This pipeline automates the analysis of Phi-29 DNA motor simulations, converting raw trajectories into reproducible metrics and visual summaries for research teams.
Molecular Dynamics Data Pipelines (Phi-29 DNA Motor)
Automated pipelines for processing molecular dynamics trajectories of the Phi-29 DNA packaging motor.
Key Reminders
- Explain the pipeline stages from trajectory ingest to derived metrics.
- Discuss performance considerations for large trajectory datasets.
- Highlight reproducibility and versioned analysis outputs.
Technologies
Problem and Scope
Built an automated pipeline to process Phi-29 DNA motor trajectories and extract structural metrics across large simulation ensembles.
System Architecture
The pipeline ingests trajectories, performs feature extraction, and aggregates results into standardized reports for downstream analysis.
python code
Code example forthcoming
Trajectory preprocessing and batching routine.
Data Validation
Validation steps include consistency checks, outlier detection, and statistical summaries across simulation replicates.
Testing and Results
Generated reproducible plots and tables that summarize key conformational dynamics for the Phi-29 motor system.
Demo and Next Steps
Future work includes scaling to additional motor systems and automated report generation for lab-wide studies.