To illustrate the literature distribution, research power distribution, and research hotspots in the radiomics research by using knowledge mapping analysis, and to provide reference for relevant researchers.
 Methods: Bibliographies from literature regarding radiomics in Web of Science database were downloaded. BICOM 2.0.1 and SATI 3.2 were used to clean and caculate the frequency of publication year, journal, author, key word, and research institution. CiteSpace V4.4.R1 was used to build the knowledge map of scientific research collaboration network between countries/regions.Ucinet 6 was used to build the knowledge map of scientific research collaboration network between core authors and institutions. gCLUTO 1.0 was applied to construct high-frequency keywords bi-clustering map.
 Results: A total of 700 literature was screened. Since 2012 the number of publications has been growing rapidly year by year. The United States, China, and Netherlands were leaders in this field. There were 5 major scientific research institution cooperative groups and 10 major author cooperative groups. Eight research hotspots were clustered by using high-frequency key word bi-clustering analysis.
 Conclusion: Radiomics is a new field and develops very fast. More and more countries, research institutions, and researchers with multidisciplinary background are going to participate in this filed. New terminology and new methods are going to appear in the field.
China ; Cluster Analysis

Single-cell transcriptome sequencing (scRNA-seq) can resolve the expression characteristics of cells in tissues with single-cell precision, enabling researchers to quantify cellular heterogeneity within populations with higher resolution, revealing potentially heterogeneous cell populations and the dynamics of complex tissues. However, the presence of a large number of technical zeros in scRNA-seq data will have an impact on downstream analysis of cell clustering, differential genes, cell annotation, and pseudotime, hindering the discovery of meaningful biological signals. The main idea to solve this problem is to make use of the potential correlation between cells and genes, and to impute the technical zeros through the observed data. Based on this, this paper reviewed the basic methods of imputing technical zeros in the scRNA-seq data and discussed the advantages and disadvantages of the existing methods. Finally, recommendations and perspectives on the use and development of the method were provided.
Cluster Analysis ; Transcriptome

No abstract available.
Cluster Analysis* ; Humans ; Risk Factors*

No abstract available.
Blister* ; Cluster Analysis* ; Skin Diseases*

OBJECTIVETo analyze the spatial-temporal distribution of Hepatitis E (HEV) in Hunan province from 2006 to 2014.

METHODSData related to HEV cases in Hunan province from 2006 to 2014 were collected from the Infectious Diseases Reporting Information System in the formation System of Disease Prevention and Control of China. Based on ArcGIS (10.2) and SaTScan(version 9.1), spatial autocorrelation analysis and space-time clustering analysis were used to study the prevalence on HEV.

RESULTSA total of 7 124 HEV cases were reported with 3 deaths during this period. The average annual incidence rate was 1.22/10(5). Most of the cases were over 55 years old and the majority of them (54.15%) were farmers. The distribution of HEV showed differences on locations and the regions with high incidence seen in northern and western areas of Hunan. However the regions with low incidence appeared in central or southern parts of Hunan. Data from the global spatial autocorrelation analysis showed that there was space autocorrelation on the HEV incidence rates in counties (cities, districts) (Moran'I was positive,P<0.05). A total of 31 countries were found in the high-high region with most of the clusters located in northern and western Hunan. According to local indication of spatial autocorrelation analysis, 31 countries in high-high region all showed statistically significant differences (P<0.05). RESULTS from the space-time scan showed 7 space-time clustering areas, including those most likely in the western Hunan area (2012-2014); the secondary clusters in northern Hunan areas (2011-2014).

CONCLUSIONSSignificant cluster pattern was found in the distribution of HEV in Hunan province. Clusters found in northern and western of Hunan province were seen more than in other regions.

Adult ; Aged ; China ; epidemiology ; Cities ; Cluster Analysis ; Farmers ; statistics & numerical data ; Hepatitis E ; epidemiology ; Humans ; Incidence ; Middle Aged ; Prevalence ; Seroepidemiologic Studies ; Space-Time Clustering ; Spatial Analysis

DNA chips are becoming increasingly popular as a convenient way to perform vast amounts of experiments related to genes on a single chip. And the importance of analyzing the data that is provided by such DNA chips is becoming significant. A very important analysis on DNA chip data would be clustering genes to identify gene groups which have similar properties such as cancer. Clustering data for DNA chips usually deal with a large search space and has a very fuzzy characteristic. The Particle Swarm Optimization algorithm which was recently proposed is a very good candidate to solve such problems. In this paper, we propose a clustering mechanism that is based on the Particle Swarm Optimization algorithm. Our experiments show that the PSO-based clustering algorithm developed is efficient in terms of execution time for clustering DNA chip data, and thus be used to extract valuable information such as cancer related genes from DNA chip data with high cluster accuracy and in a timely manner.
Cluster Analysis ; DNA ; Oligonucleotide Array Sequence Analysis

OBJECTIVETo compare and appraise the quality of germplasm resource of Ophiopogon japonicus in Sichuan basin.

