Evidence map›Paper›PMID 41535301›Full record

ArticleScientific data2026

SEA CDM: Study-Experiment-Assay Common Data Model and Databases for Cross-Domain Data Integration and Analysis.

Anthony Huffman, Feng-Yu Yeh, Junguk Hur, Jie Zheng, Anna Maria Masci, Guanming Wu, Cui Tao, Brian Athey, Yongqun He

Abstract readDataset
In one paragraph

Article in Scientific data, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Article
  4. VO: The Vaccine Ontology.Scientific data · 2026
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors.

Anthony HuffmanDepartment of Computational Medicine and Biology, University of Michigan Medical School, Ann Arbor, MI, 48109, USA.
Feng-Yu YehUnit for Laboratory Animal Medicine, University of Michigan Medical School, Ann Arbor, MI, 48109, USA.
Junguk HurDepartment of Biomedical Sciences, University of North Dakota School of Medicine and Health Sciences, Grand Forks, ND, 58202, USA.
Jie ZhengUnit for Laboratory Animal Medicine, University of Michigan Medical School, Ann Arbor, MI, 48109, USA.
Anna Maria MasciDepartment of Data Impact and Governance, University of Texas, MD Anderson Cancer Center, Houston, TX, 77030, USA.
Guanming WuDivision of Oncological Sciences, Oregon Health & Science University, Portland, OR, USA.
Cui TaoDepartment of Artificial Intelligence and Informatics, Mayo Clinic, Jacksonville, FL, 32224, USA.
Brian AtheyDepartment of Computational Medicine and Biology, University of Michigan Medical School, Ann Arbor, MI, 48109, USA.
Yongqun HeDepartment of Computational Medicine and Biology, University of Michigan Medical School, Ann Arbor, MI, 48109, USA. yongqunh@med.umich.edu.ORCID http://orcid.org/0000-0001-9189-9661

Funding

Reactome: An Open Knowledgebase of Human Pathways.U24HG012198 · NHGRI · ONTARIO INSTITUTE FOR CANCER RESEARCH · PI Marc E Gillespie, LINCOLN D. STEIN · 2022 to 2026
$7.0M
VIOLIN 2.0: Vaccine Information and Ontology LInked kNowledgebaseU24AI171008 · NIAID · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Yongqun He, Junguk Hur · 2022 to 2026
$4.2M
Ontology-supported Integrative Analysis and Visualization of Vaccine-induced Pathways and NetworksUH2AI132931 · NIAID · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI HE, YONGQUN, WU, GUANMING · 2019 to 2020
$437k
Division of Intramural Research, National Institute of Allergy and Infectious Diseases (Division of Intramural Research of the NIAID) U24AI171008NHGRI NIH HHS U24 HG012198NIAID NIH HHS U24 AI171008NIAID NIH HHS UH2 AI132931U.S. Department of Health & Human Services | NIH | National Institute of Allergy and Infectious Diseases (NIAID) U24AI171008
6 · The paper itself

Abstract

With the increasing volume of biomedical experimental data, standardizing, sharing, and integrating heterogeneous experimental data across domains has become a major challenge. To address this challenge, we have developed an ontology-supported Study-Experiment-Assay (SEA) common data model (CDM), which includes 10 core and 3 auxiliary classes based on object-oriented modeling. SEA CDM uses interoperable ontologies for data standardization and knowledge inference. Building on the SEA CDM, we developed the Ontology-based SEA Network (OSEAN) relational database and knowledge graph, along with a set of ETL (Extract, Transform, Load) and query tools, and further applied them to represent 1,278 immune studies with over two million samples from three resources: VIGET, ImmPort, and CELLxGENE. Using simple, robust queries and analyses, our research identified multiple scientific insights into sex-specific immune responses, such as neutrophil degranulation and TNF binding to physiological receptors, following live attenuated and trivalent inactivated influenza vaccination. The novel SEA CDM system lays a foundation for establishing an integrative biodata ecosystem across biological and biomedical domains.

Indexed as

Biological OntologiesDatabases, FactualAnimalsHumans

Identifiers

PMID41535301
PMCPMC12905146

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 OpenQuestion graph.