PhenoNet: identification of key networks associated with disease phenotype

@article{BenHamo2014PhenoNetIO,
  title={PhenoNet: identification of key networks associated with disease phenotype},
  author={Rotem Ben-Hamo and Moriah Gidoni and Sol Efroni},
  journal={Bioinformatics},
  year={2014},
  volume={30 17},
  pages={
          2399-405
        }
}
MOTIVATION At the core of transcriptome analyses of cancer is a challenge to detect molecular differences affiliated with disease phenotypes. This approach has led to remarkable progress in identifying molecular signatures and in stratifying patients into clinical groups. Yet, despite this progress, many of the identified signatures are not robust enough to be clinically used and not consistent enough to provide a follow-up on molecular mechanisms. RESULTS To address these issues, we… 

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