A review of multi-omics integration techniques across five machine learning method families
Adedayo Olowolayemo, Amina Souag, Konstantinos Sirlantzis, Scott Turner, Cornelia Wilson · 2026
Read A review of multi-omics integration techniques across five machine learning method families by Adedayo Olowolayemo, Amina Souag, Konstantinos Sirlantzis, Scott Turner, Cornelia Wilson (2026) 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-13135628.txt.
Description
MotivationMulti-omics integration methods are now common in cancer studies, but results remain sensitive to design choices, including when fusion occurs, what is fused, and how missingness is handled. As a result, it is difficult to compare studies and determine which integration choices are most reliable for cross-cohort cancer analyses.
Catalog record
| CREATOR | Adedayo Olowolayemo, Amina Souag, Konstantinos Sirlantzis, Scott Turner, Cornelia Wilson |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 49 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |