1Whitehead Institute for Biomedical Research, 9
2Computer Science and Artificial Intelligence
Laboratory, Massachusetts Institute of Technology,
3Dana-Farber Cancer Institute,
4Department of Statistics,
5Department of Genetics,
*To whom correspondence should be addressed, email: firstname.lastname@example.org
Paper as published in PLoS April 2009 - pdf
Supplementary figures & text:
FigS1.doc : Correlation between degrees and loss-of-function phenotypes.
FigS2.doc : Correlation between information flow scores and loss-of-function phenotypes among proteins of low or medium degrees.
FigS3.eps : Kirchhoffs current law: the basis for calculating information flow scores.
TextS1.doc : Toy networks used to illustrate the differences between information flow and betweenness.
TextS2.doc : Analysis of module size versus GO enrichment to determine appropriate size thresholds for module extraction algorithm.
Links to directories: