An Integrated Molecular Atlas of Alzheimer’s Disease
Bibliographic record
Abstract
Abstract Alzheimer’s disease (AD) is a complex neurodegenerative disorder with multifactorial etiology and widespread molecular manifestations. Investigating molecular disease associations in a broader multi-level context across omics modalities remains one central challenge in AD research, despite the increasing availability of large-scale omics data. The AD Atlas, an online multi-omics resource, provides access to harmonized, disease-relevant data from over 25 large studies on 20,363 protein-coding genes, 8,396 proteins, 1,328 metabolites and 43 AD-related phenotypes interconnected by 979,190 significant associations. Results from AD-specific omics studies from AMP-AD, NIAGADS, and other initiatives are complemented with molecular associations from population-based studies in a comprehensive network resource to provide a genome-scale molecular view on AD. In a deep learning-based evaluation of the AD Atlas content, we demonstrate the utility of the network for data-driven identification of modules strongly enriched for AD-related functional domains. We provide full access to the AD Atlas at www.adatlas.org .
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".