BIOREL: The benchmark resource to estimate the relevance of the gene networks
- 18 January 2006
- journal article
- Published by Wiley in FEBS Letters
- Vol. 580 (3) , 844-848
- https://doi.org/10.1016/j.febslet.2005.12.101
Abstract
The progress of high-throughput methodologies in functional genomics has lead to the development of statistical procedures to infer gene networks from various types of high-throughput data. However, due to the lack of common standards, the biological significance of the results of the different studies is hard to compare. To overcome this problem we propose a benchmark procedure and have developed a web resource (BIOREL), which is useful for estimating the biological relevance of any genetic network by integrating different sources of biological information. The associations of each gene from the network are classified as biologically relevant or not. The proportion of genes in the network classified as “relevant” is used as the overall network relevance score. Employing synthetic data we demonstrated that such a score ranks the networks fairly in respect to the relevance level. Using BIOREL as the benchmark resource we compared the quality of experimental and theoretically predicted protein interaction dataKeywords
This publication has 13 references indexed in Scilit:
- Inferring protein–protein interactions through high-throughput interaction data from diverse organismsBioinformatics, 2005
- Binding properties and evolution of homodimers in protein-protein interaction networksNucleic Acids Research, 2005
- Predicting gene regulation by sigma factors in Bacillus subtilis from genome-wide dataBioinformatics, 2004
- Discovery of meaningful associations in genomic data using partial correlation coefficientsBioinformatics, 2004
- Modeling T-cell activation using gene expression profiling and state-space modelsBioinformatics, 2004
- Inferring Cellular Networks Using Probabilistic Graphical ModelsScience, 2004
- MIPS: analysis and annotation of proteins from whole genomesNucleic Acids Research, 2004
- Inferring Domain–Domain Interactions From Protein–Protein InteractionsGenome Research, 2002
- Comparative assessment of large-scale data sets of protein–protein interactionsNature, 2002
- A comprehensive two-hybrid analysis to explore the yeast protein interactomeProceedings of the National Academy of Sciences, 2001