Disease relevance of Cluster Analysis

• A hierarchical cluster analysis was performed to determine whether groups of organs exhibited characteristic changes in their metastasis development index values in response to the three treatments given (i.e., rHuIL-1Ra, LPS, or rHuIL-1Ra plus LPS) [1].
• A hierarchical cluster analysis of the 128 genes revealed that a significant portion of genes demonstrate an opposing expression pattern, i.e. p53-activated genes are down-regulated in the breast tumor lines, whereas p53-repressed genes are up-regulated [2].
• Sequential extracellular matrix-focused and baited-global cluster analysis of serial transcriptomic profiles identifies candidate modulators of renal tubulointerstitial fibrosis in murine adriamycin-induced nephropathy [3].
• Biosynthesis of the angiogenesis inhibitor borrelidin by Streptomyces parvulus Tü4055: cluster analysis and assignment of functions [4].
• RESULTS: Cluster analysis revealed that hepatocellular adenoma displays a methylation profile much more similar to that found in normal liver tissue and focal nodular hyperplasia than to that found in hepatocellular carcinoma [5].

Psychiatry related information on Cluster Analysis

• A cluster analysis of California Verbal Learning Test performance classified patients into 3 subgroups [6].
• In this study, we used cluster analysis to identify MMPI profile types that predicted differential response to methadone maintenance treatment [7].
• Multistage cluster analyses with replications were used to sort score profiles of 252 methadone maintained men on 4 continuous measures of antisociality--childhood conduct disorder and adult antisocial personality disorder symptoms, the revised Psychopathy Checklist, and the Socialization scale of the California Psychological Inventory [8].

High impact information on Cluster Analysis

• A cluster analysis of these data demonstrates that genes induced by gamma radiation, UV radiation, and the zinc-induced p53 form distinct sets and subsets with a few genes in common to all these treatments [9].
• The GH data were analyzed using two distinct methods: a discrete pulse detection algorithm (Cluster analysis) and Fourier expansion time-series, which allows fixed periodicities of secretory activity to be resolved [10].
• Cluster analysis of rpm1 alleles defines functionally important residues that are highly conserved between nucleotide binding site leucine-rich repeat R proteins and those that are unique to RPM1 [11].
• Positioning of these targets along the AP axis is thought to be controlled by cis-regulatory modules (CRMs) that contain clusters of Bcd-binding sites of different "strengths." Here we use a combination of Bcd-site cluster analysis and evolutionary conservation to predict Bcd-dependent CRMs [12].
• Hierarchical cluster analysis segregated the tumors into two main groups based on their ER status, which correlated well with basal and luminal characteristics [13].

Chemical compound and disease context of Cluster Analysis

• Metastatic behavior of prostate cancer. Cluster analysis of patterns with respect to estrogen treatment [14].
• Hepatitis B virus genotyping based on cluster analysis of the region involved in lamivudine resistance [15].
• The acute toxicities of 267 compounds to six aquatic and one terrestrial species were investigated with correlation, principal component and cluster analysis techniques for relationships with each other and with the compounds' octanol/water partition coefficient [16].
• Both hierarchical cluster analysis and phylogenetic analysis of sequences for gB polypeptides of 12 different herpesviruses demonstrated that the gB glycoprotein of SA8 is most closely related to the HSV gB glycoproteins [17].
• As revealed by cluster analysis, the tamoxifen-sensitive and the tamoxifen-resistant breast carcinomas differed regarding their gene expression pattern [18].

Biological context of Cluster Analysis

• To investigate the molecular basis of this peculiar phenotype, we first studied the secondary structure of the human CPO by a predictive method, the hydrophobic cluster analysis (HCA) which allowed us to focus on a region of the enzyme [19].
• Using hierarchical cluster analysis of mass spectrometry data to identify proteins that copurify with components of the budding yeast TFIID transcription complex, we discovered that an uncharacterized protein corresponding to the YPL047W open reading frame significantly associated with shared components of the TFIID and SAGA complexes [20].
• Hierarchical cluster analysis revealed two main patterns of DNA methylation that were associated to particular mutational spectra in the K-ras and the p53 genes and alternative correlates of hypomethylation and hypermethylation with survival [21].
• METHODS: Gene expression profiles in FLS cultured from synovial tissues obtained from 19 RA patients were analyzed using complementary DNA microarrays and hierarchical cluster analysis [22].
• Methylation centers in the promoter region and exon 0N were identified by hierarchical cluster analysis of bisulfite sequencing data obtained from 710 alleles [23].

