Ajay Neginhal

This project validates clustering results for liposome and micelle simulations by combining statistical checks with clear visualization outputs for research teams.

ResearchTBDComputational Researcher

Liposome and Micelle Clustering Validation

Validation workflows for clustering liposome and micelle simulations with statistical quality checks.

Figure coming soon
Clustering validation workflow (placeholder).
Molecular DynamicsClusteringValidationResearchPython

Key Reminders

  • Explain clustering criteria and how they relate to physical structure.
  • Discuss statistical checks for cluster stability.
  • Highlight visualization outputs for lab reports.

Technologies

PythonNumPySciPypandasMatplotlib

Problem and Scope

Built validation workflows to confirm clustering results for liposome and micelle simulations, ensuring robust interpretation of structural data.

System Architecture

The workflow computes cluster statistics, evaluates stability across frames, and generates visualization-ready summaries.

Figure coming soon
Workflow schematic placeholder.

python code

Code example forthcoming

Cluster stability computation routine.

Validation and Reporting

Statistical checks quantify cluster persistence and variance across replicates to support lab conclusions.

Figure coming soon
Cluster stability plots placeholder.

Testing and Results

Produced standardized outputs for research reports and downstream analysis.

Figure coming soon
Result summary plots placeholder.

Demo and Next Steps

Future work includes automated parameter sweeps and interactive visualization dashboards.

Figure coming soon
Demo video placeholder.