233 related articles for article (PubMed ID: 22789589)
1. iBBiG: iterative binary bi-clustering of gene sets.
Gusenleitner D; Howe EA; Bentink S; Quackenbush J; Culhane AC
Bioinformatics; 2012 Oct; 28(19):2484-92. PubMed ID: 22789589
[TBL] [Abstract][Full Text] [Related]
2. CLEAN: CLustering Enrichment ANalysis.
Freudenberg JM; Joshi VK; Hu Z; Medvedovic M
BMC Bioinformatics; 2009 Jul; 10():234. PubMed ID: 19640299
[TBL] [Abstract][Full Text] [Related]
3. Differential regulation enrichment analysis via the integration of transcriptional regulatory network and gene expression data.
Ma S; Jiang T; Jiang R
Bioinformatics; 2015 Feb; 31(4):563-71. PubMed ID: 25322838
[TBL] [Abstract][Full Text] [Related]
4. Clusternomics: Integrative context-dependent clustering for heterogeneous datasets.
Gabasova E; Reid J; Wernisch L
PLoS Comput Biol; 2017 Oct; 13(10):e1005781. PubMed ID: 29036190
[TBL] [Abstract][Full Text] [Related]
5. ClusterMine: A knowledge-integrated clustering approach based on expression profiles of gene sets.
Li HD; Xu Y; Zhu X; Liu Q; Omenn GS; Wang J
J Bioinform Comput Biol; 2020 Jun; 18(3):2040009. PubMed ID: 32698720
[TBL] [Abstract][Full Text] [Related]
6. Consensus framework for exploring microarray data using multiple clustering methods.
Laderas T; McWeeney S
OMICS; 2007; 11(1):116-28. PubMed ID: 17411399
[TBL] [Abstract][Full Text] [Related]
7. A network-assisted co-clustering algorithm to discover cancer subtypes based on gene expression.
Liu Y; Gu Q; Hou JP; Han J; Ma J
BMC Bioinformatics; 2014 Feb; 15():37. PubMed ID: 24491042
[TBL] [Abstract][Full Text] [Related]
8. A novel bi-level meta-analysis approach: applied to biological pathway analysis.
Nguyen T; Tagett R; Donato M; Mitrea C; Draghici S
Bioinformatics; 2016 Feb; 32(3):409-16. PubMed ID: 26471455
[TBL] [Abstract][Full Text] [Related]
9. clusterExperiment and RSEC: A Bioconductor package and framework for clustering of single-cell and other large gene expression datasets.
Risso D; Purvis L; Fletcher RB; Das D; Ngai J; Dudoit S; Purdom E
PLoS Comput Biol; 2018 Sep; 14(9):e1006378. PubMed ID: 30180157
[TBL] [Abstract][Full Text] [Related]
10. TCLUST: a fast method for clustering genome-scale expression data.
Dost B; Wu C; Su A; Bafna V
IEEE/ACM Trans Comput Biol Bioinform; 2011; 8(3):808-18. PubMed ID: 20479508
[TBL] [Abstract][Full Text] [Related]
11. Defining an informativeness metric for clustering gene expression data.
Mar JC; Wells CA; Quackenbush J
Bioinformatics; 2011 Apr; 27(8):1094-100. PubMed ID: 21330289
[TBL] [Abstract][Full Text] [Related]
12. Spectral gene set enrichment (SGSE).
Frost HR; Li Z; Moore JH
BMC Bioinformatics; 2015 Mar; 16():70. PubMed ID: 25879888
[TBL] [Abstract][Full Text] [Related]
13. A systematic comparison of data- and knowledge-driven approaches to disease subtype discovery.
Rintala TJ; Federico A; Latonen L; Greco D; Fortino V
Brief Bioinform; 2021 Nov; 22(6):. PubMed ID: 34396389
[TBL] [Abstract][Full Text] [Related]
14. Clustering short time series gene expression data.
Ernst J; Nau GJ; Bar-Joseph Z
Bioinformatics; 2005 Jun; 21 Suppl 1():i159-68. PubMed ID: 15961453
[TBL] [Abstract][Full Text] [Related]
15. Integrative phenotyping framework (iPF): integrative clustering of multiple omics data identifies novel lung disease subphenotypes.
Kim S; Herazo-Maya JD; Kang DD; Juan-Guardela BM; Tedrow J; Martinez FJ; Sciurba FC; Tseng GC; Kaminski N
BMC Genomics; 2015 Nov; 16():924. PubMed ID: 26560100
[TBL] [Abstract][Full Text] [Related]
16. Subspace Weighting Co-Clustering of Gene Expression Data.
Chen X; Huang JZ; Wu Q; Yang M
IEEE/ACM Trans Comput Biol Bioinform; 2019; 16(2):352-364. PubMed ID: 28541221
[TBL] [Abstract][Full Text] [Related]
17. Integrative clustering of multiple genomic data types using a joint latent variable model with application to breast and lung cancer subtype analysis.
Shen R; Olshen AB; Ladanyi M
Bioinformatics; 2009 Nov; 25(22):2906-12. PubMed ID: 19759197
[TBL] [Abstract][Full Text] [Related]
18. Dynamically weighted clustering with noise set.
Shen Y; Sun W; Li KC
Bioinformatics; 2010 Feb; 26(3):341-7. PubMed ID: 20007256
[TBL] [Abstract][Full Text] [Related]
19. Graph Algorithms for Condensing and Consolidating Gene Set Analysis Results.
Savage SR; Shi Z; Liao Y; Zhang B
Mol Cell Proteomics; 2019 Aug; 18(8 suppl 1):S141-S152. PubMed ID: 31142576
[TBL] [Abstract][Full Text] [Related]
20. Quadratic regression analysis for gene discovery and pattern recognition for non-cyclic short time-course microarray experiments.
Liu H; Tarima S; Borders AS; Getchell TV; Getchell ML; Stromberg AJ
BMC Bioinformatics; 2005 Apr; 6():106. PubMed ID: 15850479
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