Anatomical context of Cluster Analysis

• Twenty-three such single units were identified by cluster analysis of multiunit recordings obtained from a total of six electrodes implanted in the mediobasal hypothalamus of three ovariectomized rhesus monkeys, and their activity was monitored before and after estradiol administration [24].
• A cluster analysis on the basis of scores for CD25, CD14, and anti-Fc gamma RIII revealed three main clusters, one cluster comprising biopsies without abnormalities, one cluster containing EMB with the histopathology of rejection and high scores in immunophenotyping for lymphocytes and macrophages, and one cluster in between [25].
• We have previously demonstrated that CD10 expression detected by multiparameter flow cytometry (FC) with cluster analysis is highly sensitive and specific for follicle-center lymphoma in the differential diagnosis of small B-cell lymphomas [26].
• Proceedings: Preliminary investigation into uterine epithelial cell types using cluster analysis [27].
• Hierarchical cluster analysis of environmental pollutants through P450 induction in cultured hepatic cells [28].

Associations of Cluster Analysis with chemical compounds

• Cluster analysis demonstrated that trandolapril was only effective in SHR [29].
• A factor analysis study of this matrix, followed by cluster analysis, allowed us to obtain accurate phylogenetic reconstructions and the detection of genes probably involved in speciation as phylogenetic correlates [30].
• Using hydrophobic cluster analysis, a conserved secondary structure motif characteristic of beta-glycosyltransferases was identified along with two highly conserved aspartic acid residues at positions 301 and 352 within the KfiC protein [31].
• Based on hydrophobic cluster analysis and on the (1)H NMR monitoring of the products of the overexpressed A. fortis iota-carrageenase, these enzymes appear to form a new family of glycoside hydrolases, unrelated to that of kappa-carrageenases and with an inverting mechanism of hydrolysis [32].
• Cortical cells were classified using an unsupervised cluster analysis based upon their quantitative and combinatorial immunoreactivity for glutamate, gamma-aminobutyric acid (GABA), aspartate, glutamine and taurine [33].

Gene context of Cluster Analysis

• Undirected cluster analysis of six paired experiments revealed 373 genes, the expression of which was altered significantly and consistently by BRCA1 induction [34].
• Using cluster analyses we classified 10.4% males to be G6PD deficient, while 18.4% had the functionally normal GdA+ enzyme [35].
• Based on HCDR3 cluster analysis, cases using IGHV3-21 could be grouped in 2 subsets of similar frequency [36].
• Cluster analysis of these data using the super paramagnetic clustering (SPC) algorithm demonstrate that the primary genes can be distinguished as a single cluster among a large pool of p53 regulated genes [37].
• With regard to the effect brought about by the deletion of rox1 and srb10, correspondence cluster analysis revealed that the transcriptome profile in aerobic conditions is very similar in the wild-type and both deletion strains [38].

Analytical, diagnostic and therapeutic context of Cluster Analysis

• Microarray analysis demonstrated that treatment of HEEC cultures with either estradiol or medroxyprogesterone acetate produced differential effects on a wide variety of genes, and cluster analysis demonstrated that many of the genes are involved in intracellular signaling and enzymatic pathways [39].
• We highlight here structural relatedness between Class I pilins from their two-dimensional sequence analysis using hydrophobic cluster analysis (HCA) and secondary structure predictions (PHD program) [40].
• Molecular profiles of allograft rejection following inhibition of CD40 ligand costimulation differentiated by cluster analysis [41].
• Using ribotyping, MRSA isolates were compared with well-characterized North American CA-MRSA strains and negative-control hospital-associated (HA) MRSA strains by cluster analysis; 91 of the 173 isolates clustered with two groups of known CA-MRSA strains, 60% of which shared an indistinguishable ribotype [42].
• Moreover, a hierarchical cluster analysis resulted in two distinctly different groups of PCOS women, a lean (PCOSL) and an obese (PCOSO) cluster: compared to healthy women, lean PCOS patients had significantly lower total SAT development, even though height, weight, and body mass index did not deviate significantly [43].

References