Dingent: a configurable agent framework for biological database retrieval and integration

Abstract AI-driven data search and integration represent an emerging research direction. Although several LLM-based backend frameworks and agentic frameworks have emerged, significant gap remains in developing a one-stop, configurable agent framework that supports various data sources and provides a web interface for efficient data retrieval using natural language. To address this, we present Dingent, a novel and configurable agent framework that facilitates data access from various resources and enables the flexible constructions of agent applications. We demonstrate its capabilities across three distinct application scenarios, achieving promising results. The Dingent framework can be readily applied to other fields, such as earth sciences and ecology, to facilitate data discovery.

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Publication Details

Journal
Computational and Structural Biotechnology Journal
Published
2026-11-03
DOI
https://doi.org/10.34133/csbj.0282
Primary Topic
Scientific Computing and Data Management
Type
article
Field-Weighted Citation Impact
0.00

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Dingent: a configurable agent framework for biological database retrieval and integration

Bixia Tang, Wenming Zhao, Shaoqi Bei, Demian Kong et al.
1 links
Computational and Structural Biotechnology Journal
Scientific Computing and Data Management
article

Dingent: a configurable agent framework for biological database retrieval and integration

Bixia Tang, Wenming Zhao, Shaoqi Bei, Demian Kong, Yueyue Wu
article en

Abstract

Abstract AI-driven data search and integration represent an emerging research direction. Although several LLM-based backend frameworks and agentic frameworks have emerged, significant gap remains in developing a one-stop, configurable agent framework that supports various data sources and provides a web interface for efficient data retrieval using natural language. To address this, we present Dingent, a novel and configurable agent framework that facilitates data access from various resources and enables the flexible constructions of agent applications. We demonstrate its capabilities across three distinct application scenarios, achieving promising results. The Dingent framework can be readily applied to other fields, such as earth sciences and ecology, to facilitate data discovery.

Computational and Structural Biotechnology Journal
Shanghai Center For Bioinformation Technology (CN)
Chinese Academy of Sciences, National Key Research and Development Program of China
Openalex Percentile: Top 87%
Scientific Computing and Data Management
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