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Items: 1 to 20 of 59

1.

Post-processing strategies for improving local gene expression pattern analysis.

Wang Q, Ye Y, Huang JZ, Feng S.

Int J Data Min Bioinform. 2013;7(1):1-21.

PMID:
23437512
2.

Clustering and re-clustering for pattern discovery in gene expression data.

Ma PC, Chan KC, Chiu DK.

J Bioinform Comput Biol. 2005 Apr;3(2):281-301.

PMID:
15852506
4.

Clustering of change patterns using Fourier coefficients.

Kim J, Kim H.

Bioinformatics. 2008 Jan 15;24(2):184-91. Epub 2007 Nov 19.

5.

Recent patents on biclustering algorithms for gene expression data analysis.

Liew AW, Law NF, Yan H.

Recent Pat DNA Gene Seq. 2011 Aug;5(2):117-25. Review.

PMID:
21529337
6.

Coclustering of human cancer microarrays using Minimum Sum-Squared Residue coclustering.

Cho H, Dhillon IS.

IEEE/ACM Trans Comput Biol Bioinform. 2008 Jul-Sep;5(3):385-400. doi: 10.1109/TCBB.2007.70268.

PMID:
18670042
7.

A general framework for biclustering gene expression data.

Li H, Chen X, Zhang K, Jiang T.

J Bioinform Comput Biol. 2006 Aug;4(4):911-33.

PMID:
17007074
8.

Dynamic model-based clustering for time-course gene expression data.

Wu FX, Zhang WJ, Kusalik AJ.

J Bioinform Comput Biol. 2005 Aug;3(4):821-36.

PMID:
16078363
9.

A hybrid genetic algorithm and expectation maximization method for global gene trajectory clustering.

Chan ZS, Kasabov N, Collins L.

J Bioinform Comput Biol. 2005 Oct;3(5):1227-42.

PMID:
16278956
10.

Attribute clustering for grouping, selection, and classification of gene expression data.

Au WH, Chan KC, Wong AK, Wang Y.

IEEE/ACM Trans Comput Biol Bioinform. 2005 Apr-Jun;2(2):83-101. Erratum in: IEEE/ACM Trans Comput Biol Bioinform. 2007 Jan-Mar;4(1):157.

PMID:
17044174
11.

Detecting clusters of different geometrical shapes in microarray gene expression data.

Kim DW, Lee KH, Lee D.

Bioinformatics. 2005 May 1;21(9):1927-34. Epub 2005 Jan 12.

12.

Minimum entropy clustering and applications to gene expression analysis.

Li H, Zhang K, Jiang T.

Proc IEEE Comput Syst Bioinform Conf. 2004:142-51.

PMID:
16448008
14.

CLICK and EXPANDER: a system for clustering and visualizing gene expression data.

Sharan R, Maron-Katz A, Shamir R.

Bioinformatics. 2003 Sep 22;19(14):1787-99.

15.

Techniques for clustering gene expression data.

Kerr G, Ruskin HJ, Crane M, Doolan P.

Comput Biol Med. 2008 Mar;38(3):283-93. Epub 2007 Dec 3. Review.

PMID:
18061589
16.

An iterative data mining approach for mining overlapping coexpression patterns in noisy gene expression data.

Ma PC, Chan KC.

IEEE Trans Nanobioscience. 2009 Sep;8(3):252-8. doi: 10.1109/TNB.2009.2026747. Epub 2009 Jul 14.

PMID:
19605326
17.

An evolutionary approach for gene expression patterns.

Tsai HK, Yang JM, Tsai YF, Kao CY.

IEEE Trans Inf Technol Biomed. 2004 Jun;8(2):69-78.

PMID:
15217251
18.

Fuzzy clustering analysis of microarray data.

Han L, Zeng X, Yan H.

Proc Inst Mech Eng H. 2008 Oct;222(7):1143-8.

PMID:
19024161
19.
20.

A new approach for clustering gene expression time series data.

Das R, Kalita J, Bhattacharyya DK.

Int J Bioinform Res Appl. 2009;5(3):310-28.

PMID:
19525203
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