DynaMate: leveraging AI-agents for customized research workflows
Developments related to large language models (LLMs) have deeply impacted everyday activities and offer the potential to automate complex research workflows involving repetitive and time-consuming tasks. The presented template enables the rapid incorporation of custom tools with LLM agents.
Authors
- Ubaldo M. Córdova‐Figueroa (ORCID: https://orcid.org/0000-0003-4891-5325)
- Jenny Torres (ORCID: https://orcid.org/0000-0002-8920-1225)
- Misael Díaz-Maldonado
- Yamil J. Colón (ORCID: https://orcid.org/0000-0001-5316-9692)
- Fernando J. Carmona Esteva (ORCID: https://orcid.org/0009-0003-6291-1547)
- Orlando A. Mendible-Barreto (ORCID: https://orcid.org/0000-0001-5797-0372)
Institutions
- University of Notre Dame (US)
- University of Puerto Rico System (PR)
- Merrimack College (US)
- University of Puerto Rico-Mayaguez (PR)
Publication Details
- Journal
- Molecular Systems Design & Engineering
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1039/d5me00062a
- Citations
- 4
- Primary Topic
- Scientific Computing and Data Management
- Type
- article
- Field-Weighted Citation Impact
- 16.68
Funders
- U.S. Department of Education
- University of Notre Dame