Build complex computational workflows by connecting specialized nodes. Visual programming for computational chemistry and bioinformatics.
Powerful features that make workflow creation intuitive and efficient.
Build complex workflows by connecting computational nodes
Automatic data type checking and conversion between nodes
Full control over workflow execution with advanced features
Ensure workflow integrity before execution
Different workflow patterns for different computational needs.
Simple sequential processing pipelines
File Input → Data Processing → Analysis → Visualization
Basic data analysis and molecular property calculations
Conditional logic and decision trees
Data Input → Condition Check → Branch A/B → Merge Results
Quality control, filtering, and conditional processing
Loops and repeated processing
Initialize → Process Batch → Check Completion → Loop Back
Batch processing, optimization loops, and parameter sweeps
Independent processing streams
Split Data → Process A + Process B → Combine Results
High-throughput screening and comparative analysis
Reusable patterns that form the basis of many computational workflows.
Process raw data into insights
Load experimental data, clean missing values, calculate descriptors, run ML model, plot results
High-throughput compound evaluation
Load compound library, prepare molecules, dock against target, score results, filter hits
Molecular dynamics preparation and analysis
Load protein structure, prepare simulation system, minimize energy, equilibrate, run production MD
Compare multiple datasets or methods
Load different datasets, process with different methods, compare results, generate comparison report
Tips and techniques for building robust and efficient workflows.
Keep related nodes together and use clear naming
Check your workflow before running expensive computations
Handle potential issues gracefully
Make your workflows run faster and more efficiently
Learn how to create workflows with the visual canvas and explore node connections.