This Research Topic collection will focus on the application of machine learning algorithms in biomolecular simulations. In particular, it will cover the application of:
- advanced non-linear dimensionality reduction techniques
- advanced clustering methods
- supervised machine learning methods such as support vector machines or decision trees
- genetic algorithms
- (deep) neural networks and autoencoders
- reinforcement learning
- big data approaches
- other related techniques
We are interested in original manuscripts as well as expert reviews on the application of these techniques in:
- clustering and dimensionality reduction of molecular structure, especially in the analysis of simulation trajectories motivated by free energy modeling
- approximation of molecular potential by machine learning algorithms
- machine learning for the building of thermodynamic and kinetic models of molecular systems
- application of machine learning in sampling enhancement
- machine learning in multi-scale modelling
- machine learning to link molecular simulations with experiments
- software tools for application of machine learning in molecular simulations
Please contact the topic editors with a short description of the study or topic covered by the planned manuscript, or submit an abstract via the portal above prior to full submission.
This Research Topic collection will focus on the application of machine learning algorithms in biomolecular simulations. In particular, it will cover the application of:
- advanced non-linear dimensionality reduction techniques
- advanced clustering methods
- supervised machine learning methods such as support vector machines or decision trees
- genetic algorithms
- (deep) neural networks and autoencoders
- reinforcement learning
- big data approaches
- other related techniques
We are interested in original manuscripts as well as expert reviews on the application of these techniques in:
- clustering and dimensionality reduction of molecular structure, especially in the analysis of simulation trajectories motivated by free energy modeling
- approximation of molecular potential by machine learning algorithms
- machine learning for the building of thermodynamic and kinetic models of molecular systems
- application of machine learning in sampling enhancement
- machine learning in multi-scale modelling
- machine learning to link molecular simulations with experiments
- software tools for application of machine learning in molecular simulations
Please contact the topic editors with a short description of the study or topic covered by the planned manuscript, or submit an abstract via the portal above prior to full submission.
