PubMed Health⌕ Search

SEARCH · PubMed Health

Results for “cluster analysis”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 559 records · Page 31Linked to original sources
PubMed2001

A cluster analysis of patients with schizophrenia in community care.

In a sample of patients with schizophrenia, four clusters were identified and service use and relatives' satisfaction analyzed. In the first cluster, patients' severity of illness was mild and their use of services low. In the second, patients' disability was more severe; psychiatric symptoms were low in severity, family burden was moderate, and use of community services was more intensive. In the third cluster, patients had serious disability and severe positive symptoms; their families suffered distressing burdens, and their use of hospital and community services was intensive. In the fourth cluster, patients' disability was very severe, negative symptoms were prominent, and relatives' burden was moderate; use of hospital services was frequent, and use of community services was less so.

Adult↗
PubMed2004

Effects of total sleep-deprivation on waking human EEG: functional cluster analysis.

OBJECTIVE: The purpose of the present study was to investigate the effects of total sleep deprivation (TSD) on brain functions with an identification procedure for strongly interactive brain regions, relying on functional cluster (FC) analysis in multichannel electroencephalogram (EEG) data. METHODS: EEGs from 16 electrodes in 18 healthy, right-handed, young male volunteers were recorded before TSD (after normal sleep) and after 24 h of experimentally induced sleep deprivation. We estimated cluster index to characterize joint interactions among many brain regions in order to determine if a particular FC is present or not, and if so, its anatomy. RESULTS: As a result, we confirmed the presence of FC and found different FC patterns in both before and after TSD. The C3 and F7 locations were outside the cluster under the TSD condition, but belonged to the cluster with C4 and F8 before the TSD condition, and the F3/F4, and O1 locations were new entries to the functional cluster during sustained wakefulness. CONCLUSIONS: These results indicate that the neuronal activities of the C3 and F7 location are functionally unrelated, whereas the F3/F4 locations are functionally involved with the C4, F8, and O1 locations after 24 h TSD. Our results suggest that FC changes with elapsed awake time and reflects the change of brain function due to TSD. SIGNIFICANCE: This paper shows the existence of FC both before and after TSD, and the anatomy of each FC is different. So FC analysis would be a potential tool to investigate the simultaneous neuronal activity of human EEGs.

Adult↗
PubMed2004

Supervised cluster analysis for microarray data based on multivariate Gaussian mixture.

MOTIVATION: Grouping genes having similar expression patterns is called gene clustering, which has been proved to be a useful tool for extracting underlying biological information of gene expression data. Many clustering procedures have shown success in microarray gene clustering; most of them belong to the family of heuristic clustering algorithms. Model-based algorithms are alternative clustering algorithms, which are based on the assumption that the whole set of microarray data is a finite mixture of a certain type of distributions with different parameters. Application of the model-based algorithms to unsupervised clustering has been reported. Here, for the first time, we demonstrated the use of the model-based algorithm in supervised clustering of microarray data. RESULTS: We applied the proposed methods to real gene expression data and simulated data. We showed that the supervised model-based algorithm is superior over the unsupervised method and the support vector machines (SVM) method. AVAILABILITY: The program written in the SAS language implementing methods I-III in this report is available upon request. The software of SVMs is available in the website http://svm.sdsc.edu/cgi-bin/nph-SVMsubmit.cgi

Algorithms↗
PubMed1989

Complete nucleotide sequence of the rabbit beta-like globin gene cluster. Analysis of intergenic sequences and comparison with the human beta-like globin gene cluster.

