Edoardo M Airoldi

Summary

Affiliation: Princeton University
Country: USA

Publications

  1. ncbi Getting started in probabilistic graphical models
    Edoardo M Airoldi
    Lewis-Sigler Institute for Integrative Genomics and Computer Science Department, Princeton University, Princeton, New Jersey, United States of America
    PLoS Comput Biol 3:e252. 2007
  2. ncbi Predicting cellular growth from gene expression signatures
    Edoardo M Airoldi
    Lewis Sigler Institute for Integrative Genomics, Carl Icahn Laboratory, Princeton University, Princeton, New Jersey, United States of America
    PLoS Comput Biol 5:e1000257. 2009
  3. ncbi Aneuploidy prediction and tumor classification with heterogeneous hidden conditional random fields
    Zafer Barutcuoglu
    Department of Computer Science, Princeton University, 35 Olden Street, Princeton, NJ 08540, USA
    Bioinformatics 25:1307-13. 2009
  4. ncbi A new machine learning classifier for high dimensional healthcare data
    Rema Padman
    The H John Heinz III School of Public Policy and Management, Carnegie Mellon University, Pittsburgh, PA 15213, USA
    Stud Health Technol Inform 129:664-8. 2007

Collaborators

Detail Information

Publications4

  1. ncbi Getting started in probabilistic graphical models
    Edoardo M Airoldi
    Lewis-Sigler Institute for Integrative Genomics and Computer Science Department, Princeton University, Princeton, New Jersey, United States of America
    PLoS Comput Biol 3:e252. 2007
  2. ncbi Predicting cellular growth from gene expression signatures
    Edoardo M Airoldi
    Lewis Sigler Institute for Integrative Genomics, Carl Icahn Laboratory, Princeton University, Princeton, New Jersey, United States of America
    PLoS Comput Biol 5:e1000257. 2009
    ..Data and tools enabling others to apply our methods are available at http://function.princeton.edu/growthrate...
  3. ncbi Aneuploidy prediction and tumor classification with heterogeneous hidden conditional random fields
    Zafer Barutcuoglu
    Department of Computer Science, Princeton University, 35 Olden Street, Princeton, NJ 08540, USA
    Bioinformatics 25:1307-13. 2009
    ..We also demonstrate that it can be used to generate novel biological hypotheses for breast cancer...
  4. ncbi A new machine learning classifier for high dimensional healthcare data
    Rema Padman
    The H John Heinz III School of Public Policy and Management, Carnegie Mellon University, Pittsburgh, PA 15213, USA
    Stud Health Technol Inform 129:664-8. 2007
    ..Furthermore, it has comparable or better prediction performance when compared against several machine learning methods, and provides insight into possible causal relations among the variables...