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A connected set algorithm for the identification of spatially contiguous regions in crystallographic envelopes
J F Hunt1, F M Vellieux, J Deisenhofer
1Howard Hughes Medical Institute and Department of Biochemistry, University of Texas Southwestern Medical Center, Dallas, TX 75235-9050, USA. hunt@howie.swmed.edu
Summary
This study introduces a straightforward algorithm to identify connected regions within crystallographic envelopes. The method efficiently traces spatial connectivity using simple set operations for improved data analysis.
Area of Science:
- Crystallography
- Computational Chemistry
- Structural Biology
Background:
- Identifying spatially contiguous regions in crystallographic envelopes is crucial for analyzing electron density maps.
- Existing methods may be computationally intensive or lack efficiency in tracing connectivity.
Purpose of the Study:
- To present a simple and efficient algorithm for identifying spatially contiguous regions in crystallographic envelopes.
- To implement this algorithm in a user-friendly program for practical application.
Main Methods:
- The algorithm processes grid points of the envelope map in a single pass.
- Occupied points are assigned to locally contiguous sets based on voxel connectivity.
- Spatially contiguous regions are identified through the union of sets sharing common elements, implicitly tracing connectivity via set operations.
Main Results:
- A simple algorithm for identifying spatially contiguous regions in crystallographic envelopes has been developed.
- The algorithm efficiently traces spatial connectivity by considering local voxel connections and performing set operations.
Conclusions:
- The described algorithm provides an efficient method for identifying connected regions in crystallographic data.
- Implementation in the CNCTDENV program facilitates its use in density-modification workflows.