Benchmark datasets for the DNA fragment assembly problem

Mallén-Fullerton, Guillermo M.; Hughes, James Alexander; Houghten, Sheridan; Fernández‐Anaya, Guillermo

doi:10.1504/ijbic.2013.058912

Cited by 19 publications

(18 citation statements)

References 34 publications

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“…Table 5, as proposed by Mallén-Fullerton et al [15], shows the benchmarks used by SDS for DNA assembly.…”

Section: Resultsmentioning

confidence: 99%

“…Some of the swarm intelligence and evolutionary algorithms, such as genetic algorithms and ant colony optimisation have been used for the fragment assembly problem focusing on the overlap, layout and consensus approach [15]. In 1995, Rebecca Parsons and Johnson created performance improvements for a genetic algorithm applied to the DNA sequence assembly problem [18].…”

Section: Dna Sequence Assembly and Swarm Intelligencementioning

confidence: 99%

“…The matrix is then used by other optimising algorithm to conduct the overlapping phase. The results of many of these algorithms are reported in [15].…”

Section: Sds Vs Smith-waterman Algorithm Imentioning

confidence: 99%

“…As in the previous set of experiments, an already commonly used dataset [15] is used. More details about the reason behind using SDS (instead of the commonly used Smith-Waterman algorithm) for generating the overlap score matrices are provided in Section 5.5.…”

Section: Generating Matrices Of Overlap Score By Sdsmentioning

confidence: 99%

“…In the dataset used [15] for the experiments reported, the file 'matrix conservative' contains matrices that store the overlap score amongst all fragments for each benchmark in the dataset. The overlap scores are computed by the Smith-Waterman algorithm.…”

Section: Sds Vs Smith-waterman Algorithm IImentioning

confidence: 99%

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Maximising Overlap Score in DNA Sequence Assembly Problem by Stochastic Diffusion Search

al-Rifaie

2016

Studies in Computational Intelligence

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This paper introduces a novel study on the performance of Stochastic Diffusion Search (SDS) -a swarm intelligence algorithm -to address DNA sequence assembly problem. This is an NP-hard problem and one of the primary problems in computational molecular biology that requires optimisation methodologies to reconstruct the original DNA sequence. In this work, SDS algorithm is adapted for this purpose and several experiments are run in order to evaluate the performance of the presented technique over several frequently used benchmarks. Given the promising results of the newly proposed algorithm and its success in assembling the input fragments, its behaviour is further analysed, thus shedding light on the process through which the algorithm conducts the task. Additionally, the algorithm is applied to overlap score matrices which are generated from the raw input fragments; the algorithm optimises the overlap score matrices to find better results. In these experiments realworld data are used and the performance of SDS is compared with several other algorithms which are used by other researchers in the field, thus demonstrating its weaknesses and strengths in the experiments presented in the paper.

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“…Table 5, as proposed by Mallén-Fullerton et al [15], shows the benchmarks used by SDS for DNA assembly.…”

Section: Resultsmentioning

confidence: 99%

Section: Dna Sequence Assembly and Swarm Intelligencementioning

confidence: 99%

“…The matrix is then used by other optimising algorithm to conduct the overlapping phase. The results of many of these algorithms are reported in [15].…”

Section: Sds Vs Smith-waterman Algorithm Imentioning

confidence: 99%

Section: Generating Matrices Of Overlap Score By Sdsmentioning

confidence: 99%

Section: Sds Vs Smith-waterman Algorithm IImentioning

confidence: 99%

See 3 more Smart Citations