Jobs
Every time you run a tool on ProteinIQ, a job is created to track the request, process your data, and store results.
What is a job?
A job represents a single execution of a tool with specific input data and settings. Each job includes:
- Input data: The sequences, structures, or molecules you provided
- Settings: Tool-specific parameters you configured
- Status: Current processing state (pending, processing, completed, or failed)
- Results: Output data when processing finishes
- Metadata: Job name, creation time, credits used
Job lifecycle
- Pending: Job submitted and waiting to start. Typical for tools with high demand or ML models that need GPU resources.
- Processing: Tool is actively working on your data. Simple conversions finish instantly, ML predictions take 1-5 minutes.
- Completed: Processing finished successfully. Results are ready to view and download.
- Failed: Processing encountered an error. Error message explains what went wrong.
Viewing jobs
Current job
After submitting a job, you'll see real-time status updates on the tool page. The interface shows a processing spinner while running, progress indicators for long-running jobs, and results immediately when complete.
Job history
Access all your previous jobs from any tool page:
- Click the History button in the sidebar
- Browse jobs for the current tool
- Click any job to view details
- Search by job name to find specific runs
Job details
Click any job in history to see complete input data, all settings used, full results, credits consumed, and execution time.
Managing jobs
Rename jobs
Give jobs meaningful names to find them later:
- Click the job menu (three dots)
- Select "Rename"
- Enter a descriptive name
- Click "Save"
Tip: Use names like "Aspirin docking run 1" instead of "Untitled job" to track experiments.
Delete jobs
Remove jobs you no longer need:
- Click the job menu (three dots)
- Select "Delete"
- Confirm deletion
Note: Deleting a job removes all associated data and results permanently.
Share jobs
Share results with collaborators via URL:
- Open the job you want to share
- Copy the URL from your browser (includes
?jobId=...) - Send the URL to collaborators
Privacy: Only you can access your jobs. Shared URLs only work for the job owner.
Job storage
- What data is stored? Input data (sequences, structures, settings), output results (predictions, converted files, scores), and job metadata (name, timestamp, status).
- How long are jobs kept? Jobs are stored in your account for easy access to previous analyses and results. You can delete jobs manually at any time to free up space.
Credits and costs
Each job consumes credits based on:
- Tool complexity: Simple conversions use 0 credits, ML predictions use 1-10 credits
- Input size: Larger proteins or molecule libraries may cost more
- Computational resources: GPU-based tools cost more than CPU tools
The credit cost is shown on the "Run" button before you submit. A tooltip explains how the cost is calculated, and your current balance appears in the sidebar.
Learn more about credits and pricing →
Best practices
- Name your jobs: Use descriptive names that include the molecule/protein identifier, experiment iteration, and date if running time-series analyses.
- Organize experiments: Create one job per parameter variation, use clear naming for A/B testing, and track iterations numerically.
- Clean up old jobs: Delete failed or test jobs to keep your history organized and focus on important results.
- Download important results: For critical data, download CSV/PDB files locally rather than relying solely on job history. Archive results in your lab storage system.
Troubleshooting
- Job stuck in pending: High server load is the most common cause—wait a few minutes. Check the status page for outages, or contact support if the job is pending for more than 10 minutes.
- Job failed immediately: Jobs usually fail due to invalid input format, missing required data, or file size exceeding limits. Check the error message for specific details.
- Can't find old job: Verify you're viewing the correct tool, try searching by partial name, or check if you accidentally deleted it.
- Job missing results: Wait for "completed" status and refresh the page if status seems outdated. Check the browser console for errors, or contact support if results are missing after completion.
Next steps
- Explore tools to start creating jobs
- Learn about credits to understand costs
- Read quickstart for workflow tips