The nucleotide sequence of the entire beta-like globin gene cluster of rabbits has been determined. This sequence of a continuous stretch of 44.5 x 10(3) base-pairs (bp) starts about 6 x 10(3) bp upstream from epsilon (the 5'-most gene) and ends about 12 x 10(3) bp downstream from beta (the 3'-most gene). Analysis of the sequence reveals that: (1) the sequence is relatively A + T rich (about 60%); (2) regions with high G + C content are associated with OcC repeats, a short interspersed repeated DNA in rabbits; (3) the distribution of polypurines, polypyrimidines and alternating purine/pyrimidine tracts is not random within the cluster; (4) most open reading frames are associated with known globin coding regions, OcC repeats or long interspersed repeats (L1 repeats); (5) the most prominent open reading frames are found in the L1 repeats; (6) different strand asymmetries in base composition are associated with embyronic and adult genes as well as the tandem L1 repeats at the 3' end of the cluster; and (7) essentially all the repeats appear to have been inserted by a transposon mechanism. A comparison of the sequence with itself by a dot-plot analysis has revealed nine new members of the OcC family of repeats in addition to the six previously reported. The OcC repeats tend to be clustered, particularly in the epsilon-gamma and gamma-psi delta intergenic regions. Dot-plot comparisons between the rabbit and the human clusters have revealed extensive sequence matches. Homology starts about 6 x 10(3) bp 5' to epsilon or as far upstream as the rabbit sequence is available. It continues throughout the entire cluster and stops about 0.7 x 10(3) bp 3' to beta, at which point several repeats have inserted in both rabbits and humans. Throughout the gene cluster, the homology is interrupted mainly by insertions or deletions in either the rabbit or the human genome. Almost all of the insertions are of known short or long repeated DNAs. The positions of the insertions are different in the two gene clusters, which indicates that both short and long repeats have been transposing throughout the genome for the time since the mammalian radiation. An alignment of rabbit and human sequences allows the calculation of the substitution rate around epsilon. Sequences far removed from the gene are evolving at a rate equivalent to the pseudogene rate, although some short regions show an apparently higher rate.(ABSTRACT TRUNCATED AT 400 WORDS)

Animals↗
PubMed2004

Biosynthesis of the angiogenesis inhibitor borrelidin by Streptomyces parvulus Tü4055: cluster analysis and assignment of functions.

The biosynthetic gene cluster for the angiogenesis inhibitor borrelidin has been cloned from Streptomyces parvulus Tü4055. Sequence analysis indicates that the macrolide ring of borrelidin is formed by a modular polyketide synthase (PKS) (borA1-A6), a result that was confirmed by disruption of borA3. The borrelidin PKS is striking because only seven rather than the nine modules expected for a nonaketide product are encoded by borA1-A6. The starter unit of the PKS has been verified as trans-cyclopentane-1,2-dicarboxylic acid (trans-1,2-CPDA), and the genes involved in its biosynthesis identified. Other genes responsible for biosynthesis of the nitrile moiety, regulation, and self-resistance were also identified.

Angiogenesis Inhibitors↗
PubMed1998

Are there subgroups within the autistic spectrum? A cluster analysis of a group of children with autistic spectrum disorders.

Comprehensive data on the developmental history and current behaviours of a large sample of high-functioning individuals with diagnoses of autism, Asperger's syndrome, or other related disorder were collected via parent interviews. This provided the basis for a taxonomic analysis to search for subgroups. Most participants also completed theory of mind tasks. Three clusters or subgroups were obtained; these differed on theory of mind performance and on verbal abilities. Although subgroups were identified which bore some relationship to clinical differentiation of autistic, Asperger syndrome, and Pervasive Developmental Disorder Not Otherwise Specified (PDD-NOS) cases, the nature of the differences between them appeared strongly related to ability variables. Examination of the kinds of behaviours that differentiated the groups suggested that a spectrum of autistic disorders on which children differ primarily in term of degrees of social and cognitive impairments could explain the findings.

Adolescent↗
PubMed2005

Early prediction of gross hemorrhagic transformation by noncontrast agent MRI cluster analysis after embolic stroke in rat.

