NDLI: Faster greedy algorithms for Multiple Degenerate Primer Selection

Content Provider	IEEE Xplore Digital Library
Author	Balla, S. Rajasekaran, S. Mandoiu, I.I.
Copyright Year	2008
Description	Author affiliation: Dept. of Comput. Sci. & Eng., Univ. of Connecticut, Storrs, CT (Rajasekaran, S.; Mandoiu, I.I.) \|\| Sloan-Kettering Cancer Center, Sloan-Kettering Inst., York Avenue, NY (Balla, S.)
Abstract	To achieve increased throughput, amplification of multiple DNA sequences is often performed using a single Polymerase Chain Reaction (PCR) called Multiplex PCR (MP-PCR). Successful MP-PCR requires efficient methods for selecting sets of synthetic oligonucleotides called primers that collectively amplify all DNA loci of interest. Since the potential for forming primer-dimer pairs and unintended amplification products increases with the number of primers, a common optimization objective is to minimize the number of primers required to amplify all targets. Significant reductions in the number of required primers can be achieved by using primers with degenerate bases, or degenerate primers. The problem of selecting the minimum number of degenerate primers that amplify a given set of loci, referred to as the Multiple Degenerate Primer Selection Problem (MDPSP) has received much attention from researchers in the past few years. Since several variants of the problem have been proved to be NP-Complete, research has focused on heuristic algorithms that perform well on real biological data. In this paper, we present two new greedy algorithms for MDPSP, analyze their time and space complexities and compare their performance on random and real biological data with that of two previously reported algorithms. Our results show that the execution time and memory requirement of proposed algorithms is less than of existing algorithms, thus enabling the processing of larger input sets. Also, the new algorithms eliminate the dependency of the previous algorithms on an empirical input parameter that affects the runtime and quality of output. The software is downloadable at http://www.engr.uconn.edu/ldrsub02005/software.html.
Starting Page	1
Ending Page	4
File Size	152714
Page Count	4
File Format	PDF
ISBN	9781424428441
DOI	10.1109/BIBE.2008.4696662
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-10-08
Publisher Place	Greece
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Greedy algorithms DNA Sequences Heuristic algorithms Algorithm design and analysis Runtime Throughput Polymers Performance analysis Cancer
Content Type	Text
Resource Type	Article

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