Name
Abstract | ||
|---|---|---|
The increasing amount of peer-reviewed manuscripts requires the development of specific mining tools to facilitate the visual exploration of evidence linking diseases and proteins. Results: We developed TIN-X, the Target Importance and Novelty eXplorer, to visualize the association between proteins and diseases, based on text mining data processed from scientific literature. In the current implementation, TIN-X supports exploration of data for G-protein coupled receptors, kinases, ion channels, and nuclear receptors. TIN-X supports browsing and navigating across proteins and diseases based on ontology classes, and displays a scatter plot with two proposed new bibliometric statistics: Importance and Novelty. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1093/bioinformatics/btx200 | BIOINFORMATICS |
Field | DocType | Volume |
Data mining,Tin,Computer science,Novelty | Journal | 33 |
Issue | ISSN | Citations |
16 | 1367-4803 | 1 |
PageRank | References | Authors |
0.35 | 2 | 11 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Daniel C. Cannon | 1 | 10 | 1.89 |
| Jeremy J. Yang | 2 | 43 | 4.62 |
| Stephen L. Mathias | 3 | 36 | 4.80 |
| Oleg Ursu | 4 | 39 | 4.57 |
| S Mani | 5 | 391 | 30.95 |
| Anna Waller | 6 | 1 | 1.03 |
| Stephan C Schürer | 7 | 131 | 14.74 |
| Lars Juhl Jensen | 8 | 2202 | 137.56 |
| Larry A. Sklar | 9 | 14 | 2.18 |
| Cristian Bologa | 10 | 29 | 3.54 |
| Tudor I Oprea | 11 | 359 | 46.89 |