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Hoffmann, R. A wiki for the life sciences where authorship matters. Nature Genetics (2008)
MeSH Review

Cluster Analysis

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Disease relevance of Cluster Analysis


Psychiatry related information on Cluster Analysis


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


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


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].


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  3. 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. Sadlier, D.M., Connolly, S.B., Kieran, N.E., Roxburgh, S., Brazil, D.P., Kairaitis, L., Wang, Y., Harris, D.C., Doran, P., Brady, H.R. J. Biol. Chem. (2004) [Pubmed]
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  5. Distinct methylation patterns of benign and malignant liver tumors revealed by quantitative methylation profiling. Lehmann, U., Berg-Ribbe, I., Wingen, L.U., Brakensiek, K., Becker, T., Klempnauer, J., Schlegelberger, B., Kreipe, H., Flemming, P. Clin. Cancer Res. (2005) [Pubmed]
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  11. Large-scale structure-function analysis of the Arabidopsis RPM1 disease resistance protein. Tornero, P., Chao, R.A., Luthin, W.N., Goff, S.A., Dangl, J.L. Plant Cell (2002) [Pubmed]
  12. The role of binding site cluster strength in Bicoid-dependent patterning in Drosophila. Ochoa-Espinosa, A., Yucel, G., Kaplan, L., Pare, A., Pura, N., Oberstein, A., Papatsenko, D., Small, S. Proc. Natl. Acad. Sci. U.S.A. (2005) [Pubmed]
  13. Breast cancer classification and prognosis based on gene expression profiles from a population-based study. Sotiriou, C., Neo, S.Y., McShane, L.M., Korn, E.L., Long, P.M., Jazaeri, A., Martiat, P., Fox, S.B., Harris, A.L., Liu, E.T. Proc. Natl. Acad. Sci. U.S.A. (2003) [Pubmed]
  14. Metastatic behavior of prostate cancer. Cluster analysis of patterns with respect to estrogen treatment. de la Monte, S.M., Moore, G.W., Hutchins, G.M. Cancer (1986) [Pubmed]
  15. Hepatitis B virus genotyping based on cluster analysis of the region involved in lamivudine resistance. Rodríguez-Nóvoa, S., Gómez-Tato, A., Aguilera-Guirao, A., Castroagudín, J., González-Quintela, A., Garcia-Riestra, C., Regueiro, B.J. J. Virol. Methods (2004) [Pubmed]
  16. Regression and cluster analysis of the acute toxicity of 267 chemicals to six species of biota and the octanol/water partition coefficient. Kaiser, K.L., Esterby, S.R. Sci. Total Environ. (1991) [Pubmed]
  17. The simian herpesvirus SA8 homologue of the herpes simplex virus gB gene: mapping, sequencing, and comparison to the HSV gB. Eberle, R., Black, D. Arch. Virol. (1991) [Pubmed]
  18. Distinct gene expression patterns in a tamoxifen-sensitive human mammary carcinoma xenograft and its tamoxifen-resistant subline MaCa 3366/TAM. Becker, M., Sommer, A., Krätzschmar, J.R., Seidel, H., Pohlenz, H.D., Fichtner, I. Mol. Cancer Ther. (2005) [Pubmed]
  19. Mutations in human CPO gene predict clinical expression of either hepatic hereditary coproporphyria or erythropoietic harderoporphyria. Schmitt, C., Gouya, L., Malonova, E., Lamoril, J., Camadro, J.M., Flamme, M., Rose, C., Lyoumi, S., Da Silva, V., Boileau, C., Grandchamp, B., Beaumont, C., Deybach, J.C., Puy, H. Hum. Mol. Genet. (2005) [Pubmed]
  20. Cluster analysis of mass spectrometry data reveals a novel component of SAGA. Powell, D.W., Weaver, C.M., Jennings, J.L., McAfee, K.J., He, Y., Weil, P.A., Link, A.J. Mol. Cell. Biol. (2004) [Pubmed]
  21. Differential DNA hypermethylation and hypomethylation signatures in colorectal cancer. Frigola, J., Solé, X., Paz, M.F., Moreno, V., Esteller, M., Capellà, G., Peinado, M.A. Hum. Mol. Genet. (2005) [Pubmed]