BACKGROUND AND PURPOSE: Our goal was to develop magnetic resonance indices, without image contrast agent enhancement, that predict hemorrhagic transformation (HT) in a rat model of embolic stroke. METHODS: Male Wistar rats subjected to embolic stroke with (n=12) or without (n=10) the combination treatment with recombinant tissue plasminogen activator and an anti-platelet glycoprotein IIb/IIIa antibody 7E3 F(ab')2 initiated at 4 hours after onset of stroke were investigated using a 7-T MRI system. Radiofrequency saturation T1 (T1sat) maps with magnetization transfer, apparent diffusion coefficient of water (ADCw) maps in 3 directions, and T2 maps were measured at 2, 24, and 48 hours after embolization. MRI data were analyzed individually and using 2D cluster plots. Histological measurements were obtained at 48 hours. RESULTS: Gross hemorrhage was detected at 48 hours in 7 (4 control, 3 treated) of 22 animals. The 2D cluster plot using MRI T1sat and ADCw maps obtained at 2 hours after stroke predicted all gross HT. The location of gross hemorrhage predicted by the 2D cluster plot was within 0.75 mm of the identifying MRI cluster. CONCLUSIONS: The 2D MRI cluster plot analysis using T1sat and ADCw maps acquired at 2 hours after the onset of embolic stroke predicts gross HT.

Animals↗
PubMed1992

Cluster analysis of depressed college students' social behaviors.

Measures of interpersonal behaviors exhibited by depressed college students toward their dormitory roommates were cluster analyzed, and this procedure produced 2 relatively distinct subgroups: a dependent, friendly, overgenerous type and an autocratic, competitive, aggressive, mistrustful type. These 2 groups were studied over a 9-month period; findings revealed that behaviors associated with each cluster were relatively stable and unrelated to gender or initial symptom severity. In longitudinal analyses, depressives in one group showed symptom abatement across time, whereas symptoms of the other group remained elevated. The roommates of depressives exhibited relatively high levels of hostility and a progressive decline in social contact and satisfaction with their depressed cohabitant. The results are discussed in relation to other typological approaches to unipolar depression.

Cluster Analysis↗
PubMed2000

Cluster analysis, richness and biodiversity indexes derived from denaturing gradient gel electrophoresis fingerprints of bacterial communities demonstrate that traditional maize fermentations are driven by the transformation process.

The bacterial communities of maize fermented foods (pozol, poto-poto and ogi) from Mexico, Congo and Benin was compared using a culture-independent approach [denaturing gradient gel electrophoresis (DGGE) analysis of total DNA]. Foods produced following the same flow chart (i) grouped in distinct clusters, (ii) shared similar richness and biodiversity indexes and (iii) exhibited a high intra-specific variability. Structural biodiversity was higher in pozol samples, probably due to oxic conditions and higher initial pH. DGGE bands found in foods of different origins suggest that Lactobacillus plantarum, Lb. delbrueckii and Lb. fermentum are particularly well adapted to the fermentation of maize.

Benin↗
PubMedDate not supplied

Cluster analysis by testing the statistical hypothesis of uniformity.

This paper presents a cluster algorithm that defines the number of clusters and allows classification of data points. The basic task of the algorithm is to identify accumulations of vectors in the analysis sample of vectors. The accumulations of vectors are determined by testing the statistical hypothesis of uniformity. On the basis of accumulations, clusters are formed.

Algorithms↗
PubMed2004

Correcting the loss of cell-cycle synchrony in clustering analysis of microarray data using weights.

MOTIVATION: Due to the existence of the loss of synchrony in cell-cycle data sets, standard clustering methods (e.g. k-means), which group open reading frames (ORFs) based on similar expression levels, are deficient unless the temporal pattern of the expression levels of the ORFs is taken into account. METHODS: We propose to improve the performance of the k-means method by assigning a decreasing weight on its variable level and evaluating the 'weighted k-means' on a yeast cell-cycle data set. Protein complexes from a public website are used as biological benchmarks. To compare the k-means clusters with the structures of the protein complexes, we measure the agreement between these two ways of clustering via the adjusted Rand index. RESULTS: Our results show the time-decreasing weight function--exp[-(1/2)(t(2)/C(2))]--which we assign to the variable level of k-means, generally increases the agreement between protein complexes and k-means clusters when C is near the length of two cell cycles.

Algorithms↗
PubMed1998

[Clustering analysis of phonocardiagrams].

