Maskiton: Interactive, web-based classification of single-particle electron microscopy images

Craig Yoshioka, Dmitry Lyumkis, Bridget Carragher, Clinton S. Potter

Research output: Contribution to journalArticle

3 Scopus citations

Abstract

Electron microscopy (EM) is an important tool for determining the composition, arrangement and structure of biological macromolecules. When studying structurally heterogeneous samples using EM, classification is a critical step toward achieving higher resolution and identifying biologically significant conformations. We have developed an interactive, web-based tool, called Maskiton, for creating custom masks and performing 2D classifications on aligned single-particle EM images. The Maskiton interface makes it considerably easier and faster to explore the significance of heterogeneity in single-particle datasets. Maskiton features include: resumable uploads to facilitate transfer of large datasets to the server, custom mask creation in the browser, continual progress updates, and interactive viewing of classification results. To demonstrate the value of this tool, we provide examples of its use on several experimental datasets and include analyses of the independent terminus mobility within the Ltn1 E3 ubiquitin ligase, the in vitro assembly of 30S ribosomal subunits, and classification complexity reduction within Immunoglobulin M. This work also serves as a proof-of-concept for the development of future cross-platform, interactive user interfaces for electron microscopy data processing.

Original languageEnglish (US)
Pages (from-to)155-163
Number of pages9
JournalJournal of Structural Biology
Volume182
Issue number2
DOIs
StatePublished - May 1 2013

Keywords

  • 30S
  • Electron microscopy
  • IgM
  • Ltn1
  • Single-particle classification
  • Software

ASJC Scopus subject areas

  • Structural Biology

Fingerprint Dive into the research topics of 'Maskiton: Interactive, web-based classification of single-particle electron microscopy images'. Together they form a unique fingerprint.

  • Cite this