Name
Title | ||
|---|---|---|
Metabolic networks classification and knowledge discovery by information granulation. |
Abstract | ||
|---|---|---|
•Novel information granulation and knowledge discovery technique for structured data.•Information granules as relevant substructures (high sensitivity and specificity).•Information granules are further filtered at classification stage (suboptimal subset).•Tests on real metabolic pathways data classification show remarkable performances.•Knowledge discovery over filtered granules paves the way for further studies. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1016/j.compbiolchem.2019.107187 | Computational Biology and Chemistry |
Keywords | Field | DocType |
68T10 (Pattern Recognition,Speech Recognition),62H30 (Classification and Discrimination,Cluster Analysis),05C82 (Small world graphs,complex networks),92C42 (Systems biology,networks) | Sensory cue,Graph,Biology,Discriminant,Semantic information,Knowledge extraction,Artificial intelligence,Mirroring,Genetics,Machine learning | Journal |
Volume | ISSN | Citations |
84 | 1476-9271 | 3 |
PageRank | References | Authors |
0.40 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Alessio Martino | 1 | 3 | 0.40 |
| Alessandro Giuliani | 2 | 170 | 25.21 |
| Virginia Todde | 3 | 3 | 0.40 |
| Mariano Bizzarri | 4 | 3 | 1.08 |
| Antonello Rizzi | 5 | 363 | 41.68 |