Intra- and inter-multi-omics interaction analysis using deep learning
Clicks: 1
ID: 320510
2026
Article Quality & Performance Metrics
Overall Quality
0.0
/100
Combines engagement data with AI-assessed academic quality
Reader Engagement
0.0
/100
0 views
0 readers
AI Quality Assessment
Not analyzed
Mint this article as an NFT
Not yet mintedCreate a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.
5
SUSD
one-off · no wallet required
Abstract
Abstract Multi-omics interactions, including intra- and inter-omics interactions as well as socio-environmental influences, are key to uncovering molecular mechanisms that may be missed by individual omics analysis or conventional integration approaches. Deep learning offers a promising solution to overcome current limitations, including the complexity of modeling high-dimensional, nonlinear interactions, limited sample size and multiple testing burden.
| Reference Key |
openalex_W7167950531
Use this key to autocite in the manuscript while using
SciMatic Manuscript Manager or Thesis Manager
|
|---|---|
| Authors | Mingon Kang, Eunyoung Jang, Tesfaye B. Mersha |
| Journal | Bioinformatics advances |
| Year | 2026 |
| DOI |
10.1093/bioadv/vbag165
|
| URL | |
| Keywords | Keywords not found |
Citations
No citations found. To add a citation, contact the admin at info@scimatic.org
Comments
No comments yet. Be the first to comment on this article.