Multiobjective artificial fish swarm algorithm for multiple sequence alignment

Dabba, Ali; Tari, Abdelkamel; Zouache, Djaafar

doi:10.1080/03155986.2019.1629782

Cited by 8 publications

(6 citation statements)

References 37 publications

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“…A list of recent works on the sequence alignment problem is shown in Table 5. Most of them study a multiobjective version of the problem (Ortuno et al., 2013; Rubio‐Largo et al., 2015; Zhu et al., 2015a; Rani and Ramyachitra, 2016; Rubio‐Largo et al., 2016; Manikandan and Ramyachitra, 2017; Rubio‐Largo et al., 2018a; Dabba et al., 2019). Common measures of the objective functions are BAliscore scores, structural information, nongaps percentage, and number of totally conserved columns.…”

Section: String Problemsmentioning

confidence: 99%

On the role of metaheuristic optimization in bioinformatics

Calvet

Benito

Juan

et al. 2022

Int Trans Operational Res

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Metaheuristic algorithms are employed to solve complex and large-scale optimization problems in many different fields, from transportation and smart cities to finance. This paper discusses how metaheuristic algorithms are being applied to solve different optimization problems in the area of bioinformatics. While the text provides references to many optimization problems in the area, it focuses on those that have attracted more interest from the optimization community. Among the problems analyzed, the paper discusses in more detail the molecular docking problem, the protein structure prediction, phylogenetic inference, and different string problems. In addition, references to other relevant optimization problems are also given, including those related to medical imaging or gene selection for classification. From the previous analysis, the paper generates insights on research opportunities for the Operations Research and Computer Science communities in the field of bioinformatics.

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Section: String Problemsmentioning

confidence: 99%

On the role of metaheuristic optimization in bioinformatics

Calvet

Benito

Juan

et al. 2022

Int Trans Operational Res

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“…In this paper, under the public health events from 2019 to 2022, performing arts enterprises' support selection strategies are selected as samples to analyze the results of strategy selection. Strategic choices include economy, technology, politics, and so on [ 24 ]. The evaluation criteria of strategy selection refer to “National Measures for Supporting Performing Arts Enterprises” and “Standards for Supporting Performing Arts Enterprises.” There are five levels of strategy selection, which are completely consistent, partially consistent, average, nonconsistent, and completely nonconsistent.…”

Section: Case Analysis Of Supporting Strategy Choice Of Performing Ar...mentioning

confidence: 99%

Research on the Development Support Strategy of Cultural Enterprises Based on Fish Swarm Algorithm under the Background of Public Health

Hua

Ding

2022

Journal of Environmental and Public Health

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Under the background of public health events, the government needs to adopt reasonable support strategies to help cultural enterprises tide over the crisis. However, the original analytic hierarchy process cannot be comprehensive and accurate analysis, resulting in that the government support strategy cannot play a role. Fish swarm algorithm is a comprehensive intelligent algorithm, which can comprehensively analyze the factors affecting the formulation of supporting strategies for cultural enterprises, and has the advantages of simple operation and strong analysis ability. Under this background, this paper puts forward a fish swarm model; this method is a comprehensive intelligent analysis method, which can help the government find the best support strategy from the perspectives of politics, economy, and society. In order to verify the effectiveness of the fish school model, this paper uses MATLAB software for verification; the results show that, in the support strategy classification, selection accuracy, and selection time, fish school model is superior to the analytic hierarchy process. Therefore, the fish swarm model can help the government to better choose supporting policies and help cultural enterprises tide over the crisis and improve the accuracy of formulating supporting strategies for cultural enterprises.

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“…Another swarm intelligent based approach is proposed by inspired from the artificial fish algorithm. Dabba et al [12] proposed multi objective artificial fish swarm algorithm called MOAFS for solving MSA problem. Here, they proposed two fitness functions to maintain diversity in exploration and exploitation in the search space.…”

Section: Introductionmentioning

confidence: 99%

Solving multiple sequence alignment problems by using a swarm intelligent optimization based approach

Paruchuri

Kancharla²,

Dara³

2023

IJECE

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<span lang="EN-US">In this article, the alignment of multiple sequences is examined through swarm intelligence based an improved particle swarm optimization (PSO). A random heuristic technique for solving discrete optimization problems and realistic estimation was recently discovered in PSO. The PSO approach is a nature-inspired technique based on intelligence and swarm movement. Thus, each solution is encoded as “chromosomes” in the genetic algorithm (GA). Based on the optimization of the objective function, the fitness function is designed to maximize the suitable components of the sequence and reduce the unsuitable components of the sequence. The availability of a public benchmark data set such as the Bali base is seen as an assessment of the proposed system performance, with the potential for PSO to reveal problems in adapting to better performance. This proposed system is compared with few existing approaches such as deoxyribonucleic acid (DNA) or ribonucleic acid (RNA) alignment (DIALIGN), PILEUP8, hidden Markov model training (HMMT), rubber band technique-genetic algorithm (RBT-GA) and ML-PIMA. In many cases, the experimental results are well implemented in the proposed system compared to other existing approaches.</span>

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Multiobjective artificial fish swarm algorithm for multiple sequence alignment

Cited by 8 publications

References 37 publications

On the role of metaheuristic optimization in bioinformatics

On the role of metaheuristic optimization in bioinformatics

Research on the Development Support Strategy of Cultural Enterprises Based on Fish Swarm Algorithm under the Background of Public Health

Solving multiple sequence alignment problems by using a swarm intelligent optimization based approach

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