213 related articles for article (PubMed ID: 18541054)
1. A practical comparison of two K-Means clustering algorithms.
Wilkin GA; Huang X
BMC Bioinformatics; 2008 May; 9 Suppl 6(Suppl 6):S19. PubMed ID: 18541054
[TBL] [Abstract][Full Text] [Related]
2. EDISA: extracting biclusters from multiple time-series of gene expression profiles.
Supper J; Strauch M; Wanke D; Harter K; Zell A
BMC Bioinformatics; 2007 Sep; 8():334. PubMed ID: 17850657
[TBL] [Abstract][Full Text] [Related]
3. Measuring similarities between gene expression profiles through new data transformations.
Kim K; Zhang S; Jiang K; Cai L; Lee IB; Feldman LJ; Huang H
BMC Bioinformatics; 2007 Jan; 8():29. PubMed ID: 17257435
[TBL] [Abstract][Full Text] [Related]
4. An effective fuzzy kernel clustering analysis approach for gene expression data.
Sun L; Xu J; Yin J
Biomed Mater Eng; 2015; 26 Suppl 1():S1863-9. PubMed ID: 26405958
[TBL] [Abstract][Full Text] [Related]
5. Fuzzy clustering analysis of microarray data.
Han L; Zeng X; Yan H
Proc Inst Mech Eng H; 2008 Oct; 222(7):1143-8. PubMed ID: 19024161
[TBL] [Abstract][Full Text] [Related]
6. Conditional clustering of temporal expression profiles.
Wang L; Montano M; Rarick M; Sebastiani P
BMC Bioinformatics; 2008 Mar; 9():147. PubMed ID: 18334028
[TBL] [Abstract][Full Text] [Related]
7. Genetic weighted k-means algorithm for clustering large-scale gene expression data.
Wu FX
BMC Bioinformatics; 2008 May; 9 Suppl 6(Suppl 6):S12. PubMed ID: 18541047
[TBL] [Abstract][Full Text] [Related]
8. A phase synchronization clustering algorithm for identifying interesting groups of genes from cell cycle expression data.
Kim CS; Bae CS; Tcha HJ
BMC Bioinformatics; 2008 Jan; 9():56. PubMed ID: 18221564
[TBL] [Abstract][Full Text] [Related]
9. Clustering of change patterns using Fourier coefficients.
Kim J; Kim H
Bioinformatics; 2008 Jan; 24(2):184-91. PubMed ID: 18025003
[TBL] [Abstract][Full Text] [Related]
10. ParaKMeans: Implementation of a parallelized K-means algorithm suitable for general laboratory use.
Kraj P; Sharma A; Garge N; Podolsky R; McIndoe RA
BMC Bioinformatics; 2008 Apr; 9():200. PubMed ID: 18416829
[TBL] [Abstract][Full Text] [Related]
11. Clustering of gene expression data: performance and similarity analysis.
Yin L; Huang CH; Ni J
BMC Bioinformatics; 2006 Dec; 7 Suppl 4(Suppl 4):S19. PubMed ID: 17217511
[TBL] [Abstract][Full Text] [Related]
12. A novel approach for clustering proteomics data using Bayesian fast Fourier transform.
Bensmail H; Golek J; Moody MM; Semmes JO; Haoudi A
Bioinformatics; 2005 May; 21(10):2210-24. PubMed ID: 15769836
[TBL] [Abstract][Full Text] [Related]
13. Microarray data clustering based on temporal variation: FCV with TSD preclustering.
Möller-Levet CS; Cho KH; Wolkenhauer O
Appl Bioinformatics; 2003; 2(1):35-45. PubMed ID: 15130832
[TBL] [Abstract][Full Text] [Related]
14. Hierarchical tree snipping: clustering guided by prior knowledge.
Dotan-Cohen D; Melkman AA; Kasif S
Bioinformatics; 2007 Dec; 23(24):3335-42. PubMed ID: 17989094
[TBL] [Abstract][Full Text] [Related]
15. Variable selection for model-based high-dimensional clustering and its application to microarray data.
Wang S; Zhu J
Biometrics; 2008 Jun; 64(2):440-8. PubMed ID: 17970821
[TBL] [Abstract][Full Text] [Related]
16. A mixture model with random-effects components for clustering correlated gene-expression profiles.
Ng SK; McLachlan GJ; Wang K; Ben-Tovim Jones L; Ng SW
Bioinformatics; 2006 Jul; 22(14):1745-52. PubMed ID: 16675467
[TBL] [Abstract][Full Text] [Related]
17. CASCADE: a novel quasi all paths-based network analysis algorithm for clustering biological interactions.
Hwang W; Cho YR; Zhang A; Ramanathan M
BMC Bioinformatics; 2008 Jan; 9():64. PubMed ID: 18230159
[TBL] [Abstract][Full Text] [Related]
18. Methods for simultaneously identifying coherent local clusters with smooth global patterns in gene expression profiles.
Tien YJ; Lee YS; Wu HM; Chen CH
BMC Bioinformatics; 2008 Mar; 9():155. PubMed ID: 18366693
[TBL] [Abstract][Full Text] [Related]
19. 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. PubMed ID: 16078363
[TBL] [Abstract][Full Text] [Related]
20. Clustering by soft-constraint affinity propagation: applications to gene-expression data.
Leone M; Sumedha ; Weigt M
Bioinformatics; 2007 Oct; 23(20):2708-15. PubMed ID: 17895277
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
