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Assessing Models with TEMPy SCCC Scores by Andrés Trujillo Mateus is a document available to read on EtoBox.

What is Assessing Models with TEMPy SCCC Scores about?

TEMPy is a Python toolkit for processing atomic models and maps and assessing how well models fit maps. It contains functions for scoring model fits locally and globally. This tutorial will use the Segment-based Cross Correlation Coefficient (SCCC) score implemented in TEMPy to assess models fitted to a map using Flex-EM. The example script get_sccc.py calculates SCCC scores for segments defined in a rigid body file. Running the script produces SCCC scores for each segment and generates a Chimera attribute

Author

Andrés Trujillo Mateus

Language

EN