  22. Fibroblast-like synoviocytes derived from patients with rheumatoid arthritis show the imprint of synovial tissue heterogeneity: evidence of a link between an increased myofibroblast-like phenotype and high-inflammation synovitis. Kasperkovitz, P.V., Timmer, T.C., Smeets, T.J., Verbeet, N.L., Tak, P.P., van Baarsen, L.G., Baltus, B., Huizinga, T.W., Pieterman, E., Fero, M., Firestein, G.S., van der Pouw Kraan, T.C., Verweij, C.L. Arthritis Rheum. (2005) [Pubmed]
  23. Dynamic regulation of estrogen receptor-beta expression by DNA methylation during prostate cancer development and metastasis. Zhu, X., Leav, I., Leung, Y.K., Wu, M., Liu, Q., Gao, Y., McNeal, J.E., Ho, S.M. Am. J. Pathol. (2004) [Pubmed]
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  25. Endomyocardial biopsies after heart transplantation. The presence of markers indicative of activation. Wijngaard, P.L., Tuijnman, W.B., Gmelig Meyling, F.H., van der Meulen, A., Huytink, M., Jambroes, G., Schuurman, H.J. Transplantation (1993) [Pubmed]
  26. Comparison of multiparameter flow cytometry with cluster analysis and immunohistochemistry for the detection of CD10 in diffuse large B-Cell lymphomas. Xu, Y., McKenna, R.W., Kroft, S.H. Mod. Pathol. (2002) [Pubmed]
  27. Proceedings: Preliminary investigation into uterine epithelial cell types using cluster analysis. Stanton, J.H. J. Reprod. Fertil. (1976) [Pubmed]
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  32. iota-Carrageenases constitute a novel family of glycoside hydrolases, unrelated to that of kappa-carrageenases. Barbeyron, T., Michel, G., Potin, P., Henrissat, B., Kloareg, B. J. Biol. Chem. (2000) [Pubmed]
  33. Cellular diversity in mouse neocortex revealed by multispectral analysis of amino acid immunoreactivity. Hill, E., Kalloniatis, M., Tan, S.S. Cereb. Cortex (2001) [Pubmed]
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  37. DNA microarrays identification of primary and secondary target genes regulated by p53. Kannan, K., Amariglio, N., Rechavi, G., Jakob-Hirsch, J., Kela, I., Kaminski, N., Getz, G., Domany, E., Givol, D. Oncogene (2001) [Pubmed]
  38. The yeast transcriptome in aerobic and hypoxic conditions: effects of hap1, rox1, rox3 and srb10 deletions. Becerra, M., Lombardía-Ferreira, L.J., Hauser, N.C., Hoheisel, J.D., Tizon, B., Cerdán, M.E. Mol. Microbiol. (2002) [Pubmed]
  39. Endometrial endothelial cell steroid receptor expression and steroid effects on gene expression. Krikun, G., Schatz, F., Taylor, R., Critchley, H.O., Rogers, P.A., Huang, J., Lockwood, C.J. J. Clin. Endocrinol. Metab. (2005) [Pubmed]
  40. Conserved structural features in class I major fimbrial subunits (Pilin) in gram-negative bacteria. Molecular basis of classification in seven subfamilies and identification of intrasubfamily sequence signature motifs which might Be implicated in quaternary structure. Girardeau, J.P., Bertin, Y., Callebaut, I. J. Mol. Evol. (2000) [Pubmed]
  41. Molecular profiles of allograft rejection following inhibition of CD40 ligand costimulation differentiated by cluster analysis. Damrauer, S.M., DeFina, R., He, H., Haley, K.J., Perkins, D.L. J. Leukoc. Biol. (2002) [Pubmed]
  42. Use of ribotyping to retrospectively identify methicillin-resistant Staphylococcus aureus isolates from phase 3 clinical trials for tigecycline that are genotypically related to community-associated isolates. McAleese, F., Murphy, E., Babinchak, T., Singh, G., Said-Salim, B., Kreiswirth, B., Dunman, P., O'Connell, J., Projan, S.J., Bradford, P.A. Antimicrob. Agents Chemother. (2005) [Pubmed]
  43. Android subcutaneous adipose tissue topography in lean and obese women suffering from PCOS: comparison with type 2 diabetic women. Horejsi, R., Möller, R., Rackl, S., Giuliani, A., Freytag, U., Crailsheim, K., Sudi, K., Tafeit, E. Am. J. Phys. Anthropol. (2004) [Pubmed]
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