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Items: 1 to 20 of 168

1.
2.

Biclustering via optimal re-ordering of data matrices in systems biology: rigorous methods and comparative studies.

DiMaggio PA Jr, McAllister SR, Floudas CA, Feng XJ, Rabinowitz JD, Rabitz HA.

BMC Bioinformatics. 2008 Oct 27;9:458. doi: 10.1186/1471-2105-9-458.

3.

Parallelized evolutionary learning for detection of biclusters in gene expression data.

Huang Q, Tao D, Li X, Liew AW.

IEEE/ACM Trans Comput Biol Bioinform. 2012;9(2):560-70. doi: 10.1109/TCBB.2011.53.

PMID:
21383419
4.

cMonkey2: Automated, systematic, integrated detection of co-regulated gene modules for any organism.

Reiss DJ, Plaisier CL, Wu WJ, Baliga NS.

Nucleic Acids Res. 2015 Jul 27;43(13):e87. doi: 10.1093/nar/gkv300.

5.

The Inferelator: an algorithm for learning parsimonious regulatory networks from systems-biology data sets de novo.

Bonneau R, Reiss DJ, Shannon P, Facciotti M, Hood L, Baliga NS, Thorsson V.

Genome Biol. 2006;7(5):R36.

6.

Discovering biclusters in gene expression data based on high-dimensional linear geometries.

Gan X, Liew AW, Yan H.

BMC Bioinformatics. 2008 Apr 23;9:209. doi: 10.1186/1471-2105-9-209.

7.

Multi-species integrative biclustering.

Waltman P, Kacmarczyk T, Bate AR, Kearns DB, Reiss DJ, Eichenberger P, Bonneau R.

Genome Biol. 2010;11(9):R96. doi: 10.1186/gb-2010-11-9-r96.

8.

CompMoby: comparative MobyDick for detection of cis-regulatory motifs.

Chaivorapol C, Melton C, Wei G, Yeh RF, Ramalho-Santos M, Blelloch R, Li H.

BMC Bioinformatics. 2008 Oct 27;9:455. doi: 10.1186/1471-2105-9-455.

9.

QServer: a biclustering server for prediction and assessment of co-expressed gene clusters.

Zhou F, Ma Q, Li G, Xu Y.

PLoS One. 2012;7(3):e32660. doi: 10.1371/journal.pone.0032660.

10.

A new geometric biclustering algorithm based on the Hough transform for analysis of large-scale microarray data.

Zhao H, Liew AW, Xie X, Yan H.

J Theor Biol. 2008 Mar 21;251(2):264-74. doi: 10.1016/j.jtbi.2007.11.030.

PMID:
18199458
11.

Comparative microbial modules resource: generation and visualization of multi-species biclusters.

Kacmarczyk T, Waltman P, Bate A, Eichenberger P, Bonneau R.

PLoS Comput Biol. 2011 Dec;7(12):e1002228. doi: 10.1371/journal.pcbi.1002228.

12.

Dynamic biclustering of microarray data by multi-objective immune optimization.

Liu J, Li Z, Hu X, Chen Y, Park EK.

BMC Genomics. 2011;12 Suppl 2:S11. doi: 10.1186/1471-2164-12-S2-S11.

13.

Inferring regulatory elements from a whole genome. An analysis of Helicobacter pylori sigma(80) family of promoter signals.

Vanet A, Marsan L, Labigne A, Sagot MF.

J Mol Biol. 2000 Mar 24;297(2):335-53.

PMID:
10715205
14.

Identification of co-regulated genes through Bayesian clustering of predicted regulatory binding sites.

Qin ZS, McCue LA, Thompson W, Mayerhofer L, Lawrence CE, Liu JS.

Nat Biotechnol. 2003 Apr;21(4):435-9.

PMID:
12627170
15.

Biclustering algorithms for biological data analysis: a survey.

Madeira SC, Oliveira AL.

IEEE/ACM Trans Comput Biol Bioinform. 2004 Jan-Mar;1(1):24-45.

PMID:
17048406
16.

Unraveling networks of co-regulated genes on the sole basis of genome sequences.

Brohée S, Janky R, Abdel-Sater F, Vanderstocken G, André B, van Helden J.

Nucleic Acids Res. 2011 Aug;39(15):6340-58. doi: 10.1093/nar/gkr264.

17.

Identification of coherent patterns in gene expression data using an efficient biclustering algorithm and parallel coordinate visualization.

Cheng KO, Law NF, Siu WC, Liew AW.

BMC Bioinformatics. 2008 Apr 23;9:210. doi: 10.1186/1471-2105-9-210.

18.

Querying Co-regulated Genes on Diverse Gene Expression Datasets Via Biclustering.

Deveci M, Küçüktunç O, Eren K, Bozdağ D, Kaya K, Çatalyürek ÜV.

Methods Mol Biol. 2016;1375:55-74. doi: 10.1007/7651_2015_246.

PMID:
26626937
19.
20.

Analysis of differentially-regulated genes within a regulatory network by GPS genome navigation.

Zwir I, Huang H, Groisman EA.

Bioinformatics. 2005 Nov 15;21(22):4073-83.

PMID:
16159917

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