Prediction of photolysis half-lives of dihydroindolizines by genetic algorithm-multiple linear regression (GA-MLR)

Beiknejad, Davoud; Chaichi, Mohammad Javad; Fatemi, M.

doi:10.1002/poc.3540

Cited by 4 publications

(2 citation statements)

References 51 publications

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“…By changing the method of neighborhood clustering in the improved algorithm in the process of experiment 171 verification method using neighborhood linear decreasing, can increase the calculation efficiency, this research will decrease to 4 from the 12 linear neighborhood [10].…”

Section: Methodsmentioning

confidence: 98%

Single Nucleotide Polymorphisms Data Analysis using Improved Ant Colony Algorithm

Zheng¹,

Zhuo²

2017

Proceedings of the 2017 7th International Conference on Education, Management, Computer and Society (EMCS 2017)

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Abstract. Improved classical ant colony clustering algorithm (LF algorithm), applied to salt sensitive hypertension SNPs data analysis, in order to explore the high throughput SNPs statistical analysis to provide new ideas. The LF algorithm was improved, and the improved algorithm was programmed with Mat 1ab8.0 software. The cluster analysis was performed on 335 samples of salt sensitive hypertension. The LF algorithm was successfully improved and the software interface was realized. Using the new algorithm, all samples are divided into 2 categories, the first class of 169 samples, second of 166 samples of consistency test and latent class analysis results, the Kappa value is 0.93, P<0.001, and the two kinds of differences in population SNPs probability distribution statistical test, we selected 3 SNPs:rs848307, rs1739843, rs1010069, clear it plays an important role in the classification of. Conclusion: ant colony clustering algorithm has the characteristics of unique thinking, automatic calculation, easy to improve, etc. it has broad application prospects in the field of high throughput SNPs data analysis and other related fields of genomics.

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Section: Methodsmentioning

confidence: 98%

Single Nucleotide Polymorphisms Data Analysis using Improved Ant Colony Algorithm

Zheng¹,

Zhuo²

2017

Proceedings of the 2017 7th International Conference on Education, Management, Computer and Society (EMCS 2017)

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“…In order to find out the optimal chromosome hidden in optimal chromosome under, through repeated use of genetic algorithms, the multiple optimization results and obtain a set of candidate features with frequency of SNP (Candidate SNP CSNP), according to the characteristics of SNP need to select a certain frequency, for the second phase of the research use. The author proposed multiple genetic algorithm based on mutual information (MGA) [9] to get a small number of CSNP collection, this collection as much as possible to remove the disease and unrelated to SNP, at the same time as much as possible to retain the true disease associated with SNP (GroundTruthSNP, GTSNP), to reduce the scale of SNP set objective. In the same way as the author's work, Miller proposes a method of finding the characteristic SNP set with the maximum entropy method (ME) [10] under certain constraints.…”

Section: Introductionmentioning

confidence: 99%

Feature Selection for Single Nucleotide Polymorphisms using Parallal Genetic Algorithm

Zheng¹,

Zhuo²

2017

Proceedings of the 2017 7th International Conference on Education, Management, Computer and Society (EMCS 2017)

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Abstract. The application of statistical machine learning methods to study the association between large scale single nucleotide polymorphism (SNP) and complex diseases is facing the "Curse of dimensionality". The first task is to reduce the large scale SNP to smaller sets. For this reason, a multiple genetic algorithm is proposed for feature selection of single nucleotide polymorphism. For the first time, a new method is proposed to measure the degree of association between SNP and disease by mutual information, and as the fitness value of genetic algorithm (GA), the candidate feature SNP set is obtained by the use of genetic algorithm. In the SNP experiment on simulation data and the maximum entropy (ME) method for performance comparison shows that, this method can reduce the SNP collection and disease related SNP, while retaining the disease associated with SNP, SNP provides data for further research on the suitable scale, this method can be used in medium or large scale SNP set.

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QSAR model of photolysis kinetic parameters in aquatic environment

He,

Wang

2023

QSAR in Safety Evaluation and Risk Assessment

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Prediction of photolysis half-lives of dihydroindolizines by genetic algorithm-multiple linear regression (GA-MLR)

Cited by 4 publications

References 51 publications

Single Nucleotide Polymorphisms Data Analysis using Improved Ant Colony Algorithm

Single Nucleotide Polymorphisms Data Analysis using Improved Ant Colony Algorithm

Feature Selection for Single Nucleotide Polymorphisms using Parallal Genetic Algorithm

QSAR model of photolysis kinetic parameters in aquatic environment

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