Name
Abstract | ||
|---|---|---|
Motivation: Assessing functional associations between an experimentally derived gene or protein set of interest and a database of known gene/protein sets is a common task in the analysis of large-scale functional genomics data. For this purpose, a frequently used approach is to apply an over-representation-based enrichment analysis. However, this approach has four drawbacks: (i) it can only score functional associations of overlapping gene/proteins sets; (ii) it disregards genes with missing annotations; (iii) it does not take into account the network structure of physical interactions between the gene/protein sets of interest and (iv) tissue-specific gene/protein set associations cannot be recognized. Results: To address these limitations, we introduce an integrative analysis approach and web-application called EnrichNet. It combines a novel graph-based statistic with an interactive sub-network visualization to accomplish two complementary goals: improving the prioritization of putative functional gene/protein set associations by exploiting information from molecular interaction networks and tissue-specific gene expression data and enabling a direct biological interpretation of the results. By using the approach to analyse sets of genes with known involvement in human diseases, new pathway associations are identified, reflecting a dense sub-network of interactions between their corresponding proteins. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1093/bioinformatics/bts389 | BIOINFORMATICS |
Keywords | Field | DocType |
gene regulatory networks,genes,gene expression profiling,internet | Data mining,Gene,Statistic,Visualization,Computer science,Gene expression,Functional genomics,Bioinformatics,Overlapping gene,Gene regulatory network,Gene expression profiling | Journal |
Volume | Issue | ISSN |
28 | 18 | 1367-4803 |
Citations | PageRank | References |
47 | 1.98 | 22 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Enrico Glaab | 1 | 123 | 7.68 |
| Anaïs Baudot | 2 | 107 | 6.83 |
| Natalio Krasnogor | 3 | 1213 | 85.53 |
| Reinhard Schneider | 4 | 475 | 28.53 |
| Alfonso Valencia | 5 | 2577 | 322.43 |