Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6853411 | Artificial Intelligence in Medicine | 2017 | 13 Pages |
Abstract
On a benchmark dataset composed of nine human networks and 708 medical subject headings (MeSH) diseases, Gene2DisCo largely outperformed the best benchmark algorithm, kernelized score functions, in terms of both area under the ROC curve (0.94 against 0.86) and precision at given recall levels (for recall levels from 0.1 to 1 with steps 0.1). Furthermore, we enriched and extended the benchmark data to the whole human genome and provided the top-ranked unannotated candidate genes even for MeSH disease terms without known annotations.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Marco Frasca,