תקציר
Particle picking is a crucial first step in the computational pipeline of single-particle cryo-electron microscopy (cryo-EM). Selecting particles from the micrographs is difficult especially for small particles with low contrast. As high-resolution reconstruction typically requires hundreds of thousands of particles, manually picking that many particles is often too time-consuming. While template-based particle picking is currently a popular approach, it may suffer from introducing manual bias into the selection process. In addition, this approach is still somewhat time-consuming. This paper presents the APPLE (Automatic Particle Picking with Low user Effort) picker, a simple and novel approach for fast, accurate, and template-free particle picking. This approach is evaluated on publicly available datasets containing micrographs of β-galactosidase, T20S proteasome, 70S ribosome and keyhole limpet hemocyanin projections.
| שפה מקורית | אנגלית |
|---|---|
| עמודים (מ-עד) | 215-227 |
| מספר עמודים | 13 |
| כתב עת | Journal of Structural Biology |
| כרך | 204 |
| מספר גיליון | 2 |
| מזהי עצם דיגיטלי (DOIs) | |
| סטטוס פרסום | פורסם - נוב׳ 2018 |
| פורסם באופן חיצוני | כן |
טביעת אצבע
להלן מוצגים תחומי המחקר של הפרסום 'APPLE picker: Automatic particle picking, a low-effort cryo-EM framework'. יחד הם יוצרים טביעת אצבע ייחודית.פורמט ציטוט ביבליוגרפי
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