ArticlebioRxiv : the preprint server for biology2025
OmniCellAgent: Towards AI Co-Scientists for Scientific Discovery in Precision Medicine.
Article in bioRxiv : the preprint server for biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
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Authors and funding
12 authors.
Funding
Abstract
The convergence of large language models (LLMs), AIagents, and large-scale omic datasets-such as single-cell omics, marks the arrival of a critical inflection point in biomedical research, via autonomous data mining and novel hypothesis generation. However, there is no specifically designed agentic AI model that can systematically integrate large-scale single-cell (sc) RNAseq (covering diverse diseases and cell types), omic data analytic tools, accumulated biomedical knowledge, and literature search to facilitate autonomous scientific discovery in precision medicine. In this study, we develop a novel agentic AI, OmniCellAgent, to empower non-computational-expert users-such as patients and family members, clinicians, and wet-lab researchers-to conduct scRNA-seq data-driven biomedical research like experts, uncovering molecular disease mechanisms and identifying effective precision therapies. The code of omniCellAgent is publicly accessible at: https://fuhailiailab.github.io/.
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.