Published Date: 04 May 2012
Publisher: Proquest, Umi Dissertation Publishing
Original Languages: English
Format: Paperback::38 pages
ISBN10: 1248962834
ISBN13: 9781248962831
Publication City/Country: Charleston SC, United States
Dimension: 203x 254x 3mm::95g
Download Link: A Particle Swarm Optimization Algorithm for Finding DNA Sequence Motifs
A Particle Swarm Optimization Algorithm for Finding DNA Sequence Motifs epub. Particle Swarm Optimization for Finding RNA Secondary Structures Michael Geis Martin Middendorf Received: date / Accepted: date Abstract This paper proposes a Particle Swarm Optimization (PSO) algorithm called HelixPSO for flnding RNA secondary structures that have a low energy and are similar to the native structure. HelixPSO is compared to the recent This is a chronologically ordered list of metaphor-based metaheuristics and swarm intelligence For problems where finding the precise global optimum is less important than finding an acceptable local Particle swarm optimization (PSO) is a computational method that optimizes a problem "Cuckoo designs spring". Use the SimpleIsBeautiful algorithm basic local alignment search tool (BLAST) for sequence-based homology detection. SIC - a tool to detect short inverted segments in a biological sequence. Search short inverted segments (length 3 Bp to 5000 Bp) in a DNA sequence. SIRW - a web server for the Simple Indexing and Retrieval System that combines sequence motif After you have discovered similar sequences but the motif searching tools have failed to recognize your group of proteins you can use the following tools to create a list of potential motifs. The MEME Suite-Motif-based sequence analysis tools (National Biomedical Computation Resource, U.S.A.). N.B. EMD: an ensemble algorithm for discovering regulatory motifs in DNA sequences. BMC Bioinformatics20067:342 DOI: 10.1186/1471-2105-7-342. BioMed Central Page 1 of 13 (page number not for citation purposes) BMC Bioinformatics Research article Open Access EMD: an ensemble algorithm for discovering regulatory motifs in DNA sequences Jianjun Hu1, Yifeng D Keywords: DNA motif; optimisation; swarm intelligence; PSO; particle swarm optimisation. Reference to this paper should be made as follows: Lei, C. And Ruan, J. A new optimization algorithm which is named as WCC (World Competitive TF are categorized as a sequence of specific DNA binding factors that are of great Proposing a genetic algorithm for the motif discovery based on the statistical Lei CW, Ruan JH,A particle swarm optimization algorithm for finding DNA sequence motifs, Proc. IEEE Bioinformatics and Biomedicine Workshops, pp. 166 173, 2008. Google Scholar; 8. Lee ZJ, Su SF, Chuang CC, Liu KH,Genetic algorithm with ant colony optimization (GA-ACO) for multiple sequence alignment, Appl Soft Comput 8:55 78, 2008. COMPARISON OF GENETIC ALGORITHM AND PARTICLE SWARM OPTIMISATION Dr. Karl O. Jones Abstract:In recent years the area of Evolutionary Computation has come into its own. Two of the popular developed approaches are Genetic Algorithms and Particle Swarm Optimisation, both of which are used in optimisation problems. Since the two approaches are supposed to find Genetic-Algorithms and Particle-Swarm-Optimization both are population based heuristic search algorithm. Genetic algorithm creates new population as offspring in every generation through some genetic operations over parent population like: selecti DEVELOPMENT OF PARTICLE SWARM OPTIMIZATION BASED ALGORITHM FOR GRAPH PARTITIONING 6.1 Introduction From the review, it is studied that the min cut k partitioning problem is a fundamental partitioning problem and is NP hard also. Most of the existing partitioning algorithms are heuristic in nature and they try to find a reasonably good A Particle Swarm Optimization Algorithm for Finding DNA Sequence Motifs..Abstract. Discovering short DNA motifs from a set of co-regulated genes is an important step towards deciphering the complex gene regulatory networks and understanding gene functions. Despite significant improvement in the last decade, it still remains one of the most challenging Furthermore, high-dimensional FS problems such as finding a small set of biomarkers to We developed a combinatorial PSO algorithm, called COMB-PSO, that scales up to high-dimensional gene expression data while still A particle swarm optimization-based algorithm for finding gapped motifs. Lei Chengwei and Ruan Jianhua. Cite.BibTex; Full citation; Abstract
Abstract
Background
Identifying approximately repeated patterns, or motifs, in DNA sequences from a set of co-regulated genes is an important step towards deciphering the complex gene regulatory In this work, gene expression in autism spectrum disorder (ASD) is the amount of available data for discriminative motif discovery (DMD) [23, 24]. In addition, a new discrete form of the PSO, the DPSO algorithm, which is Complex Phenomena journal homepage: ified particle swarm optimization algorithm can be used to create a gallery of 2D algorithm combines the Bat algorithm and PSO algorithm. Fast nondominated straints into a fitness function to find a reliable solution. Different from above proposed algorithm for motif discovery in a set of DNA sequences is presented in Section 5. Also, this section reports experimental analysis on the proposed algorithm. Finally, section 6 concludes the paper. 2. Principles of formulations, only the best particle in the neiParticle Swarm Optimization [20] This paper presents a Linear-Particle Swarm Optimization (PSO) algorithm for discovering motifs in DNA sequences, and the strengths and weaknesses of using the Linear-PSO for discovering motifs Conclusions In this work, we have proposed a novel algorithm for finding DNA motifs based on Particle Swarm Optimization (PSO). Our contributions include a novel modification of the PSO update rule to allow discrete variables, a model to allow gapped motifs, and a simple method to ne-tune the motif when some sequences contain zero or multiple binding sites. Experimental I have used both algorithms for my problems and I can give you some insights. Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) both are very strong algorithm and both have their own advantages. If I wanted to root for GA I would hail a Discovering short DNA motifs from a set of co-regulated genes is an important step towards deciphering the complex gene regulatory networks and understandi A Particle Swarm Optimization algorithm for finding DNA sequence motifs - IEEE Conference Publication EPSO - Evolutionary Particle Swarm Optimization, a New Algorithm with Applications in Power Systems Vladimiro Miranda and Nuno Fonseca Abstract This paper presents a new optimization model EPSO, Evolutionary Particle Swarm Optimization, inspired in both Evolutionary Algorithms and in Particle Swarm Optimization algorithms. The fundamentals of A conceptual overview of gradient free optimization algorithms, part one of two. This video is part of an introductory optimization series. TRANSCRIPT: Hello, and welcome to Introduction To Keywords: Motif Finding, Particle Swarm Optimization (PSO), Swarm Intelligence (SI), Transcriptional Factor Binding Sites (TFBS), Planted Motifs. Possible only at the cost of exercising more 1. INTRODUCTION A gene is a segment of DNA that is the blueprint for protein.
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