A hypercubic Mk model framework for capturing reversibility in disease, cancer, and evolutionary accumulation modelling
Iain G Johnston, Ramon Diaz-Uriarte, Russell Schwartz · 2024
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Description
Iain Johnston and co-authors adapt a classic evolution model to track how features pile up and sometimes vanish, in a 2024 paper. Cancer growth and drug resistance are often read as one way gains of traits. Real systems can lose a trait too, which most inference tools forbid.
Their frame sets the Mk model on a hypercube graph, where each corner is a set of traits and each edge a gain or a loss. It handles tangled interactions among many traits and messy data: one time snapshots, series, or tree shaped samples. Tests on made up data, bacterial resistance, and cancer series show it works. Free code in R is posted.
Catalog record
| CREATOR | Iain G Johnston, Ramon Diaz-Uriarte, Russell Schwartz |
|---|---|
| YEAR | 2024 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 37 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |