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At least 577 records · Page 32Linked to original sources
PubMed2005

A variational Bayesian mixture modelling framework for cluster analysis of gene-expression data.

MOTIVATION: Accurate subcategorization of tumour types through gene-expression profiling requires analytical techniques that estimate the number of categories or clusters rigorously and reliably. Parametric mixture modelling provides a natural setting to address this problem. RESULTS: We compare a criterion for model selection that is derived from a variational Bayesian framework with a popular alternative based on the Bayesian information criterion. Using simulated data, we show that the variational Bayesian method is more accurate in finding the true number of clusters in situations that are relevant to current and future microarray studies. We also compare the two criteria using freely available tumour microarray datasets and show that the variational Bayesian method is more sensitive to capturing biologically relevant structure.

Algorithms↗
PubMed1993

Multivariate cluster analysis of the MMPI-2 in chronic low-back pain patients.

OBJECTIVE: The purpose of our study was to investigate whether Minnesota Multiphasic Personality Inventory-2 cluster solutions of chronic low-back pain patients would replicate those found in previous research with the Minnesota Multiphasic Personality Inventory. SETTING: A multidisciplinary pain clinic in the southeastern United States. PATIENTS: The subjects were 201 chronic low-back pain patients who had suffered a work-related back injury. OUTCOME MEASURES: The Minnesota Multiphasic Personality Inventory-2. RESULTS: We found four relatively homogeneous subgroups of chronic low-back pain patients that were similar to those identified by previous researchers using data collected with the Minnesota Multiphasic Personality Inventory. CONCLUSION: These findings indicate that interpretations of the Minnesota Multiphasic Personality Inventory-2 should parallel those of the Minnesota Multiphasic Personality Inventory for chronic low-back pain patients. They further suggest that the results of Minnesota Multiphasic Personality Inventory-based studies are also applicable to Minnesota Multiphasic Personality Inventory-2.

Adult↗
PubMed1994

A cluster analysis of Basic Personality Inventory (BPI) adolescent profiles.

Basic Personality Inventory profiles of 95 male and 118 female adolescent admissions to a crisis intervention unit were subjected to a cluster analytic procedure. For both males and females, four subgroups were identified: Mental Health Maladjustment, Interpersonal Maladjustment, High-risk Rebellion, and Adjustment. Subgroups differed significantly on alternative markers of psychopathology (SCL-90-R and Diagnoses). Subgroups identified were consistent with groupings identified previously. The subgroups also corresponded with broad-band syndromes that are conventional within the literature on adolescent psychopathology. Subgroup characteristics and implications for adolescent assessment are discussed.

Adolescent↗
PubMed1994

Summary of first round cluster analysis: complete antibody panel.

The reactivities of 141 monoclonal antibodies (mAbs) with 60 target cell types or lines were analysed by flow cytometry and the data subjected to statistical clustering. mAbs were assigned to 23 clusters by statistical similarity and information on specificity supplied by the contributor. Clustered mAbs were examined in more detail in the second round of workshop analyses.

Animals↗
PubMed2002

Genesis: cluster analysis of microarray data.

A versatile, platform independent and easy to use Java suite for large-scale gene expression analysis was developed. Genesis integrates various tools for microarray data analysis such as filters, normalization and visualization tools, distance measures as well as common clustering algorithms including hierarchical clustering, self-organizing maps, k-means, principal component analysis, and support vector machines. The results of the clustering are transparent across all implemented methods and enable the analysis of the outcome of different algorithms and parameters. Additionally, mapping of gene expression data onto chromosomal sequences was implemented to enhance promoter analysis and investigation of transcriptional control mechanisms.

Algorithms↗
PubMed2004

Drinking patterns in French adult men--a cluster analysis of alcoholic beverages and relationship with lifestyle.

BACKGROUND: Establishing patterns of alcohol consumption may be useful for investigating the relationship between alcohol and diseases. METHODS: We used a hierarchical agglomerative clustering method to describe the intake of eight types of alcoholic beverages and to determine drinking patterns in a cohort of 1797 men enrolled in a French 8-year intervention study involving nutritional doses of vitamins and minerals, the SU.VI.MAX study. RESULTS: Cluster 1, referred to as 'abstainers', was defined a priori and included 329 men who drank less than 5 g of alcohol per day. Six drinking patterns were defined in alcohol drinkers, with increasing mean alcohol intake: cluster 2, 'low drinkers', included 670 subjects, who drank little of any type of alcoholic beverage; cluster 3, 'high quality wines', included 584 men with a high intake of champagne, high quality wines, and high-alcohol aperitifs; cluster 4, 'beer and cider', included 190 subjects with a high intake of beer and cider; cluster 5, 'digestives', included 54 men with a specifically high consumption of digestive beverages; cluster 6, 'local wines', included 238 subjects with a high intake of local wines and low-alcohol aperitifs; cluster 7, 'table wines', included 61 men with a high intake of table wines and high-alcohol aperitifs. These clusters were significantly associated with socioeconomic and lifestyle variables such as place of residence, occupation, mean caloric intake and distribution of energy intake throughout the day, body mass index, and smoking habits. CONCLUSIONS: They will be useful in future studies of the relationship between alcohol intake and medical conditions or risk factors.

Alcohol Drinking↗
PubMed2006

Classification of projection neurons and interneurons in the rat lateral amygdala based upon cluster analysis.

Neurons in the rat lateral amygdala in situ were classified based upon electrophysiological and molecular parameters, as studied by patch-clamp, single-cell RT-PCR and unsupervised cluster analyses. Projection neurons (class I) were characterized by low firing rates, frequency adaptation and expression of the vesicular glutamate transporter (VGLUT1). Two classes were distinguished based upon electrotonic properties and the presence (IB) or absence (IA) of vasointestinal peptide (VIP). Four classes of glutamate decarboxylase (GAD67) containing interneurons were encountered. Class III reflected "classical" interneurons, generating fast spikes with no frequency adaptation. Class II neurons generated fast spikes with early frequency adaptation and differed from class III by the presence of VIP and the relatively rare presence of neuropeptide Y (NPY) and somatostatin (SOM). Class IV and V were not clearly separated by molecular markers, but by membrane potential values and spike patterns. Morphologically, projection neurons were large, spiny cells, whereas the other neuronal classes displayed smaller somata and spine-sparse dendrites.

Amygdala↗
PubMed2006

RHD(T201R, F223V) cluster analysis in five different ethnic groups and serologic characterization of a new Ethiopian variant DARE, the DIII type 6, and the RHD(F223V).

BACKGROUND: The RHD phylogeny in humans shows four main clusters of which three are predominantly observed in (African) black persons. Each of the African clusters is characterized by specific amino acid substitutions relative to the Eurasian RHD allele. RH phylogeny defines the framework for identification of clinically relevant aberrant alleles. This study focuses on the weak D type 4 cluster (characterized by RHD(T201R, F223V) (602C>G 667T>G)) in five ethnic groups. STUDY DESIGN AND METHODS: A total of 1702 samples were screened for the presence of 602C>G and 667T>G by sequence-specific polymerase chain reaction (PCR-SSP). Eighty samples were assigned to the weak D type 4 cluster and were molecularly characterized by PCR-SSP and RHD sequencing. Antigens of aberrant alleles were characterized with monoclonal anti-D according to the 37-epitope model when possible. RESULTS: Five new aberrant alleles, DIII type 6, DIII type 7, DARE, RHD(T201R, F223V) (without 819G>A), and RHD(F223V), were identified and DIII type 6, DARE, and RHD(F223V) were serologically characterized with monoclonal anti-D. Both the DARE and RHD(F223V) showed epitope loss. It is postulated that the 1136C>T nucleotide substitution (characteristic for the DAU allele cluster) is present on the DVa(KOU) allele. CONCLUSION: Identification of the new variant alleles refines the phylogeny of RHD in humans. The proposed DVa(KOU) allele with 1136C>T (DVa(KOU)T379M) is probably caused by conversion of the DAU0 allele and the DVa(KOU) allele, forming a phylogenetic link between the DV allele and the DAU cluster. By describing the RHD(F223V) (602C>G) and RHD(T201R, F223V) (602C>G and 667T>G) alleles formal proof is given for the origin of the non-Eurasian cluster.

Amino Acid Substitution↗
PubMed2003

[Quick identification of scullcaps in different geographical origins using clustering analysis method and infrared fingerprint spectra].

Based on the infrared fingerprint spectra, scullcap samples from 15 geographical origins were clustered into 6 classes with principal component analysis. The classification was related to their geographical origins and weather. In the same class, chemical components of scullcaps are similar to each other, which can be considered as the criterion of evaluating the quality of scullcaps. 43 geographical origins were predicted with radial basis function, which was demonstrated to be a powerful ANN method in discrimination. The classes of scullcaps can be distinguished by the method. The method can be used to class and identify geographical origins of scullcaps. It is one of the methods in the quality control of traditional Chinese medicines.

Cluster Analysis↗
PubMed1991

[Studies on the strain differences of Schistosoma japonicum in the mainland of China. IV. Fuzzy cluster analysis on some biological characters of different isolates of Schistosoma japonicum].

In this paper, a computerized numerical systematics was used to analyse the 5 different isolates of Schistosoma japonicum in the mainland of China by means of fuzzy clustering method with 32 quantitative data of each isolate about the morphological and biological characters. A dendrogram of the 5 isolates of S. japonicum was constructed on the basis of similarity coefficients as shown. The phylogenetic relationships revealed by the present study show that the two isolates of Anhui and Hubei get together firstly in one group, then the isolates of both Yunnan and Guangxi gather in another group, while the Sichuan isolate is closely related to the group of Anhui-Hubei isolates, not to the Yunnan ones, although both Sichuan and Yunnan isolates were in the southwest China.

Animals↗
PubMed2006

Cluster analysis and gene expression profiles: a cDNA microarray system-based comparison between human dental pulp stem cells (hDPSCs) and human mesenchymal stem cells (hMSCs) for tissue engineering cell therapy.

We investigated gene expression patterns and functional classifications regarding the clusters of human dental pulp stem cells (hDPSCs) and human mesenchymal stem cells (hMSCs)--which possess a multipotent ability--because little is known about the precise moleculobiological clues by which these cells activate their differentiating ability or functionality to eventually form dentin and bone, respectively. We first verified the expressions of the alkaline phosphatase (ALP) gene, dentin matrix protein 1 (DMP-1), and dentinsialophosphoprotein (DSPP) by real-time reverse-transcriptase polymerase chain reaction (RT-PCR) and consequently discovered the high expressions of these genes. Total RNA was also followed by hybridization with a human microarray system consisting of 12,814 genes. Analyses of gene expression patterns indicated several genes which encode extracellular matrix components, cell adhesion molecules, growth factors, and transcription regulators. Functional and clustering analyses of differences in gene expression levels revealed cell signaling, cell communication, or cell metabolism. In the future, information on the gene expression patterns of hDPSCs and hMSCs might be useful in determining the detailed functional roles of the relevant genes and applicable to stem cell therapies, and these cells could also be used as multipotent cell sources for gene technology and tissue engineering technology.

Adult↗
PubMedDate not supplied

Cluster analysis of the codon use frequency of MHC genes from different species.

The relative synonymous codon use frequency of 135 MHC genes from four mammal species (Homo sapiens, Pan troglodyte, Macaca mulanta and Rattus norvegicus) is analyzed using a hierarchical cluster method. The result suggests that gene function is the dominant factor that determines codon usage bias, while species is a minor factor that determines further difference in codon usage bias for genes with similar functions. The conclusion may be useful in gene classification and gene function prediction.

Animals↗
PubMed1985

Cluster analysis to improve food classification within commodity groups.

Mathematical clustering algorithms were used to classify foods within dairy, grain, and fat commodity groups on the basis of nutrients with limited availability in the food supply as well as those posing a possible health risk due to excess consumption. The procedure overcomes the problem that has made objective and accurate grouping, i.e., dealing simultaneously with 10 or more nutrients, difficult. The clustering routine classifies foods on the basis of similar nutrient content for any number of food attributes and assigns a degree of association to each food to indicate its compositional similarity to a prototype food for the cluster group. Foods within dairy, grain, and fat commodity groups were clustered on the basis of similar content of vitamin B-6, calcium, iron, magnesium, folacin, zinc, and added sugar, fat, cholesterol, and sodium. Whole milk and natural cheese clustered together on the basis of their moderate nutrient and relatively high fat and sodium content. Whole wheat breads, pumpernickel bread, and pancakes from mix constituted a grain subgroup with highest nutrient content, lowest cholesterol and sugar, lower fat, and higher sodium. Other subgroups based upon similarities in attributes were identified within food commodity categories. The result is an expansion of some food groups to incorporate concepts of both nutritional adequacy and moderation of food components of current nutritional concern.

Dairy Products↗