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Results: 1 to 20 of 34

1.

BitPhylogeny: a probabilistic framework for reconstructing intra-tumor phylogenies.

Yuan K, Sakoparnig T, Markowetz F, Beerenwinkel N.

Genome Biol. 2015 Feb 13;16:36. doi: 10.1186/s13059-015-0592-6.

2.

Spatial and temporal heterogeneity in high-grade serous ovarian cancer: a phylogenetic analysis.

Schwarz RF, Ng CK, Cooke SL, Newman S, Temple J, Piskorz AM, Gale D, Sayal K, Murtaza M, Baldwin PJ, Rosenfeld N, Earl HM, Sala E, Jimenez-Linan M, Parkinson CA, Markowetz F, Brenton JD.

PLoS Med. 2015 Feb 24;12(2):e1001789. doi: 10.1371/journal.pmed.1001789. eCollection 2015 Feb.

3.

Combined image and genomic analysis of high-grade serous ovarian cancer reveals PTEN loss as a common driver event and prognostic classifier.

Martins FC, Santiago Id, Trinh A, Xian J, Guo A, Sayal K, Jimenez-Linan M, Deen S, Driver K, Mack M, Aslop J, Pharoah PD, Markowetz F, Brenton JD.

Genome Biol. 2014 Dec 17;15(12):526. doi: 10.1186/s13059-014-0526-8.

4.

Cancer evolution: mathematical models and computational inference.

Beerenwinkel N, Schwarz RF, Gerstung M, Markowetz F.

Syst Biol. 2015 Jan;64(1):e1-25. doi: 10.1093/sysbio/syu081. Epub 2014 Oct 7. Review.

5.

SANTA: quantifying the functional content of molecular networks.

Cornish AJ, Markowetz F.

PLoS Comput Biol. 2014 Sep 11;10(9):e1003808. doi: 10.1371/journal.pcbi.1003808. eCollection 2014 Sep.

6.

GoIFISH: a system for the quantification of single cell heterogeneity from IFISH images.

Trinh A, Rye IH, Almendro V, Helland A, Russnes HG, Markowetz F.

Genome Biol. 2014 Aug 26;15(8):442. doi: 10.1186/s13059-014-0442-y.

7.

Phylogenetic quantification of intra-tumour heterogeneity.

Schwarz RF, Trinh A, Sipos B, Brenton JD, Goldman N, Markowetz F.

PLoS Comput Biol. 2014 Apr 17;10(4):e1003535. doi: 10.1371/journal.pcbi.1003535. eCollection 2014 Apr.

8.

Master regulators of FGFR2 signalling and breast cancer risk.

Fletcher MN, Castro MA, Wang X, de Santiago I, O'Reilly M, Chin SF, Rueda OM, Caldas C, Ponder BA, Markowetz F, Meyer KB.

Nat Commun. 2013;4:2464. doi: 10.1038/ncomms3464.

9.

Dissecting cancer heterogeneity--an unsupervised classification approach.

Wang X, Markowetz F, De Sousa E Melo F, Medema JP, Vermeulen L.

Int J Biochem Cell Biol. 2013 Nov;45(11):2574-9. doi: 10.1016/j.biocel.2013.08.014. Epub 2013 Sep 1. Review.

PMID:
24004832
10.

Poor-prognosis colon cancer is defined by a molecularly distinct subtype and develops from serrated precursor lesions.

De Sousa E Melo F, Wang X, Jansen M, Fessler E, Trinh A, de Rooij LP, de Jong JH, de Boer OJ, van Leersum R, Bijlsma MF, Rodermond H, van der Heijden M, van Noesel CJ, Tuynman JB, Dekker E, Markowetz F, Medema JP, Vermeulen L.

Nat Med. 2013 May;19(5):614-8. doi: 10.1038/nm.3174. Epub 2013 Apr 14.

PMID:
23584090
11.

Quantitative image analysis of cellular heterogeneity in breast tumors complements genomic profiling.

Yuan Y, Failmezger H, Rueda OM, Ali HR, Gräf S, Chin SF, Schwarz RF, Curtis C, Dunning MJ, Bardwell H, Johnson N, Doyle S, Turashvili G, Provenzano E, Aparicio S, Caldas C, Markowetz F.

Sci Transl Med. 2012 Oct 24;4(157):157ra143. doi: 10.1126/scitranslmed.3004330. Erratum in: Sci Transl Med. 2012 Oct 24;4(157):161er6.

12.

Posterior association networks and functional modules inferred from rich phenotypes of gene perturbations.

Wang X, Castro MA, Mulder KW, Markowetz F.

PLoS Comput Biol. 2012;8(6):e1002566. doi: 10.1371/journal.pcbi.1002566. Epub 2012 Jun 28.

13.

Diverse epigenetic strategies interact to control epidermal differentiation.

Mulder KW, Wang X, Escriu C, Ito Y, Schwarz RF, Gillis J, Sirokmány G, Donati G, Uribe-Lewis S, Pavlidis P, Murrell A, Markowetz F, Watt FM.

Nat Cell Biol. 2012 Jun 24;14(7):753-63. doi: 10.1038/ncb2520.

PMID:
22729083
14.

RedeR: R/Bioconductor package for representing modular structures, nested networks and multiple levels of hierarchical associations.

Castro MA, Wang X, Fletcher MN, Meyer KB, Markowetz F.

Genome Biol. 2012 Apr 24;13(4):R29. doi: 10.1186/gb-2012-13-4-r29.

15.

The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups.

Curtis C, Shah SP, Chin SF, Turashvili G, Rueda OM, Dunning MJ, Speed D, Lynch AG, Samarajiwa S, Yuan Y, Gräf S, Ha G, Haffari G, Bashashati A, Russell R, McKinney S; METABRIC Group, Langerød A, Green A, Provenzano E, Wishart G, Pinder S, Watson P, Markowetz F, Murphy L, Ellis I, Purushotham A, Børresen-Dale AL, Brenton JD, Tavaré S, Caldas C, Aparicio S.

Nature. 2012 Apr 18;486(7403):346-52. doi: 10.1038/nature10983.

16.

Patient-specific data fusion defines prognostic cancer subtypes.

Yuan Y, Savage RS, Markowetz F.

PLoS Comput Biol. 2011 Oct;7(10):e1002227. doi: 10.1371/journal.pcbi.1002227. Epub 2011 Oct 20.

17.

Penalized regression elucidates aberration hotspots mediating subtype-specific transcriptional responses in breast cancer.

Yuan Y, Rueda OM, Curtis C, Markowetz F.

Bioinformatics. 2011 Oct 1;27(19):2679-85. doi: 10.1093/bioinformatics/btr450. Epub 2011 Jul 30.

18.

A sparse regulatory network of copy-number driven gene expression reveals putative breast cancer oncogenes.

Yuan Y, Curtis C, Caldas C, Markowetz F.

IEEE/ACM Trans Comput Biol Bioinform. 2012 Jul-Aug;9(4):947-54. doi: 10.1109/TCBB.2011.105.

PMID:
21788678
19.

Differential C3NET reveals disease networks of direct physical interactions.

Altay G, Asim M, Markowetz F, Neal DE.

BMC Bioinformatics. 2011 Jul 21;12:296. doi: 10.1186/1471-2105-12-296.

20.

Deregulation upon DNA damage revealed by joint analysis of context-specific perturbation data.

Szczurek E, Markowetz F, Gat-Viks I, Biecek P, Tiuryn J, Vingron M.

BMC Bioinformatics. 2011 Jun 21;12:249. doi: 10.1186/1471-2105-12-249.

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