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TEMPy: a Python library for assessment of three-dimensional electron microscopy density fits.


ABSTRACT: Three-dimensional electron microscopy is currently one of the most promising techniques used to study macromolecular assemblies. Rigid and flexible fitting of atomic models into density maps is often essential to gain further insights into the assemblies they represent. Currently, tools that facilitate the assessment of fitted atomic models and maps are needed. TEMPy (template and electron microscopy comparison using Python) is a toolkit designed for this purpose. The library includes a set of methods to assess density fits in intermediate-to-low resolution maps, both globally and locally. It also provides procedures for single-fit assessment, ensemble generation of fits, clustering, and multiple and consensus scoring, as well as plots and output files for visualization purposes to help the user in analysing rigid and flexible fits. The modular nature of TEMPy helps the integration of scoring and assessment of fits into large pipelines, making it a tool suitable for both novice and expert structural biologists.

SUBMITTER: Farabella I 

PROVIDER: S-EPMC4520291 | biostudies-literature | 2015 Aug

REPOSITORIES: biostudies-literature

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<i>TEMPy</i>: a Python library for assessment of three-dimensional electron microscopy density fits.

Farabella Irene I   Vasishtan Daven D   Joseph Agnel Praveen AP   Pandurangan Arun Prasad AP   Sahota Harpal H   Topf Maya M  

Journal of applied crystallography 20150627 Pt 4


Three-dimensional electron microscopy is currently one of the most promising techniques used to study macromolecular assemblies. Rigid and flexible fitting of atomic models into density maps is often essential to gain further insights into the assemblies they represent. Currently, tools that facilitate the assessment of fitted atomic models and maps are needed. <i>TEMPy</i> (template and electron microscopy comparison using Python) is a toolkit designed for this purpose. The library includes a s  ...[more]

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