Ye C - Search Results

1

Detecting the presence and absence of causal relationships between expression of yeast genes with very few samples.

Kang EY, Ye C, Shpitser I, Eskin E. Kang EY, et al. Among authors: ye c. J Comput Biol. 2010 Mar;17(3):533-46. doi: 10.1089/cmb.2009.0176. J Comput Biol. 2010. PMID: 20377462 Free PMC article.

2

Assessing computational tools for the discovery of transcription factor binding sites.

Tompa M, Li N, Bailey TL, Church GM, De Moor B, Eskin E, Favorov AV, Frith MC, Fu Y, Kent WJ, Makeev VJ, Mironov AA, Noble WS, Pavesi G, Pesole G, Régnier M, Simonis N, Sinha S, Thijs G, van Helden J, Vandenbogaert M, Weng Z, Workman C, Ye C, Zhu Z. Tompa M, et al. Among authors: ye c. Nat Biotechnol. 2005 Jan;23(1):137-44. doi: 10.1038/nbt1053. Nat Biotechnol. 2005. PMID: 15637633 Free article.

3

Discovering tightly regulated and differentially expressed gene sets in whole genome expression data.

Ye C, Eskin E. Ye C, et al. Bioinformatics. 2007 Jan 15;23(2):e84-90. doi: 10.1093/bioinformatics/btl315. Bioinformatics. 2007. PMID: 17237110

4

Accurate discovery of expression quantitative trait loci under confounding from spurious and genuine regulatory hotspots.

Kang HM, Ye C, Eskin E. Kang HM, et al. Among authors: ye c. Genetics. 2008 Dec;180(4):1909-25. doi: 10.1534/genetics.108.094201. Epub 2008 Sep 14. Genetics. 2008. PMID: 18791227 Free PMC article.

5

Using network component analysis to dissect regulatory networks mediated by transcription factors in yeast.

Ye C, Galbraith SJ, Liao JC, Eskin E. Ye C, et al. PLoS Comput Biol. 2009 Mar;5(3):e1000311. doi: 10.1371/journal.pcbi.1000311. Epub 2009 Mar 20. PLoS Comput Biol. 2009. PMID: 19300475 Free PMC article.

6

Mixed-model coexpression: calculating gene coexpression while accounting for expression heterogeneity.

Furlotte NA, Kang HM, Ye C, Eskin E. Furlotte NA, et al. Among authors: ye c. Bioinformatics. 2011 Jul 1;27(13):i288-94. doi: 10.1093/bioinformatics/btr221. Bioinformatics. 2011. PMID: 21685083 Free PMC article.

7

Integrated computational and experimental analysis of the neuroendocrine transcriptome in genetic hypertension identifies novel control points for the cardiometabolic syndrome.

Friese RS, Ye C, Nievergelt CM, Schork AJ, Mahapatra NR, Rao F, Napolitan PS, Waalen J, Ehret GB, Munroe PB, Schmid-Schönbein GW, Eskin E, O'Connor DT. Friese RS, et al. Among authors: ye c. Circ Cardiovasc Genet. 2012 Aug 1;5(4):430-40. doi: 10.1161/CIRCGENETICS.111.962415. Epub 2012 Jun 5. Circ Cardiovasc Genet. 2012. PMID: 22670052 Free PMC article.

8

Effectively identifying eQTLs from multiple tissues by combining mixed model and meta-analytic approaches.

Sul JH, Han B, Ye C, Choi T, Eskin E. Sul JH, et al. Among authors: ye c. PLoS Genet. 2013 Jun;9(6):e1003491. doi: 10.1371/journal.pgen.1003491. Epub 2013 Jun 13. PLoS Genet. 2013. PMID: 23785294 Free PMC article.

9

Effectively identifying regulatory hotspots while capturing expression heterogeneity in gene expression studies.

Joo JW, Sul JH, Han B, Ye C, Eskin E. Joo JW, et al. Among authors: ye c. Genome Biol. 2014 Apr 7;15(4):r61. doi: 10.1186/gb-2014-15-4-r61. Genome Biol. 2014. PMID: 24708878 Free PMC article.

10

The single-cell eQTLGen consortium.

van der Wijst M, de Vries DH, Groot HE, Trynka G, Hon CC, Bonder MJ, Stegle O, Nawijn MC, Idaghdour Y, van der Harst P, Ye CJ, Powell J, Theis FJ, Mahfouz A, Heinig M, Franke L. van der Wijst M, et al. Among authors: ye cj. Elife. 2020 Mar 9;9:e52155. doi: 10.7554/eLife.52155. Elife. 2020. PMID: 32149610 Free PMC article.

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