Particle picking by segmentation: a comparative study with SPIDER-based manual particle picking.

TitleParticle picking by segmentation: a comparative study with SPIDER-based manual particle picking.
Publication TypeJournal Article
Year of Publication2005
AuthorsAdiga, U, Baxter, B, Hall, RJ, Rockel, B, Rath, BK, Frank, J, Glaeser, RM
JournalJ Struct Biol
Volume152
Issue3
Pagination211-20
Date Published12/2005
ISSN1047-8477
KeywordsAlgorithms, Aminopeptidases, Cryoelectron Microscopy, Dipeptidyl-Peptidases and Tripeptidyl-Peptidases, Image Processing, Computer-Assisted, Imaging, Three-Dimensional, Internet, Particle Size, Ribosomes, Serine Endopeptidases, Software, Software Validation
Abstract

Boxing hundreds of thousands of particles in low-dose electron micrographs is one of the major bottle-necks in advancing toward achieving atomic resolution reconstructions of biological macromolecules. We have shown that a combination of pre-processing operations and segmentation can be used as an effective, automatic tool for identifying and boxing single-particle images. This paper provides a brief description of how this method has been applied to a large data set of micrographs of ice-embedded ribosomes, including a comparative analysis of the efficiency of the method. Some results on processing micrographs of tripeptidyl peptidase II particles are also shown. In both cases, we have achieved our goal of selecting at least 80% of the particles that an expert would select with less than 10% false positives.

URLhttp://www.ncbi.nlm.nih.gov/pubmed/16330229
DOI10.1016/j.jsb.2005.09.007
Alternate JournalJ. Struct. Biol.
PubMed ID16330229

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