Name
Title | ||
|---|---|---|
iLncRNAdis-FB: Identify lncRNA-Disease Associations by Fusing Biological Feature Blocks Through Deep Neural Network |
Abstract | ||
|---|---|---|
Identification of lncRNA-disease associations is not only important for exploring the disease mechanism, but will also facilitate the molecular targeting drug discovery. Fusing multiple biological information is able to generate a more comprehensive view of lncRNA-disease association feature. However, the existing fusion strategies in this field fail to remove the noisy and irrelevant information ... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/TCBB.2020.2964221 | IEEE/ACM Transactions on Computational Biology and Bioinformatics |
Keywords | DocType | Volume |
Diseases,Biology,Kernel,Semantics,Benchmark testing,Feature extraction,Matrix decomposition | Journal | 18 |
Issue | ISSN | Citations |
5 | 1545-5963 | 3 |
PageRank | References | Authors |
0.38 | 0 | 3 |