| Accession |
PRJCA035418 |
| Title |
Integrating Traditional Omics and Machine Learning Approaches to Identify Microbial Biomarkers and Therapeutic Targets in Pediatric Inflammatory Bowel Disease |
| Relevance |
Inflammatory Bowel Disease |
| Data types |
Raw sequence reads
|
| Organisms |
Colon
|
| Description |
This study demonstrates that integrating established biological techniques with AI-driven approaches can improve the accuracy and reproducibility of microbial biomarker discovery. Such strategies hold promises for guiding novel therapeutic interventions and informing precision medicine strategies in pediatric IBD. |
| Sample scope |
FECAL |
| Release date |
2025-01-22 |
| Publication |
|
| Grants |
| Agency |
program |
Grant ID |
Grant title |
| No funding support
|
|
|
|
|
|
| Submitter |
Tao
Huang (24867509@qq.com)
|
| Organization |
Maternal and Child Health Hospital of Hubei Province |
| Submission date |
2025-01-22 |
