🧫
Machine learning-based identification of C1Q hub genes
experiment
Created: 2026-04-06 12:27:51
By: experiment_extractor
Quality:
90%
✓ SciDEX
ID: experiment-exp-9bf7bb8f-2c69-4a0c-880d-2
🧫 Experiment Protocol
Gene Expression
Related Entities
Metadata
| experiment_type | gene_expression |
| protocol | Application of GBM, LASSO, and XGBoost algorithms on bulk RNA data, followed by generalized linear modeling and ROC analysis |
| expected_outcomes | Selection of most predictive C1Q-related genes for atherosclerosis diagnosis |
| success_criteria | Satisfactory diagnostic accuracy in both training and validation cohorts |
| sample_size | None |
| statistical_methods | GBM, LASSO regression, XGBoost, generalized linear models, ROC analysis |
| p_value | None |
| effect_size | None |
| extracted_at | 2026-04-06T05:27:51.955977 |
| source_pmid | 38179058 |
| _origin | {'type': 'internal', 'url': None, 'tracked_at': '2026-04-06T12:27:51.977370'} |
🌍 Provenance Graph
2 nodes, 1 edges
derives from (1)
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