Aedin Culhane

Research Scientist
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My Website

 

Research


Application of multivariate statistical methods and machine learning to the analysis of high-throughput data arising from genomic, transcriptomic and proteomic studies of cancer, with a particular focus on meta analysis and integration of microarray data from multiple studies, to further our understanding of

  • molecular heterogeneity of tumor subtypes
  • cancer microenvironment in breast and ovarian cancer. 

 

Biography

BSc 1994 University of Limerick, Ireland
PhD. 2000 University of Manchester, UK 

 

Recent Publications

Bowman-Colin C, Xia B, Bunting S, Klijn C, Drost R, Bouwman P, Fineman L, Chen X, Culhane AC, Cai H, Rodig SJ, Bronson RT, Jonkers J, Nussenzweig A, Kanellopoulou C, Livingston DM. Palb2 synergizes with Trp53 to suppress mammary tumor formation in a model of inherited breast cancer. Proc Natl Acad Sci U S A. 2013 May 8.

 

Schwede M, Spentzos D, Bentink S, Hofmann O, Haibe-Kains B, Harrington D, Quackenbush J, Culhane AC. Stem cell-like gene expression in ovarian cancer predicts type II subtype and prognosis. PLoS One. 2013;8(3):e57799.

 

Beck AH, Knoblauch NW, Hefti MM, Kaplan J, Schnitt SJ, Culhane AC, Schroeder MS, Risch T, Quackenbush J, Haibe-Kains B. Significance analysis of prognostic signatures. PLoS Comput Biol. 2013 Jan;9(1):e1002875.

 

Kelly AD, Haibe-Kains B, Janeway KA, Hill KE, Howe E, Goldsmith J, Kurek K,Perez-Atayde AR, Francoeur N, Fan JB, April C, Schneider H, Gebhardt MC, Culhane A, Quackenbush J, Spentzos D. MicroRNA paraffin-based studies in osteosarcoma reveal reproducible independent prognostic profiles at 14q32. Genome Med. 2013 Jan 22;5(1):2.

 

Schröder MS, Gusenleitner D, Quackenbush J, Culhane AC, Haibe-Kains B. RamiGO:an R/Bioconductor package providing an AmiGO visualize interface. Bioinformatics. 2013 Mar 1;29(5):666-8.

 

Wang ZC, Birkbak NJ, Culhane AC, Drapkin R, Fatima A, Tian R, Schwede M, Alsop K, Daniels KE, Piao H, Liu J, Etemadmoghadam D, Miron A, Salvesen HB, Mitchell G, DeFazio A, Quackenbush J, Berkowitz RS, Iglehart JD, Bowtell DD; Australian Ovarian Cancer Study Group, Matulonis UA. Profiles of genomic instability in high-grade serous ovarian cancer predict treatment outcome. Clin Cancer Res. 2012 Oct 15;18(20):5806-15.

 

Gusenleitner D, Howe EA, Bentink S, Quackenbush J, Culhane AC. iBBiG:
iterative binary bi-clustering of gene sets. Bioinformatics. 2012 Oct
1;28(19):2484-92. Epub 2012 Jul 12.

 

Bentink S, Haibe-Kains B, Risch T, Fan JB, Hirsch MS, Holton K, Rubio R, April C, Chen J, Wickham-Garcia E, Liu J, Culhane A, Drapkin R, Quackenbush J, Matulonis UA. Angiogenic mRNA and microRNA gene expression signature predicts a novel subtype of serous ovarian cancer. PLoS One. 2012;7(2):e30269.

 

Haibe-Kains B, Desmedt C, Loi S, Culhane AC, Bontempi G, Quackenbush J, Sotiriou C. A three-gene model to robustly identify breast cancer molecular subtypes. J Natl Cancer Inst. 2012 Feb 22;104(4):311-25.

 

Ho Sui SJ, Begley K, Reilly D, Chapman B, McGovern R, Rocca-Sera P, Maguire E, Altschuler GM, Hansen TA, Sompallae R, Krivtsov A, Shivdasani RA, Armstrong SA, Culhane AC, Correll M, Sansone SA, Hofmann O, Hide W. The Stem Cell Discovery Engine: an integrated repository and analysis system for cancer stem cell comparisons. Nucleic Acids Res. 2012 Jan;40(Database issue):D984-91.

 

Related Links


GeneSigDB

Gene Signature Database is a searchable database of manually curated gene expression signatures which we have collected from the literature. Release 1.0 (Aug 2009) contains over 560 gene signature which focus on breast, ovarian and other cancers and stem cell gene signatures.

 

Made4

made4 is a Bioconductor package which I develop and maintain. made4 is an extension to ade4, and provides functions to perform between group analysis, coinertia analysis and other methods we have described. It provides many visualization functions, including heatplot (adapted heatmap which includes a scale bar and sample/gene color bar), pretty.dend  (dendrogram with covariate colorbars), and functions to view the results of prinipcal component analysis or correspondence analysis in 1D, 2D or 3D plots.

 

DFCI

The Department of Biostatistics and Computational Biology at Dana-Farber Cancer Institute

The Women's Cancer Program at Dana-Farber Cancer Institute

 

Lab Groups

The Computational Biology and Functional Genomics Laboratory - See more about the projects I am working on in Prof. John Quackenbush's Computational Biology and Functional Genomics Laboratory at Dana-Farber Cancer Institute.

Prof Des Higgins, Conway Institute, University College Dublin, Ireland - I am collaborating with Prof Des Higgins (UCD) in the development and application of multivariate methods for the analysis of high throughout genomic and proteomic data.

 

HSPH

My Harvard School of Public Health Page