AI & Computational Structural Biology
AI & Computational Structural Biology are transforming the way scientists study biomolecules by enabling faster, more accurate structure prediction and analysis. Tools like AlphaFold and Rose TTA Fold have revolutionized protein structure prediction, reducing the need for time-consuming experimental methods. Computational approaches also support molecular modeling, docking, and dynamics simulations, helping researchers understand interactions, design drugs, and predict mutations. These technologies are essential for accelerating discoveries, improving precision medicine, and bridging the gap between structural data and functional insights. Their importance continues to grow as they integrate with experimental techniques to offer a more complete view of biological systems.
Related Conference of AI & Computational Structural Biology
17th International Conference on Tissue Science and Regenerative Medicine
AI & Computational Structural Biology Conference Speakers
Recommended Sessions
- 3D Structure Determination
- Advanced Techniques in Structural Biology
- AI & Computational Structural Biology
- Biochemistry and Biophysics
- Computational Approach in Structural Biology
- Drug Designing and Biomarkers
- Hybrid Approaches for Structure Prediction
- Membrane Proteins and Receptors
- Molecular Modelling and Dynamics
- Proteomics and Genomics
- Structural Bioinformatics and Computational Biology
- Structural Biology in Cancer Research
- Structural Virology
- Structural Virology and Infectious Diseases
- Structure-Based Drug Discovery
- Structure-Based Solutions to Global Health Challenges
- Structure-Function Relationships
- The Structural Basis of Disease