Connect the analytical steps.
Build a pipeline from individual tasks. Define how data moves between them, which steps depend on others, and which can run in parallel.
THE BIOINFORMATICS PIPELINE ENGINE
Connect analytical steps into a pipeline, run the work, and follow its progress. Gobble keeps inputs, outputs, and execution state organized throughout the analysis.
Built in Go. Designed for bioinformatics workflows.
The inputs and the work to be done.
Inputs, outputs, and dependencies
Tasks in the right order
Progress, logs, and run state
Outputs to inspect, interpret, and build on.
Illustrative workflow
WHAT THE ENGINE DOES
Gobble handles the execution work around the analysis, so each step has a defined place in the research workflow.
Build a pipeline from individual tasks. Define how data moves between them, which steps depend on others, and which can run in parallel.
Validate the pipeline and inspect the work it describes. Make inputs, outputs, and resource requirements clear before starting.
Run the analysis steps in their intended order, manage their dependencies, and collect the outputs they produce.
Follow progress across the pipeline. Inspect individual tasks and their logs to see what has finished and what needs attention.
Resume a pipeline with its recorded state in view. Reuse compatible completed tasks and carry out the work that remains.
Package a pipeline as a runner that another researcher can execute. Keep the defined workflow together when passing it on.
BIOINFORMATICS WORKFLOWS
The biological question shapes the workflow. Gobble provides the structure for running its analytical steps.
THE ENGINE’S ROLE IN YOUR RESEARCH
The researcher brings the scientific context. An agent helps shape the analysis. Gobble manages the pipeline execution.
Defines the question and interprets the results in the context of the experiment.
Helps turn the research goal into analytical steps and pipeline code.
Executes the steps and keeps their outputs and run state organized.
LET’S TALK RESEARCH
Bring your questions, your data challenges, and where you want to go next.