BioClaw: Human-Bot Research Collaboration Ecosystems in Group Chats
Xu, M.; Yan, J.; Feng, R.; Cai, Q.; Zhang, P.; Zhao, C.; He, C.; Wei, Z.; Li, J.; Lin, S.; Dong, H.; Jin, R.; Hou, T.; Liu, Q.; Zhang, Z.
Show abstract
Day-to-day research discussions in group chats often generate hypotheses, analysis requests, and interpretation decisions, yet executing those analyses still requires researchers to leave the conversation and rely on fragmented local tools, databases, visualization software, and literature search engines. In this work, we present BioClaw, a human-bot research collaboration ecosystem that converts natural-language requests in group conversations into tool-grounded analyses executed within isolated Docker containers. Deployed across 8 messaging platforms, BioClaw turns each group chat into a persistent execution workspace. Its design combines multi-channel orchestration, per-group state and workspace management, and isolated containerized execution for reliable shared use over long-lived conversations. To support practical research workflows, BioClaw combines containerized execution with preinstalled 31 biomedical tools and 95+ skills. The application of BioClaw spans various biomedical domains (e.g., genomics, clinics, structural biology) and data modalities (e.g., sequencing data, EHR data, protein structure data). These results establish the viability of embedding executable, tool-rich agent workflows within shared digital workspaces, positioning group chats as a transformative paradigm for collaborative scientific discovery and innovation.
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