Through the development of the ART-2 neural network, we had constructed the 2-dimensional ART neural network appropriate for clustering the time-varying spectrums. After that, according to the character of phonocardiagram(PCG), we chose the scalogram of PCG to be the input feature of the network. By adjusting parameters the network was enabled to cluster the input PCGs to two clusters. The result demonstrates that the system we designed can pick out, from among 32 continuous PCGs, two PCGs which have the tendency toward abnormality. This result may be applicable to basic physiological studies and clinical diagnosis.

Cluster Analysis↗
PubMed2004

Iterative cluster analysis of protein interaction data.

MOTIVATION: Generation of fast tools of hierarchical clustering to be applied when distances among elements of a set are constrained, causing frequent distance ties, as happens in protein interaction data. RESULTS: We present in this work the program UVCLUSTER, that iteratively explores distance datasets using hierarchical clustering. Once the user selects a group of proteins, UVCLUSTER converts the set of primary distances among them (i.e. the minimum number of steps, or interactions, required to connect two proteins) into secondary distances that measure the strength of the connection between each pair of proteins when the interactions for all the proteins in the group are considered. We show that this novel strategy has advantages over conventional clustering methods to explore protein-protein interaction data. UVCLUSTER easily incorporates the information of the largest available interaction datasets to generate comprehensive primary distance tables. The versatility, simplicity of use and high speed of UVCLUSTER on standard personal computers suggest that it can be a benchmark analytical tool for interactome data analysis. AVAILABILITY: The program is available upon request from the authors, free for academic users. Additional information available at http://www.uv.es/genomica/UVCLUSTER.

Actins↗
PubMed2005

Cluster analysis and association study of structured multilocus genotype data.

We propose an algorithm for testing association using structured multilocus genotype data. The algorithm implements the clustering of the data by a hierarchical clustering technique and a k-means algorithm. After clustering, the program analyzes all the clusters together using the Mantel-Haenszel (MH) test, by which common associations in the clusters are examined. To use the MH test, the number of subpopulations has to be determined. A method of cross-validation (CV) and the k-means algorithm are applied for estimating the number of subpopulations. The algorithm described was implemented in the computer program POPSTRUCT. In the simulation study, we found that when the two groups with different marker allele frequencies were combined, an inflation of the type I errors was observed. The inflation was more marked when the differences in the marker allele frequencies were larger, the difference in the minor allele frequencies at the disease locus was larger, and the genotype relative risk associated with the disease locus was higher. Our simulation study indicated that the MH test was efficient for decreasing type I errors and increasing the power compared with any test performed on each cluster. Then, we compared the results of STRUCTURE, a model-based method, and POPSTRUCT, a distance-based method. When two subgroups with different allele frequencies were mixed together at a high fixed ratio, POPSTRUCT was superior to STRUCTURE in classifying the combined population into the accurate clusters, each of which reflects one of the original groups.

Algorithms↗
PubMed1990

Cluster analysis of acrylates to guide sampling for toxicity testing.

A set of 143 acrylates drawn from the TSCA inventory have been investigated for structurally defined clusters of compounds to simplify sampling for future toxicity screening. Each acrylate was represented by eight descriptors calculated from the molecular structure. Several standard clustering methods have been used to find five natural clusters of compounds. These five clusters are largely populated by compounds with similar chemical attributes with separate clusters formed for compounds with high absolute partial atomic charges, hydrophobic compounds, small compounds, halogenated compounds, and large or oligomeric compounds.

Acrylates↗
PubMed2004

[Clustering analysis and optimal cut-apart of arthropod community in megranate orchard].

Based on the principles of community ecology and by the method of fuzzy clustering, this paper studied the temporal and quantitative dynamics of the arthropod community and sub-community in megranate orchard, aimed to utilize natural enemy resources for pests control. The results showed that both of total community and natural enemy sub-community could be grouped into 4 clusters, and non-natural enemy sub-community could be grouped into 3 clusters. This clustering reflected the complexity of the community structure. The optimal cut-apart could divide the total community and sub-community into 3 stages, i. e., April-August, September-October, and November.

Animals↗