Sequencing by hybridization: an enhanced crossover operator for a hybrid genetic algorithm

Brizuela, Carlos A.; González-Gurrola, Luis Carlos; Tchernykh, Andrei; Trystram, Denis

doi:10.1007/s10732-007-9014-6

Cited by 5 publications

(3 citation statements)

References 20 publications

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“…In second, third and fourth column correspond to the input and output spectrum of size 50, 70 and 90 individuals (the four nucleotide bases) respectively. Using the results of the computational experiments, the proposed method has been compared with the three other approaches: a tabu-search method described by J. Blazewicz et al [1], a hybrid genetic algorithm described by J. Blazewicz et al [7] and Sequencing by hybridization: an enhanced crossover operator for a hybrid genetic algorithm described by Carlos A. Brizuela et al [9]. Here we denote tabu and scatter search as TSS, sequencing by hybridization as SBH, and hybrid genetic algorithm as HGA.…”

Section: Resultsmentioning

confidence: 99%

“…System performs the crossover operation of chromosomes as described by Carlos A. Brizuela et al [9] must choose a pair of chromosomes from a population by the selection operation. After a pair of chromosomes has been chosen by the selection operation, the system randomly generates a value between zero and one and compares it with a predefined crossover rate [0, 1] determined by the user.…”

Section: Crossover Operationmentioning

confidence: 99%

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DNA Sequence Reconstruction Based On Genetic Algorithm

Islam

Shahriar

Shaheed

2008

MJCS

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It is becoming increasingly important to develop a novel INTRODUCTIONDNA molecule, the fundamental fabric of life carries the genetic instruction for making living organisms. The main role of DNA is the long-term storage of information and it is often compared to a set of blueprints, since DNA contains the instructions needed to construct other components of cells, such as proteins and RNA molecules. The DNA segments that carry this genetic information are called genes, but other DNA sequences have structural purposes, or are involved in regulating the use of this genetic information. Chemically, DNA is a long polymer of simple units called nucleotides, which are held together by a backbone made of alternating sugars and phosphate groups. Attached to each sugar is one of four types of molecules called bases. The bases are adenine (A), thymine (T), cytosine (C) and guanine (G). It is the sequence of these four bases along the backbone that encodes information. This information is read using the genetic code, which specifies the sequence of the amino acids within proteins. Within cells, DNA is organized into structures called chromosomes and the set of chromosomes within a cell make up a genome. These chromosomes are duplicated before the cells divide, in a process called DNA replication.In chemical laboratory methods of DNA sequencing, a long DNA strand is chopped into slices and then biochemical method is applied to detect the nucleotide sequence in a single fragment. Then these known fragments are used to form a superstring, which is almost the same as the original DNA strand. In 1994, Leonard Adleman used molecular tools to solve a hard computational problem [3]. Adleman used traveling salesperson problem to manipulate DNA sequence and this is the first solution of a mathematical problem with biological tools. In The limitations of the conventional DNA sequencing methods can be overcome in the hybridization technique with the help of genetic algorithm; where in a single biochemical experiment (using a DNA probe chip) is possible to know almost all the subsequences of a specified length, which are presented in the original sequence. S-M. Chen et al. presented the method to solve DNA sequence alignment using genetic algorithm [3]. Inspired from their paper we present a new method for DNA sequence reconstruction using genetic algorithm. We choose the right successor with the help of successor choice technique and the fitness function. This method also deals with the oligonucleotides with negative and positive errors. Through this method we also manage the duplication of oligonucleotides.

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Section: Resultsmentioning

confidence: 99%

Section: Crossover Operationmentioning

confidence: 99%

DNA Sequence Reconstruction Based On Genetic Algorithm

Islam

Shahriar

Shaheed

2008

MJCS

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“…The realization of NBAGA. Powell algorithm，as an operator，which is parallel with selection, crossover and variation, and embeds Powell algorithm into modified real-coded genetic algorithms [8]. And for every individual, it goes on Powell direction to accelerate the local search with a probability p powell .…”

Section: Components and Implementation Of Nbagamentioning

confidence: 99%

The Calibration on Nonlinear Single Return Period Storm Intensity Model Parameters by the New Blending Accelerating Genetic Algorithm

Ren

Lü

Zhou

2012

AMM

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Through improving the real-coded genetic algorithms and embedding the algorithm of accelerating the local search in the Powell direction and the operation of accelerating cycle, thereby it is constructed the New blend Accelerating Genetic Algorithm (hereinafter referred to as NBAGA). The applied examples of the calibration on nonlinear single return period storm intensity model parameters show that this method takes into account of the advantages of both the advantages of the improved real-coded genetic algorithms and the Powell Algorithm, therefore this method is an excellent nonlinear optimization method which can search the global optimal exact solutions quickly and in greater probability, as well as doing subtle search locally.

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Tabu search algorithm for DNA sequencing by hybridization with multiplicity information available

Kwarciak

Formanowicz

2014

Computers & Operations Research

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Sequencing by hybridization: an enhanced crossover operator for a hybrid genetic algorithm

Cited by 5 publications

References 20 publications

DNA Sequence Reconstruction Based On Genetic Algorithm

DNA Sequence Reconstruction Based On Genetic Algorithm

The Calibration on Nonlinear Single Return Period Storm Intensity Model Parameters by the New Blending Accelerating Genetic Algorithm

Tabu search algorithm for DNA sequencing by hybridization with multiplicity information available

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