Genome-wide association neural networks identify genes linked to family history of Alzheimer’s disease
Upamanyu Ghose, William Sproviero, Laura Winchester, Najaf Amin, Taiyu Zhu, Danielle Newby, Brittany S Ulm, Angeliki Papathanasiou, Liu Shi, Qiang Liu, Marco Fernandes, Cassandra Adams, Ashwag Albukhari, Majid Almansouri, Hani Choudhry, Cornelia van Duijn, Alejo Nevado-Holgado · 2025
Read Genome-wide association neural networks identify genes linked to family history of Alzheimer’s disease by Upamanyu Ghose, William Sproviero, Laura Winchester, Najaf Amin, Taiyu Zhu, Danielle Newby, Brittany S Ulm, Angeliki Papathanasiou, Liu Shi, Qiang Liu, Marco Fernandes, Cassandra Adams, Ashwag Albukhari, Majid Almansouri, Hani Choudhry, Cornelia van Duijn, Alejo Nevado-Holgado (2025) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-11707606.txt.
Description
Augmenting traditional genome-wide association studies (GWAS) with advanced machine learning algorithms can allow the detection of novel signals in available cohorts. We introduce “genome-wide association neural networks (GWANN)” a novel approach that uses neural networks (NNs) to perform a gene-level association study with family history of Alzheimer’s disease (AD).
Catalog record
| CREATOR | Upamanyu Ghose, William Sproviero, Laura Winchester, Najaf Amin, Taiyu Zhu, Danielle Newby, Brittany S Ulm, Angeliki Papathanasiou, Liu Shi, Qiang Liu, Marco Fernandes, Cassandra Adams, Ashwag Albukhari, Majid Almansouri, Hani Choudhry, Cornelia van Duijn, Alejo Nevado-Holgado |
|---|---|
| YEAR | 2025 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 36 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |