Benjamin Haibe-Kains

Summary

Affiliation: Harvard University
Country: USA

Publications

  1. pmc Multiple-input multiple-output causal strategies for gene selection
    Gianluca Bontempi
    Machine Learning Group, Computer Science Department, Universite Libre de Bruxelles, Belgium
    BMC Bioinformatics 12:458. 2011
  2. pmc A three-gene model to robustly identify breast cancer molecular subtypes
    Benjamin Haibe-Kains
    Department of Biostatistics and Computational Biology, Dana Farber Cancer Institute, Boston, MA 02115, USA
    J Natl Cancer Inst 104:311-25. 2012
  3. pmc Predictive networks: a flexible, open source, web application for integration and analysis of human gene networks
    Benjamin 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
  4. pmc Consistent metagenes from cancer expression profiles yield agent specific predictors of chemotherapy response
    Qiyuan Li
    Center for Biological Sequence Analysis, Department of Systems Biolology, Technical University of Denmark, 2800 Lyngby, Denmark
    BMC Bioinformatics 12:310. 2011
  5. pmc curatedOvarianData: clinically annotated data for the ovarian cancer transcriptome
    Benjamin Frederick Ganzfried
    Department of Biostatistics and Computational Biology, Dana Farber Cancer Institute, Boston, MA 02115, USA
    Database (Oxford) 2013:bat013. 2013
  6. pmc Stem cell-like gene expression in ovarian cancer predicts type II subtype and prognosis
    Matthew Schwede
    Biostatistics and Computational Biology, Dana Farber Cancer Institute, Boston, Massachusetts, United States of America
    PLoS ONE 8:e57799. 2013
  7. pmc GeneSigDB: a manually curated database and resource for analysis of gene expression signatures
    Aedin C Culhane
    Biostatistics and Computational Biology, Dana Farber Cancer Institute, 450 Brookline Avenue, Boston, MA 02215, USA
    Nucleic Acids Res 40:D1060-6. 2012
  8. pmc survcomp: an R/Bioconductor package for performance assessment and comparison of survival models
    Markus S Schröder
    Department of Biostatistics and Computational Biology, Dana Farber Cancer Institute, Boston, MA 02215, USA
    Bioinformatics 27:3206-8. 2011
  9. pmc Amplification of LAPTM4B and YWHAZ contributes to chemotherapy resistance and recurrence of breast cancer
    Yang Li
    Department of Cancer Biology, Dana Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts, USA
    Nat Med 16:214-8. 2010
  10. doi Elucidating prognosis and biology of breast cancer arising in young women using gene expression profiling
    Hatem 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

Collaborators

Detail Information

Publications11

  1. pmc Multiple-input multiple-output causal strategies for gene selection
    Gianluca 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...
  2. pmc A three-gene model to robustly identify breast cancer molecular subtypes
    Benjamin 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...
  3. pmc Predictive networks: a flexible, open source, web application for integration and analysis of human gene networks
    Benjamin 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/...
  4. pmc Consistent metagenes from cancer expression profiles yield agent specific predictors of chemotherapy response
    Qiyuan 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...
  5. pmc curatedOvarianData: clinically annotated data for the ovarian cancer transcriptome
    Benjamin Frederick Ganzfried
    Department of Biostatistics and Computational Biology, Dana Farber Cancer Institute, Boston, MA 02115, USA
    Database (Oxford) 2013:bat013. 2013
    ..The package and pipeline for producing it are available from http://bcb.dfci.harvard.edu/ovariancancer...
  6. pmc Stem cell-like gene expression in ovarian cancer predicts type II subtype and prognosis
    Matthew Schwede
    Biostatistics and Computational Biology, Dana Farber Cancer Institute, Boston, Massachusetts, United States of America
    PLoS ONE 8:e57799. 2013
    ....
  7. pmc GeneSigDB: a manually curated database and resource for analysis of gene expression signatures
    Aedin 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...
  8. pmc survcomp: an R/Bioconductor package for performance assessment and comparison of survival models
    Markus S Schröder
    Department of Biostatistics and Computational Biology, Dana Farber Cancer Institute, Boston, MA 02215, USA
    Bioinformatics 27:3206-8. 2011
    ....
  9. pmc Amplification of LAPTM4B and YWHAZ contributes to chemotherapy resistance and recurrence of breast cancer
    Yang 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...
  10. doi Elucidating prognosis and biology of breast cancer arising in young women using gene expression profiling
    Hatem 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...
  11. pmc Angiogenic mRNA and microRNA gene expression signature predicts a novel subtype of serous ovarian cancer
    Stefan 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...