Update announcement: the latest version of YeastNet (v3) is now available from here.
Networks: v. 2
Applications: Phenotype Prediction
YeastNet v. 2
YeastNet v. 2 is a probabilistic functional gene network of yeast genes, constructed from
~1.8 million expermental observations from DNA microarrays, physical protein interactions,
genetic interactions, literature, and comparative genomics methods. In total, YeastNet v.2
covers 102,803 linkages among 5,483 yeast proteins (95% of the validated proteome).
YeastNet was constructed using a modified Bayesian integration of diverse data types,
with each data type weighted according to how well it links genes that are known to share
functions. Each interaction in YeastNet has an associated log-likelihood score (LLS) that
measures the probability of an interaction representing a true functional linkage between two genes.
YeastNet v. 2 reference:
Lee, I., Li, Z. and Marcotte, E. M.
. An improved, bias-reduced probabilistic functional gene network of baker's yeast, Saccharomyces cerevisiae
2007 2(10):e988). Download here
Download the network interactions:
Benchmark set, common gene names (approx. 0.7MB).
Benchmark set, systematic orf names (approx. 1.1MB).
Full network, common gene names (approx. 2.9MB).
Full network, systematic orf names (approx. 3.4MB).
Evidence for each link, common gene names (approx. 7.8MB).
Evidence for each link, systematic orf names (approx. 8.3MB).
A web server to search the network interactively will be added shortly.
Evidence in YeastNet v. 2 derives from the following datasets, listed in the order used in the evidence file (followed by the overall LLS score):
Co-citation of yeast genes
Co-expression among yeast genes (500 microarray datasets)
Gene neighbourhoods of bacterial and archaeal orthologs
Yeast genetic interactions (multiple datasets)
Literature curated yeast protein interactions
Protein complexes from affinity purification/mass spectrometry (multiple datasets)
Co-inheritance of bacterial orthologs of yeast genes
Rosetta Stone protein-based functional linkages
Protein interactions inferred from tertiary structures of complexes
High-throughput yeast 2-hybrid assays (multiple datasets)
Network Based Phenotype Prediction
We demonstrate that loss-of-function yeast phenotypes are predictable by guilt-by-association
in functional gene networks. Testing 1,102 loss-of-function phenotypes from genome-wide
assays of yeast reveals predictability of diverse phenotypes, spanning cellular morphology,
growth, metabolism, and quantitative cell shape features. We apply the method to (1) extend
a genome-wide screen by predicting, then verifying, genes whose disruption elongates yeast
cells, and (2) predict human disease genes.
Yeast network-based phenotype prediction reference:
McGary, K. L., Lee, I., and Marcotte, E. M.
Broad network-based predictability of Saccharomyces cerevisiae
gene loss-of-function phenotypes (Genome Biology
2007 8(12):R258) Download here