FlowAgent: A Modular Agent-Based System for Automated Workflow Management and Data Interpretation

Abstract

Reproducibility, automation, and flexibility remain persistent challenges in bioinformatics, where complex workflows require integration of diverse computational tools, rigorous quality control, and dynamic adaptability to evolving datasets. Existing workflow managers often trade off usability for flexibility, limiting accessibility for non-specialists and enforcing rigid execution pipelines. We present FlowAgent, an adaptive agent-based framework that embeds computational heuristics and intelligent decision-making into workflow management. Unlike static pipeline managers, FlowAgent leverages agentic systems for context-aware automation, enhancing error detection, correction, and real-time optimisation while minimising manual intervention. By integrating bioinformatics tools with adaptive control, FlowAgent ensures robust quality control and enables workflow execution through an intuitive natural language interface. This approach democratises advanced computational methods for biologists while allowing bioinformaticians to focus on high-level analysis. FlowAgent redefines workflow automation, making bioinformatics pipelines more intelligent, efficient, and accessible, ultimately accelerating scientific discovery across diverse omics data modalities. Availability and implementationFlowAgent is available with GLPv3 license at https://github.com/EnteloBio/flowagent