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Foreword on special issue on robotics methods for structural and dynamic modeling of molecular systems

Published online by Cambridge University Press:  11 July 2016

Lydia Tapia*
Affiliation:
Department of Computer Science, University of New Mexico, Albuquerque, NM, USA
Juan Cortés
Affiliation:
Robotics and Interactions, LAAS-CNRS, Toulouse, France
Amarda Shehu
Affiliation:
Department of Computer Science, George Mason University, Fairfax, VA, USA
Jinalin Chen
Affiliation:
Department of Computer Science, University of Missouri, Columbia, MO, USA
*
*Corresponding author. E-mail: tapia@cs.unm.edu
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Molecular biological systems can be seen as extremely complex mobile systems. The development of methods for modeling the structure and the motion of such systems is essential to better understand their physiochemical properties and biological functions. In recent years, many computer scientists in robotics and artificial intelligence have made significant contributions to modeling biological systems. Research expertise in planning, search, learning, evolutionary computation, constraint programming, and data mining is being used to make great progress on molecular motion, structure prediction, and design.

Type
Foreword
Copyright
Copyright © Cambridge University Press 2016 

References

1. Kim, J. S. and Chirikjian, G. S., “Inverse Kinematic Solutions of 6-D.O.F. Biopolymer Segments,” In: Robotica Journal Special Issue on Robotics Methods for Structural and Dynamics Modeling of Molecular Systems (2016) pp. 17341753.Google Scholar
2. Molloy, K., Clausen, R. and Shehu, A., “A Stochastic Roadmap Method to Model Protein Structural Transitions,” In: Robotica Journal Special Issue on Robotics Methods for Structural and Dynamics Modeling of Molecular Systems (2016) pp. 17051733.Google Scholar
3. Nasr, K. A. and He, J., “Constrained Cyclic Coordinate Descent - Beyond the Protein Loop Closure Problem,” In: Robotica Journal Special Issue on Robotics Methods for Structural and Dynamics Modeling of Molecular Systems (2016) pp. 17771790.Google ScholarPubMed
4. Chirikjian, G. S. and Shiffman, B., “Collision-Free Configuration-Spaces in Macromolecular Crystals,” In: Robotica Journal Special Issue on Robotics Methods for Structural and Dynamics Modeling of Molecular Systems (2016) pp. 16791704.Google Scholar
5. Manavi, K., Jacobson, B., Hoard, B. and Tapia, L., “Influence of Model Resolution on Geometric Simulations of Antibody Aggregation,” In: Robotica Journal Special Issue on Robotics Methods for Structural and Dynamics Modeling of Molecular Systems (2016) pp. 17541776.Google Scholar
6. Fricke, G. M., Hecker, J. P., Cannon, J. L. and Moses, M. E., “Immune-Inspired Search Strategies for Robot Swarms,” In: Robotica Journal Special Issue on Robotics Methods for Structural and Dynamics Modeling of Molecular Systems (2016) pp. 17911810.Google Scholar