Future Research Ideas

This is a collection of potential research directions that I’m considering exploring in the future. These are preliminary thoughts that need further development.

Epigenetics & Genomics

  • Developing improved methods for integrating DNA methylation and histone modification data
  • Exploring the role of 3D chromatin structure in epigenetic regulation
  • Comparative analysis of epigenetic patterns across different cell types and disease states
  • Investigating the dynamics of epigenetic changes during cellular differentiation

Machine Learning Applications

  • Applying transfer learning to improve prediction accuracy across different cell types
  • Developing interpretable deep learning models for genomic data
  • Exploring reinforcement learning for optimizing experimental design in epigenetics
  • Benchmarking different neural network architectures for epigenetic pattern prediction

Bioinformatics Tool Development

  • Creating interactive visualization tools for multi-modal epigenetic data
  • Developing scalable pipelines for processing large-scale genomic datasets
  • Building user-friendly interfaces for complex bioinformatics analyses
  • Improving reproducibility in computational biology workflows

Questions to Explore

  • How can we better integrate prior biological knowledge into machine learning models?
  • What are the most effective ways to visualize complex relationships in epigenetic data?
  • How can we address batch effects and technical variability in epigenetic datasets?
  • What are the ethical considerations in developing AI tools for genomic medicine?

Resources to Investigate

  • Recent advances in single-cell epigenomics technologies
  • Benchmark datasets for evaluating epigenetic prediction models
  • State-of-the-art methods for multi-modal data integration
  • Emerging standards for reproducible bioinformatics research

This note contains preliminary research ideas that will be refined and developed over time. Suggestions and collaborations are welcome.