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Items: 1 to 20 of 72

1.

Partitioning biological data with transitivity clustering.

Wittkop T, Emig D, Lange S, Rahmann S, Albrecht M, Morris JH, Böcker S, Stoye J, Baumbach J.

Nat Methods. 2010 Jun;7(6):419-20. doi: 10.1038/nmeth0610-419. No abstract available.

PMID:
20508635
2.

Clustering microarray data.

Gollub J, Sherlock G.

Methods Enzymol. 2006;411:194-213. Review.

PMID:
16939791
3.

Profiling local optima in K-means clustering: developing a diagnostic technique.

Steinley D.

Psychol Methods. 2006 Jun;11(2):178-92.

PMID:
16784337
4.

Analysis of large-scale gene expression data.

Sherlock G.

Curr Opin Immunol. 2000 Apr;12(2):201-5. Review.

PMID:
10712947
5.

A new approach of data clustering using a flock of agents.

Picarougne F, Azzag H, Venturini G, Guinot C.

Evol Comput. 2007 Fall;15(3):345-67.

PMID:
17705782
6.

A hybrid approach to clustering biomedical data.

Thayer JF.

Biomed Sci Instrum. 1996;32:39-46.

PMID:
8672688
7.

Cluster significance testing using the bootstrap.

Auffermann WF, Ngan SC, Hu X.

Neuroimage. 2002 Oct;17(2):583-91.

PMID:
12377136
8.

Minimum spanning trees for gene expression data clustering.

Xu Y, Olman V, Xu D.

Genome Inform. 2001;12:24-33.

PMID:
11791221
9.

Assessment of hierarchical clustering methodologies for proteomic data mining.

Meunier B, Dumas E, Piec I, Béchet D, Hébraud M, Hocquette JF.

J Proteome Res. 2007 Jan;6(1):358-66. Erratum in: J Proteome Res. 2007 Mar;6(3):1215.

PMID:
17203979
10.

Graph-based consensus clustering for class discovery from gene expression data.

Yu Z, Wong HS, Wang H.

Bioinformatics. 2007 Nov 1;23(21):2888-96. Epub 2007 Sep 14.

11.

Advances in clustering and visualization of time series using GTM through time.

Olier I, Vellido A.

Neural Netw. 2008 Sep;21(7):904-13. doi: 10.1016/j.neunet.2008.05.013. Epub 2008 Jun 14.

PMID:
18653311
12.

How does gene expression clustering work?

D'haeseleer P.

Nat Biotechnol. 2005 Dec;23(12):1499-501. Review.

PMID:
16333293
13.

Methods for investigating localized clustering of disease. The data-sets.

[No authors listed]

IARC Sci Publ. 1996;(135):165-84. No abstract available.

PMID:
9103938
14.

Comment on "Clustering by passing messages between data points".

Brusco MJ, Köhn HF.

Science. 2008 Feb 8;319(5864):726; author reply 726. doi: 10.1126/science.1150938.

15.

The combined use of multivariate and clustering analyses in functional morphology.

Oxnard CE.

J Biomech. 1969 Mar;2(1):73-88. No abstract available.

PMID:
16335114
16.

Determining the number of clusters using the weighted gap statistic.

Yan M, Ye K.

Biometrics. 2007 Dec;63(4):1031-7. Epub 2007 Apr 9.

PMID:
17425640
17.

Unfolding preprocessing for meaningful time series clustering.

Simon G, Lee JA, Verleysen M.

Neural Netw. 2006 Jul-Aug;19(6-7):877-88. Epub 2006 Jul 3.

PMID:
16815672
18.

A model for clustering of longitudinal data sets of infant mortality rates in India.

Bansal AK, Sharma S.

Med Sci Monit. 2003 Apr;9(4):PH1-6.

PMID:
12709679
19.
20.

Ant-based clustering and topographic mapping.

Handl J, Knowles J, Dorigo M.

Artif Life. 2006 Winter;12(1):35-61.

PMID:
16393450
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