Name
Abstract | ||
|---|---|---|
We investigated the possibility of gaining information on the mode of action of a set of compounds by means of Gene Ontology (GO) enrichment analysis.To this aim, we developed a new method, based on fuzzy-sets, which is able to compute sets of genes that are consistently differentially expressed when treating cells with the analyzed compounds. Then a Gene Ontology enrichment analysis is performed on these sets.The method has been tested on several different groups of drugs, whose similarity in mode of action has been predicted by a gene-expression based, unsupervised, approach and verified by searching literature.The obtained results show that GO terms that are over-represented in these fuzzy sets provide a quick and "easy-to-interpret" view of the mode of action of the analyzed drugs. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/IJCNN.2010.5596585 | 2010 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS IJCNN 2010 |
Keywords | Field | DocType |
genetics,biological processes,fuzzy set theory,mode of action,fuzzy set,clustering algorithms,fuzzy sets,proteins,gene expression | Data mining,Computer science,Gene ontology,Fuzzy logic,Mode (statistics),Fuzzy set,Artificial intelligence,Cluster analysis,Mode of action,Machine learning | Conference |
ISSN | Citations | PageRank |
2161-4393 | 0 | 0.34 |
References | Authors | |
2 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Francesco Iorio | 1 | 53 | 6.89 |
| Loredana Murino | 2 | 20 | 2.91 |
| Diego Di Bernardo | 3 | 244 | 22.35 |
| Giancarlo Raiconi | 4 | 118 | 15.08 |
| Roberto Tagliaferri | 5 | 428 | 55.64 |