Knowledge Synthesis using Large Language Models for a Computational Biology Workflow Ecosystem-Reference-Cited by-同舟云学术

Knowledge Synthesis using Large Language Models for a Computational Biology Workflow Ecosystem

Published:2024-04-08 Issue: Volume:60 Page:523-530
ISSN:
Container-title:Proceedings of the 39th ACM/SIGAPP Symposium on Applied Computing
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Author:

Jamil Hasan¹^ORCID,Krawetz Stephen²^ORCID,Gow Alexander²^ORCID

Affiliation:

1. Department of Computer Science, University of Idaho, Moscow, Idaho, USA

2. School of Medicine, Wayne State University, Detroit, Michigan, United States

Funder

National Institutes of Health

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3605098.3636026

Reference31 articles.

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2. Using Declarative Workflow Languages to Develop Process-Centric Web Applications

3. Sridevi Bonthu, S. Rama Sree, and Munaga H. M. Krishna Prasad. 2021. Text2PyCode: Machine Translation of Natural Language Intent to Python Source Code. In International Cross-Domain Conference, CD-MAKE 2021, August 17--20 (LNCS, Vol. 12844). Springer, 51--60.

4. From Natural Language to Workflows: Towards Emergent Intelligence in Robotic Process Automation

5. Lonnie Chrisman, Pat Langley, and Stephen D. Bay. 2003. Incorporating Biological Knowledge into Evaluation of Causal Regulatory Hypotheses. In PSB 2003, Lihue, Hawaii, USA, January 3--7. 128--139.

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