334 related articles for article (PubMed ID: 27153661)
1. densityCut: an efficient and versatile topological approach for automatic clustering of biological data.
Ding J; Shah S; Condon A
Bioinformatics; 2016 Sep; 32(17):2567-76. PubMed ID: 27153661
[TBL] [Abstract][Full Text] [Related]
2. HGC: fast hierarchical clustering for large-scale single-cell data.
Zou Z; Hua K; Zhang X
Bioinformatics; 2021 Nov; 37(21):3964-3965. PubMed ID: 34096998
[TBL] [Abstract][Full Text] [Related]
3. LCE: a link-based cluster ensemble method for improved gene expression data analysis.
Iam-on N; Boongoen T; Garrett S
Bioinformatics; 2010 Jun; 26(12):1513-9. PubMed ID: 20444838
[TBL] [Abstract][Full Text] [Related]
4. Knowledge-assisted recognition of cluster boundaries in gene expression data.
Okada Y; Sahara T; Mitsubayashi H; Ohgiya S; Nagashima T
Artif Intell Med; 2005; 35(1-2):171-83. PubMed ID: 16054350
[TBL] [Abstract][Full Text] [Related]
5. Functional grouping of similar genes using eigenanalysis on minimum spanning tree based neighborhood graph.
Jothi R; Mohanty SK; Ojha A
Comput Biol Med; 2016 Apr; 71():135-48. PubMed ID: 26945461
[TBL] [Abstract][Full Text] [Related]
6. Analysis of a Gibbs sampler method for model-based clustering of gene expression data.
Joshi A; Van de Peer Y; Michoel T
Bioinformatics; 2008 Jan; 24(2):176-83. PubMed ID: 18033794
[TBL] [Abstract][Full Text] [Related]
7. A dynamically growing self-organizing tree (DGSOT) for hierarchical clustering gene expression profiles.
Luo F; Khan L; Bastani F; Yen IL; Zhou J
Bioinformatics; 2004 Nov; 20(16):2605-17. PubMed ID: 15130935
[TBL] [Abstract][Full Text] [Related]
8. Detecting clusters of different geometrical shapes in microarray gene expression data.
Kim DW; Lee KH; Lee D
Bioinformatics; 2005 May; 21(9):1927-34. PubMed ID: 15647300
[TBL] [Abstract][Full Text] [Related]
9. A modified hyperplane clustering algorithm allows for efficient and accurate clustering of extremely large datasets.
Sharma A; Podolsky R; Zhao J; McIndoe RA
Bioinformatics; 2009 May; 25(9):1152-7. PubMed ID: 19261720
[TBL] [Abstract][Full Text] [Related]
10. 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]
11. A cross-species bi-clustering approach to identifying conserved co-regulated genes.
Sun J; Jiang Z; Tian X; Bi J
Bioinformatics; 2016 Jun; 32(12):i137-i146. PubMed ID: 27307610
[TBL] [Abstract][Full Text] [Related]
12. 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]
13. Weighted rank aggregation of cluster validation measures: a Monte Carlo cross-entropy approach.
Pihur V; Datta S; Datta S
Bioinformatics; 2007 Jul; 23(13):1607-15. PubMed ID: 17483500
[TBL] [Abstract][Full Text] [Related]
14. 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]
15. A new algorithm for comparing and visualizing relationships between hierarchical and flat gene expression data clusterings.
Torrente A; Kapushesky M; Brazma A
Bioinformatics; 2005 Nov; 21(21):3993-9. PubMed ID: 16141251
[TBL] [Abstract][Full Text] [Related]
16. Graph-based consensus clustering for class discovery from gene expression data.
Yu Z; Wong HS; Wang H
Bioinformatics; 2007 Nov; 23(21):2888-96. PubMed ID: 17872912
[TBL] [Abstract][Full Text] [Related]
17. Clusterdv: a simple density-based clustering method that is robust, general and automatic.
Marques JC; Orger MB
Bioinformatics; 2019 Jun; 35(12):2125-2132. PubMed ID: 30407500
[TBL] [Abstract][Full Text] [Related]
18. Clustering threshold gradient descent regularization: with applications to microarray studies.
Ma S; Huang J
Bioinformatics; 2007 Feb; 23(4):466-72. PubMed ID: 17182700
[TBL] [Abstract][Full Text] [Related]
19. Studies on the Clustering Algorithm for Analyzing Gene Expression Data with a Bidirectional Penalty.
Yang H; Liu X
J Comput Biol; 2017 Jul; 24(7):689-698. PubMed ID: 28489418
[TBL] [Abstract][Full Text] [Related]
20. SCHNEL: scalable clustering of high dimensional single-cell data.
Abdelaal T; de Raadt P; Lelieveldt BPF; Reinders MJT; Mahfouz A
Bioinformatics; 2020 Dec; 36(Suppl_2):i849-i856. PubMed ID: 33381821
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]