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

  • Lydia Tapia (a1), Juan Cortés (a2), Amarda Shehu (a3) and Jinalin Chen (a4)

Extract

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.

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Copyright

Corresponding author

*Corresponding author. E-mail: tapia@cs.unm.edu

References

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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.
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.
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.
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.
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.
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.

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