METHODAccording to the main contents and yield traits, 24 wild germplasm resources of O. japonicus from different areas of Sichuan basin were comprehensively compared by the SPSS 17.0 software with principal component analysis and cluster analysis.

RESULTThe six samples of Ziyang, Jianyang, Leshan, Yibin, Chongqing, Mianyang, their comprehensive evaluation value of quality were higher than the others, and the sample of Ziyang had the best quality, the sample of Dazhou had the least quality, the results of the cluster analysis to raw data were also shown a similar results as principal component analysis.

CONCLUSIONThe wild resources of O. japonicus in Sichuan basin is rich, there are much differences among their quality; the method, through principal component analysis to study the comprehensive evaluation of the O. japonicus quality, is reliability and the results of cluster analysis is also support the conclusions, it could be able to provide a reference to select high O. japonicus quality resources.

Cluster Analysis ; Ophiopogon ; chemistry ; Principal Component Analysis

For speech detection in Parkinson's patients, we proposed a method based on time-frequency domain gradient statistics to analyze speech disorders of Parkinson's patients. In this method, speech signal was first converted to time-frequency domain (time-frequency representation). In the process, the speech signal was divided into frames. Through calculation, each frame was Fourier transformed to obtain the energy spectrum, which was mapped to the image space for visualization. Secondly, deviations values of each energy data on time axis and frequency axis was counted. According to deviations values, the gradient statistical features were used to show the abrupt changes of energy value in different time-domains and frequency-domains. Finally, KNN classifier was applied to classify the extracted gradient statistical features. In this paper, experiments on different speech datasets of Parkinson's patients showed that the gradient statistical features extracted in this paper had stronger clustering in classification. Compared with the classification results based on traditional features and deep learning features, the gradient statistical features extracted in this paper were better in classification accuracy, specificity and sensitivity. The experimental results show that the gradient statistical features proposed in this paper are feasible in speech classification diagnosis of Parkinson's patients.
Cluster Analysis ; Humans ; Parkinson Disease/diagnosis* ; Speech

Tuberculosis (TB) is known as a disease that prone to spatial clustering. Recent development has seen a sharp rise in the number of epidemiologic studies employing Geographical Information System (GIS), particularly in identifying TB clusters and evidences of etiologic factors. The aim of this systematic review is to determine evidence of TB clustering, type of spatial analysis commonly used and the application of GIS in TB surveillance and control. A literature search of articles published in English language between 2000 and November 2015 was performed using MEDLINE and Science Direct using relevant search terms related to spatial analysis in studies of TB cluster. The search strategy was adapted and developed for each database using appropriate subject headings and keywords. The literature reviewed showed strong evidence of TB clustering occurred in high risk areas in both developed and developing countries. Spatial scan statistics were the most commonly used analysis and proved useful in TB surveillance through detection of outbreak, early warning and identifying area of increased TB transmission. Among others are targeted screening and assessment of TB program using GIS technology. However there were limitations on suitability of utilizing aggregated data such as national cencus that were pre-collected in explaining the present spatial distribution among population at risk. Spatial boundaries determined by zip code may be too large for metropolitan area or too small for country. Nevertheless, GIS is a powerful tool in aiding TB control and prevention in developing countries and should be used for real-time surveillance and decision making.
Tuberculosis cluster ; geographical information system ; spatial analysis

OBJECTIVETo explore the genetic evolutionary distance between plants by using karyotype parameters identification of medicinal plants.

METHODThe cluster analysis of karyotype resemblance-near coefficient and evolutionary distance was used for 6 Bupleurum species.

RESULTThe results showed that there were the biggest karyotype resemblance-near coefficient (0.9920) and the smallest evolutionary distance (D(e) = 0.0080) between B. scorzonerifolium and B. chinense, indicating the closest relationship, and the minimum karyotype resemblance-near coefficient (0.4794) and the maximum evolutionary distance (D(e) = 0.7352) between B. smityii and B. falcatum, indicating the most distant relationship.

CONCLUSIONKaryotype was an important parameter for identification of medicinal plants because karyotype was stabilized for species. The genetic distance between in 6 species of Bupleurum species was obtained by karyotype clustering analysis of karyotype resemblance-near coefficient. There was the bigger evolutionary distance between the species which had different chromosome number.

Bupleurum ; classification ; genetics ; Cluster Analysis ; Karyotype