[PSI]-CIC: A Deep-Learning Pipeline for the Annotation of Sectored Saccharomyces cerevisiae Colonies
Jordan Collignon, Wesley Naeimi, Tricia R Serio, Suzanne Sindi · 2024
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Description
Yeast colonies carrying the [PSI+] prion grow white, but treatments that cure the prion leave red sectors inside the white, like slices of a pie. Jordan Collignon and co-authors build the first computer pipeline to measure those sectors. Sector sizes and counts carry clues about how curing works at the molecular level, yet older lab routines ignore colony patterns.
Lacking hand-labeled examples, the team trained their neural network on synthetic colony images, then turned it loose on real ones. On hand-checked experimental images, the pipeline named the state of about ninety-five percent of colonies correctly and judged sector frequency correctly in about eighty-nine and a half percent. The authors note the tool can be extended across growing conditions, letting experiments be compared in fine detail. They offer it as a way to turn colony photographs into hard numbers on prion curing.
Catalog record
| CREATOR | Jordan Collignon, Wesley Naeimi, Tricia R Serio, Suzanne Sindi |
|---|---|
| YEAR | 2024 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 86 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |