Aedin Culhane

Senior 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

de Velasco G, Culhane AC, Fay AP, Hakimi AA, Voss MH, Tannir NM, Tamboli P,
Appleman LJ, Bellmunt J, Kimryn Rathmell W, Albiges L, Hsieh JJ, Heng DY,
Signoretti S, Choueiri TK. Molecular Subtypes Improve Prognostic Value of
International Metastatic Renal Cell Carcinoma Database Consortium Prognostic
Model. Oncologist. 2017 Mar;22(3):286-292.

 

Meng C, Culhane A. Integrative Exploratory Analysis of Two or More Genomic
Datasets. Methods Mol Biol. 2016;1418:19-38.

 

Meng C, Zeleznik OA, Thallinger GG, Kuster B, Gholami AM, Culhane AC.
Dimension reduction techniques for the integrative analysis of multi-omics data.
Brief Bioinform. 2016 Jul;17(4):628-41.

 

Neupane M, Clark AP, Landini S, Birkbak NJ, Eklund AC, Lim E, Culhane AC,
Barry WT, Schumacher SE, Beroukhim R, Szallasi Z, Vidal M, Hill DE, Silver DP.
MECP2 Is a Frequently Amplified Oncogene with a Novel Epigenetic Mechanism That Mimics the Role of Activated RAS in Malignancy. Cancer Discov. 2016
Jan;6(1):45-58.

 

Kannan L, Ramos M, Re A, El-Hachem N, Safikhani Z, Gendoo DM, Davis S,
Gomez-Cabrero D, Castelo R, Hansen KD, Carey VJ, Morgan M, Culhane AC,
Haibe-Kains B, Waldron L. Public data and open source tools for multi-assay
genomic investigation of disease. Brief Bioinform. 2016 Jul;17(4):603-15.

 

Kochupurakkal BS, Wang ZC, Hua T, Culhane AC, Rodig SJ, Rajkovic-Molek K,
Lazaro JB, Richardson AL, Biswas DK, Iglehart JD. RelA-Induced Interferon
Response Negatively Regulates Proliferation. PLoS One. 2015 Oct
13;10(10):e0140243.

 

Meng C, Kuster B, Culhane AC, Gholami AM. A multivariate approach to the
integration of multi-omics datasets. BMC Bioinformatics. 2014 May 29;15:162.

Riester M, Wei W, Waldron L, Culhane AC, Trippa L, Oliva E, Kim SH, Michor F,
Huttenhower C, Parmigiani G, Birrer MJ. Risk prediction for late-stage ovarian
cancer by meta-analysis of 1525 patient samples. J Natl Cancer Inst. 2014 Apr
3;106(5).

 

Waldron L, Haibe-Kains B, Culhane AC, Riester M, Ding J, Wang XV, Ahmadifar M,
Tyekucheva S, Bernau C, Risch T, Ganzfried BF, Huttenhower C, Birrer M,
Parmigiani G. Comparative meta-analysis of prognostic gene signatures for
late-stage ovarian cancer. J Natl Cancer Inst. 2014 Apr 3;106(5).

 

Santagata S, Thakkar A, Ergonul A, Wang B, Woo T, Hu R, Harrell JC, McNamara
G, Schwede M, Culhane AC, Kindelberger D, Rodig S, Richardson A, Schnitt SJ,
Tamimi RM, Ince TA. Taxonomy of breast cancer based on normal cell phenotype
predicts outcome. J Clin Invest. 2014 Feb;124(2):859-70.

 

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