Affiliation: Harvard University
- Multiple-input multiple-output causal strategies for gene selectionGianluca Bontempi
Machine Learning Group, Computer Science Department, Universite Libre de Bruxelles, Belgium
BMC Bioinformatics 12:458. 2011..In this study, we show how to efficiently incorporate causal information into gene selection by moving from a single-input single-output to a multiple-input multiple-output setting...
- A three-gene model to robustly identify breast cancer molecular subtypesBenjamin Haibe-Kains
Department of Biostatistics and Computational Biology, Dana Farber Cancer Institute, Boston, MA 02115, USA
J Natl Cancer Inst 104:311-25. 2012..The aim of this study was to compare the robustness, classification concordance, and prognostic value of these classifiers with those of a simplified three-gene SCM in a large compendium of microarray datasets...
- Predictive networks: a flexible, open source, web application for integration and analysis of human gene networksBenjamin Haibe-Kains
Department of Biostatistics and Computational Biology, Dana Farber Cancer Institute, Harvard School of Public Health, Boston, MA 02215, USA, USA
Nucleic Acids Res 40:D866-75. 2012..The PN web application is accessible from http://predictivenetworks.org. The PN code base is freely available at https://sourceforge.net/projects/predictivenets/...
- Consistent metagenes from cancer expression profiles yield agent specific predictors of chemotherapy responseQiyuan Li
Center for Biological Sequence Analysis, Department of Systems Biolology, Technical University of Denmark, 2800 Lyngby, Denmark
BMC Bioinformatics 12:310. 2011..However, identification of clinically predictive or prognostic classifiers can be challenging when a large number of genes are measured in a small number of tumors...
- Stem Cell-Like Gene Expression in Ovarian Cancer Predicts Type II Subtype and PrognosisMatthew Schwede
Biostatistics and Computational Biology, Dana Farber Cancer Institute, Boston, Massachusetts, United States of America
PLoS ONE 8:e57799. 2013....
- GeneSigDB: a manually curated database and resource for analysis of gene expression signaturesAedin C Culhane
Biostatistics and Computational Biology, Dana Farber Cancer Institute, 450 Brookline Avenue, Boston, MA 02215, USA
Nucleic Acids Res 40:D1060-6. 2012..All data in GeneSigDB can be downloaded in numerous formats including .gmt file format for gene set enrichment analysis or as a R/Bioconductor data file. GeneSigDB is available from http://www.genesigdb.org...
- survcomp: an R/Bioconductor package for performance assessment and comparison of survival modelsMarkus S Schröder
Department of Biostatistics and Computational Biology, Dana Farber Cancer Institute, Boston, MA 02215, USA
Bioinformatics 27:3206-8. 2011....
- Amplification of LAPTM4B and YWHAZ contributes to chemotherapy resistance and recurrence of breast cancerYang Li
Department of Cancer Biology, Dana Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts, USA
Nat Med 16:214-8. 2010..Overexpression of these two genes may predict anthracycline resistance and influence selection of chemotherapy...
- Elucidating prognosis and biology of breast cancer arising in young women using gene expression profilingHatem A Azim
Breast Cancer Translational Research Laboratory BCTL J C Heuson, Institut Jules Bordet, Universite Libre de Bruxelles, Brussels, Belgium
Clin Cancer Res 18:1341-51. 2012..Breast cancer in young women is associated with poor prognosis. We aimed to define the role of gene expression signatures in predicting prognosis in young women and to understand biological differences according to age...
- curatedOvarianData: clinically annotated data for the ovarian cancer transcriptomeBenjamin Frederick Ganzfried
Department of Biostatistics and Computational Biology, Dana Farber Cancer Institute, Boston, MA, 02115
Database (Oxford) 2013:bat013. 2013..The package and pipeline for producing it are available from http://bcb.dfci.harvard.edu/ovariancancer. Database URL: http://bcb.dfci.harvard.edu/ovariancancer...
- Angiogenic mRNA and microRNA gene expression signature predicts a novel subtype of serous ovarian cancerStefan Bentink
Department of Biostatistics and Computational Biology, Dana Farber Cancer Institute, Boston, Massachusetts, United States of America
PLoS ONE 7:e30269. 2012..The subtypes we have defined are of potential translational interest as they may be relevant for identifying patients who may benefit from the addition of anti-angiogenic therapies that are now being tested in clinical trials...