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Items: 1 to 20 of 105

1.

Melissa: Bayesian clustering and imputation of single-cell methylomes.

Kapourani CA, Sanguinetti G.

Genome Biol. 2019 Mar 21;20(1):61. doi: 10.1186/s13059-019-1665-8.

2.

CIDR: Ultrafast and accurate clustering through imputation for single-cell RNA-seq data.

Lin P, Troup M, Ho JW.

Genome Biol. 2017 Mar 28;18(1):59. doi: 10.1186/s13059-017-1188-0.

3.

Single-cell DNA methylome sequencing and bioinformatic inference of epigenomic cell-state dynamics.

Farlik M, Sheffield NC, Nuzzo A, Datlinger P, Schönegger A, Klughammer J, Bock C.

Cell Rep. 2015 Mar 3;10(8):1386-97. doi: 10.1016/j.celrep.2015.02.001. Epub 2015 Feb 26.

4.

A nonparametric Bayesian approach for clustering bisulfate-based DNA methylation profiles.

Zhang L, Meng J, Liu H, Huang Y.

BMC Genomics. 2012;13 Suppl 6:S20. doi: 10.1186/1471-2164-13-S6-S20. Epub 2012 Oct 26.

5.
6.

Recursively partitioned mixture model clustering of DNA methylation data using biologically informed correlation structures.

Koestler DC, Christensen BC, Marsit CJ, Kelsey KT, Houseman EA.

Stat Appl Genet Mol Biol. 2013 Mar 5;12(2):225-40. doi: 10.1515/sagmb-2012-0068.

7.

A full Bayesian partition model for identifying hypo- and hyper-methylated loci from single nucleotide resolution sequencing data.

Wang H, He C, Kushwaha G, Xu D, Qiu J.

BMC Bioinformatics. 2016 Jan 11;17 Suppl 1:7. doi: 10.1186/s12859-015-0850-3.

8.

Systematic identification and annotation of human methylation marks based on bisulfite sequencing methylomes reveals distinct roles of cell type-specific hypomethylation in the regulation of cell identity genes.

Liu H, Liu X, Zhang S, Lv J, Li S, Shang S, Jia S, Wei Y, Wang F, Su J, Wu Q, Zhang Y.

Nucleic Acids Res. 2016 Jan 8;44(1):75-94. doi: 10.1093/nar/gkv1332. Epub 2015 Dec 3.

9.

Comprehensive Whole DNA Methylome Analysis by Integrating MeDIP-seq and MRE-seq.

Xing X, Zhang B, Li D, Wang T.

Methods Mol Biol. 2018;1708:209-246. doi: 10.1007/978-1-4939-7481-8_12.

10.

Bayesian inference supports a location and neighbour-dependent model of DNA methylation propagation at the MGMT gene promoter in lung tumours.

Bonello N, Sampson J, Burn J, Wilson IJ, McGrown G, Margison GP, Thorncroft M, Crossbie P, Povey AC, Santibanez-Koref M, Walters K.

J Theor Biol. 2013 Nov 7;336:87-95. doi: 10.1016/j.jtbi.2013.07.019. Epub 2013 Jul 30.

PMID:
23911575
11.

Discovering cooperative relationships of chromatin modifications in human T cells based on a proposed closeness measure.

Lv J, Qiao H, Liu H, Wu X, Zhu J, Su J, Wang F, Cui Y, Zhang Y.

PLoS One. 2010 Dec 3;5(12):e14219. doi: 10.1371/journal.pone.0014219.

12.

Relational analysis of CpG islands methylation and gene expression in human lymphomas using possibilistic C-means clustering and modified cluster fuzzy density.

Sjahputera O, Keller JM, Davis JW, Taylor KH, Rahmatpanah F, Shi H, Anderson DT, Blisard SN, Luke RH, Popescu M, Arthur GC, Caldwell CW.

IEEE/ACM Trans Comput Biol Bioinform. 2007 Apr-Jun;4(2):176-89.

PMID:
17473312
13.

BASiCS: Bayesian Analysis of Single-Cell Sequencing Data.

Vallejos CA, Marioni JC, Richardson S.

PLoS Comput Biol. 2015 Jun 24;11(6):e1004333. doi: 10.1371/journal.pcbi.1004333. eCollection 2015 Jun.

14.

A multitask clustering approach for single-cell RNA-seq analysis in Recessive Dystrophic Epidermolysis Bullosa.

Zhang H, Lee CAA, Li Z, Garbe JR, Eide CR, Petegrosso R, Kuang R, Tolar J.

PLoS Comput Biol. 2018 Apr 9;14(4):e1006053. doi: 10.1371/journal.pcbi.1006053. eCollection 2018 Apr.

15.

A Novel Computational Method for Detecting DNA Methylation Sites with DNA Sequence Information and Physicochemical Properties.

Pan G, Jiang L, Tang J, Guo F.

Int J Mol Sci. 2018 Feb 8;19(2). pii: E511. doi: 10.3390/ijms19020511.

16.

Bayesian mixture model based clustering of replicated microarray data.

Medvedovic M, Yeung KY, Bumgarner RE.

Bioinformatics. 2004 May 22;20(8):1222-32. Epub 2004 Feb 10.

PMID:
14871871
17.

Dissecting trait heterogeneity: a comparison of three clustering methods applied to genotypic data.

Thornton-Wells TA, Moore JH, Haines JL.

BMC Bioinformatics. 2006 Apr 12;7:204.

18.

Integrative single-cell omics analyses reveal epigenetic heterogeneity in mouse embryonic stem cells.

Luo Y, He J, Xu X, Sun MA, Wu X, Lu X, Xie H.

PLoS Comput Biol. 2018 Mar 21;14(3):e1006034. doi: 10.1371/journal.pcbi.1006034. eCollection 2018 Mar.

19.

Scalable optimal Bayesian classification of single-cell trajectories under regulatory model uncertainty.

Hajiramezanali E, Imani M, Braga-Neto U, Qian X, Dougherty ER.

BMC Genomics. 2019 Jun 13;20(Suppl 6):435. doi: 10.1186/s12864-019-5720-3.

20.

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