inverse polymerase chain reaction,Clique problem
Journal
Volume
Issue
ISSN
14
2
1748-5673
Citations 
PageRank 
References 
0
0.34
15
Authors
5
Name
Order
Citations
PageRank
Ren-Hao Pan1323.42
Rung-Ching Chen233137.37
Elong Lin341.15
Yung-Kuan Chan447633.67
Yung-fu Chen5173.59