ArticleBiological research for nursing2021
Multi-Staged Data-Integrated Multi-Omics Analysis for Symptom Science Research.
Article in Biological research for nursing, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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.
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
8 citing papers in PubMed.
- Artificial intelligence construction: a review of the bridge between CT imaging features of lung ground-glass nodules adenocarcinoma and carcinogenic driver genes.Journal of cancer research and clinical oncology · 2026Review
- Article
- Research Priorities of the Oncology Nursing Society: 2024-2027.Oncology nursing forum · 2024Article
- Big Data in Oncology Nursing Research: State of the Science.Seminars in oncology nursing · 2023Review
- Advancing Nursing Research Through Interactive Data Visualization With R Shiny.Biological research for nursing · 2023Article
- Gastrointestinal Symptom Cluster is Associated With Epigenetic Regulation of Lymphotoxin Beta in Oncology Patients Receiving Chemotherapy.Biological research for nursing · 2023Article
- Strengthening Systematic Research on Aging: Reflections from an Omics Perspective.China CDC weekly · 2022Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
The incorporation of omics approaches into symptom science research can provide researchers with information about the molecular mechanisms that underlie symptoms. Most of the omics analyses in symptom science have used a single omics approach. Therefore, these analyses are limited by the information contained within a specific omics domain (e.g., genomics and inherited variations, transcriptomics and gene function). A multi-staged data-integrated multi-omics (MS-DIMO) analysis integrates multiple types of omics data in a single study. With this integration, a MS-DIMO analysis can provide a more comprehensive picture of the complex biological mechanisms that underlie symptoms. The results of a MS-DIMO analysis can be used to refine mechanistic hypotheses and/or discover therapeutic targets for specific symptoms. The purposes of this paper are to: (1) describe a MS-DIMO analysis using "Symptom X" as an example; (2) discuss a number of challenges associated with specific omics analyses and how a MS-DIMO analysis can address them; (3) describe the various orders of omics data that can be used in a MS-DIMO analysis; (4) describe omics analysis tools; and (5) review case exemplars of MS-DIMO analyses in symptom science. This paper provides information on how a MS-DIMO analysis can strengthen symptom science research through the prioritization of functional genes and biological processes associated with a specific symptom.
Indexed as
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What OpenQuestion 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 OpenQuestion graph.