ReviewCurrent opinion in systems biology2017
Designing and interpreting 'multi-omic' experiments that may change our understanding of biology.
Review in Current opinion in systems biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 64 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
64 citing papers in PubMed.
- Intravenously delivered multilineage-differentiating stress-enduring cells dampen hyperoxia-induced lung injury in a rat model with features of bronchopulmonary dysplasia.Stem cell research & therapy · 2026Article
- Metab8D: a metabolic regulome network from multiomics and machine learning.Communications biology · 2026Article
- Biomarkers and advances in AML-MRC: from bench to bedside.Annals of hematology · 2026Review
- Secondary metabolism ofApplied and environmental microbiology · 2026Review
- Neonatal microbiome in the multiomics era: development and its impact on long-term health.Pediatric research · 2025Review
- Article
- Regulation of gene expression through protein-metabolite interactions.npj metabolic health and disease · 2025Review
- Conceptual frameworks for the integration of genetic and social epidemiology in complex diseases.Global epidemiology · 2024Article
- An integrative network-based approach to identify driving gene communities in chronic obstructive pulmonary disease.NPJ systems biology and applications · 2024Article
- RettDb: the Rett syndrome omics database to navigate the Rett syndrome genomic landscape.Database : the journal of biological databases and curation · 2024Article
- Application of Pan-Omics Technologies in Research on Important Economic Traits for Ruminants.International journal of molecular sciences · 2024Review
- Metabolomes evolve faster than metabolic network structures.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- A machine learning and deep learning-based integrated multi-omics technique for leukemia prediction.Heliyon · 2024Article
- Pan-Omics in Sheep: Unveiling Genetic Landscapes.Animals : an open access journal from MDPI · 2024Review
- Improvement in the prediction power of an astrocyte genome-scale metabolic model using multi-omic data.Frontiers in systems biology · 2024Article
- Pinpointing the integration of artificial intelligence in liver cancer immune microenvironment.Frontiers in immunology · 2024Review
- Article
- How is Big Data reshaping preclinical aging research?Lab animal · 2023Review
- Protective Effects and Mechanism of Polysaccharides from Edible Medicinal Plants in Alcoholic Liver Injury: A Review.International journal of molecular sciences · 2023Review
- Gene communities in co-expression networks across different tissues.PLoS computational biology · 2023Article
4 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
Most biological mechanisms involve more than one type of biomolecule, and hence operate not solely at the level of either genome, transcriptome, proteome, metabolome or ionome. Datasets resulting from single-omic analysis are rapidly increasing in throughput and quality, rendering multi-omic studies feasible. These should offer a comprehensive, structured and interactive overview of a biological mechanism. However, combining single-omic datasets in a meaningful manner has so far proved challenging, and the discovery of new biological information lags behind expectation. One reason is that experiments conducted in different laboratories can typically not to be combined without restriction. Second, the interpretation of multi-omic datasets represents a significant challenge by nature, as the biological datasets are heterogeneous not only for technical, but also for biological, chemical, and physical reasons. Here, multi-layer network theory and methods of artificial intelligence might contribute to solve these problems. For the efficient application of machine learning however, biological datasets need to become more systematic, more precise - and much larger. We conclude our review with basic guidelines for the successful set-up of a multi-omic experiment.
Identifiers
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.