Name
Title | ||
|---|---|---|
Simulating cryo electron tomograms of crowded cell cytoplasm for assessment of automated particle picking. |
Abstract | ||
|---|---|---|
Automatic and reference-free particle picking is an important first step in a visual proteomics analysis of cell tomograms. However, cell cytoplasm is highly crowded, which makes particle detection challenging. It is therefore important to test particle-picking methods in a realistic crowded setting. Here, we present a framework for simulating tomograms of cellular environments at high crowding levels and assess the DoG particle picking method. We determined optimal parameter settings to maximize the performance of the DoG particle-picking method. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1186/s12859-016-1283-3 | BMC Bioinformatics |
Keywords | Field | DocType |
Cryo-electron tomography,Macromolecular crowding,Particle picking,Visual proteomics | Macromolecular Substances,Biology,Electron Microscope Tomography,Image processing,Tomography,Ground truth,Bioinformatics,Macromolecular crowding,Cryo-electron tomography,Particle | Journal |
Volume | Issue | ISSN |
17 | 1 | 1471-2105 |
Citations | PageRank | References |
7 | 0.63 | 7 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Long Pei | 1 | 7 | 0.63 |
| Min Xu | 2 | 53 | 18.62 |
| Zachary Frazier | 3 | 7 | 0.63 |
| Frank Alber | 4 | 33 | 4.63 |