Journal
BIOINFORMATICS
Volume 37, Issue 19, Pages 3369-3371Publisher
OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/btab189
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Funding
- Fonds de Recherche du Quebec - Nature et Technologie (FRQ-NT) PhD fellowship
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NRGTEN is a Python toolkit that implements four different NMA models and various metrics for benchmarking. It is easily extensible and includes the Elastic Network Contact Model developed by the group, which considers the specific chemical nature of atomic interactions.
The Najmanovich Research Group Toolkit for Elastic Networks (NRGTEN) is a Python toolkit that implements four different NMA models in addition to popular and novel metrics to benchmark and measure properties from these models. Furthermore, the toolkit is available as a public Python package and is easily extensible for the development or implementation of additional normal mode analysis models. The inclusion of the Elastic Network Contact Model developed in our group within NRGTEN is noteworthy, owing to its account for the specific chemical nature of atomic interactions.
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