Genetic Data Clustering Based on Minimum Coding Length

[Objective] This paper aimed to provide a new method for genetic data clustering by analyzing the clustering effect of genetic data clustering algorithm based on the minimum coding length. [Method] The genetic data clustering was regarded as high dimensional mixed data clustering. After preprocessing genetic data, the dimensions of the genetic data were reduced by principal component analysis, when genetic data presented Gaussian-like distribution. This distribution of genetic data could be clustered effectively through lossy data compression, which clustered the genes based on a simple clustering algorithm. This algorithm could achieve its best clustering result when the length of the codes of encoding clustered genes reached its minimum value. This algorithm and the traditional clustering algorithms were used to do the genetic data clustering of yeast and Arabidopsis, and the effectiveness of the algorithm was verified through genetic clustering internal evaluation and function evaluation. [Result] The clustering effect of the new algorithm in this study was superior to traditional clustering algorithms, and it also avoided the problems of subjective determination of clustering data and sensitiveness to initial clustering center. [Conclusion] This study provides a new clustering method for the genetic data clustering.

Optimizing combination of aircraft maintenance tasks by adaptive genetic algorithm based on cluster search

It is significant to combine multiple tasks into an optimal work package in decision-making of aircraft maintenance to reduce cost,so a cost rate model of combinatorial maintenance is an urgent need.However,the optimal combination under various constraints not only involves numerical calculations but also is an NP-hard combinatorial problem.To solve the problem,an adaptive genetic algorithm based on cluster search,which is divided into two phases,is put forward.In the first phase,according to the density,all individuals can be homogeneously scattered over the whole solution space through crossover and mutation and better individuals are collected as candidate cluster centres.In the second phase,the search is confined to the neighbourhood of some selected possible solutions to accurately solve with cluster radius decreasing slowly,meanwhile all clusters continuously move to better regions until all the peaks in the question space is searched.This algorithm can efficiently solve the combination problem.Taking the optimization on decision-making of aircraft maintenance by the algorithm for an example,maintenance which combines multiple parts or tasks can significantly enhance economic benefit when the halt cost is rather high.

Genetic diversity analysis of Lepidium sativum(Chandrasur) using inter simple sequence repeat(ISSR) markers

Lepidium sativum（commonly known as garden cress） belongs to the family Brassicaceae. It is a fastgrowing erect, annual herbaceous plant. Its seeds possess significant fracture healing, anti-asthmatic, anti-diabetic,hypoglycemic, nephrocurative and nephroprotective activities. In the present study, we assessed the genetic diversity of various genotypes of L. sativum using inter-simple sequence repeat（ISSR） markers. Out of 41 ISSR primers screened, 32 primers showed significant, clear and reproducible bands. A total of 510 amplified bands were obtained using 32 ISSR primers, out of which 422 bands were polymorphic and 88 bands were monomorphic. The percentage of polymorphism was found to be 82. A total of 35 unique alleles ranging insize from 200 to 2,900 bp were observed.Cluster analysis based on unweighted pair-group method,arithmetic mean divided the 18 genotypes into two main clusters, with the first having only HCS-08 genotype of L.sativum and other having all of the other 17 genotypes. The Jaccard similarity coefficient revealed a broad range32–72 % genetic relatedness among the 18 genotypes.

Assessment of genetic diversity by simple sequence repeat markers among forty elite varieties in the germplasm for malting barley breeding

The genetic diversity and relationship among 40 elite barley varieties were analyzed based on simple sequence repeat （SSR） genotyping data. The amplified fragments from SSR primers were highly polymorphic in the badey accessions investigated. A total of 85 alleles were detected at 35 SSR loci, and allelic variations existed at 29 SSR loci. The allele number per locus ranged from 1 to 5 with an average of 2.4 alleles per locus detected from the 40 badey accessions. A cluster analysis based on the genetic similarity coefficients was conducted and the 40 varieties were classified into two groups. Seven malting barley varieties from China fell into the same subgroup. It was found that the genetic diversity within the Chinese malting barley varieties was narrower than that in other barley germplasm sources, suggesting the importance and feasibility of introducing elite genotypes from different origins for malting barley breeding in China.

Genetic climatic regionalization of the Balkan Peninsula using cluster analysis

Sea Level Pressure（SLP） data for the period 1950–2012 at 61 stations located in or around the Balkan Peninsula was used. The main concept is that intra-annual course of SLP represents the best different air masses that are situated over the Balkan Peninsula during the year. The method for differentiation of climatic zones is cluster analysis. A hierarchical clustering technique–average linkage between groups with Pearson correlation for measurement of intervals was employed in the research. The climate of the Balkan Peninsula is transitional between oceanic and continental and also between subtropical and temperate climates. Several major changes in atmospheric circulation over the Balkan Peninsula have happened over the period 1950–2012. There is a serious increase of the influence of the Azores High in the period January–Marchwhich leads to an increase of SLP and enhances oceanic influence. There is an increase of the influence of the north-west extension of the monsoonal low in the period June–September. This leads to more continental climatebut also to more tropical air masses over the Balkan Peninsula. Accordinglythe extent of subtropical climate widens in northern direction. There is an increase of the influence of the Siberian High in the period October–December. This influence covers central and eastern part of the peninsula in October and Novemberand it reaches western parts in December. Thusthe climate becomes more continental.