MARBLE: Multi-Agent Reasoning for Bioinformatics Learning and Evolution

• URL: http://arxiv.org/abs/2601.14349v1
• Date: Tue, 20 Jan 2026 17:10:47 GMT
• Title: MARBLE: Multi-Agent Reasoning for Bioinformatics Learning and Evolution
• Abstract summary: We introduce MARBLE, an execution-stable autonomous model refinement framework for bioinformatics models.<n>MARBLE consistently achieves sustained performance improvements over strong baselines across multiple refinement cycles.<n> Framework-level analyses demonstrate that structured debate, balanced evidence selection, and performance-grounded memory are critical for stable, repeatable model evolution.
• Score: 1.6489796571958972
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: Motivation: Developing high-performing bioinformatics models typically requires repeated cycles of hypothesis formulation, architectural redesign, and empirical validation, making progress slow, labor-intensive, and difficult to reproduce. Although recent LLM-based assistants can automate isolated steps, they lack performance-grounded reasoning and stability-aware mechanisms required for reliable, iterative model improvement in bioinformatics workflows. Results: We introduce MARBLE, an execution-stable autonomous model refinement framework for bioinformatics models. MARBLE couples literature-aware reference selection with structured, debate-driven architectural reasoning among role-specialized agents, followed by autonomous execution, evaluation, and memory updates explicitly grounded in empirical performance. Across spatial transcriptomics domain segmentation, drug-target interaction prediction, and drug response prediction, MARBLE consistently achieves sustained performance improvements over strong baselines across multiple refinement cycles, while maintaining high execution robustness and low regression rates. Framework-level analyses demonstrate that structured debate, balanced evidence selection, and performance-grounded memory are critical for stable, repeatable model evolution, rather than single-run or brittle gains. Availability: Source code, data and Supplementary Information are available at https://github.com/PRISM-DGU/MARBLE.

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