Scope of Submission
We welcome submissions from a broad range of disciplines, including but not limited to:
- Predictive modeling in molecular chemistry
- Machine learning applications in chemistry
- Data-driven approaches to molecular prediction
- Modeling chemical properties using AI
- Predictive analytics for drug design
- Computational methods for molecular simulations
- Quantitative structure-activity relationship models
- Predictive modeling of reaction outcomes
- Molecular dynamics and predictive modeling
- Statistical methods in chemical predictions
- Integration of experimental and computational data
- Uncertainty quantification in molecular modeling
- Predictive models for material properties
- Applications of deep learning in chemistry
- Predictive modeling for environmental chemistry
- Chemoinformatics and predictive analytics
- Benchmarking predictive models in chemistry
- Future trends in predictive modeling
- Collaborative approaches in molecular predictions
- Ethics in predictive modeling in chemistry
All papers must be original and not previously published or submitted elsewhere.
