The DOI matches its Crossref record; 224 of the 224 references it cites were found in a registry or an index.
Multi-omics integration in biomedical research – A metabolomics-centric review
Open accessAbstract
Recent advances in high-throughput technologies have enabled the profiling of multiple layers of a biological system, including DNA sequence data (genomics), RNA expression levels (transcriptomics), and metabolite levels (metabolomics). This has led to the generation of vast amounts of biological data that can be integrated in so-called multi-omics studies to examine the complex molecular underpinnings of health and disease. Integrative analysis of such datasets is not straightforward and is particularly complicated by the high dimensionality and heterogeneity of the data and by the lack of universal analysis protocols. Previous reviews have discussed various strategies to address the challenges of data integration, elaborating on specific aspects, such as network inference or feature selection techniques. Thereby, the main focus has been on the integration of two omics layers in their relation to a phenotype of interest. In this review we provide an overview over a typical multi-omics workflow, focusing on integration methods that have the potential to combine metabolomics data with two or more omics. We discuss multiple integration concepts including data-driven, knowledge-based, simultaneous and step-wise approaches. We highlight the application of these methods in recent multi-omics studies, including large-scale integration efforts aiming at a global depiction of the complex relationships within and between different biological layers without focusing on a particular phenotype.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Breiman, L. (2001) · Machine Learning · doi:10.1023/a:1010933404324 · Cited by 133,538
Subramanian, A., Tamayo, P., Mootha, V. K., Mukherjee, S., Ebert, B. L., Gillette, M. A., Paulovich, A., Pomeroy, S. L., Golub, T. R., Lander, E. S., et al. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0506580102 · Cited by 53,625
Cytoscape: A software Environment for integrated models of biomolecular interaction networks
Shannon, P., Markiel, A., Ozier, O., Baliga, N. S., Wang, J. T., Ramage, D., Amin, N., Schwikowski, B., & Ideker, T. (2003) · Genome Research · doi:10.1101/gr.1239303 · Cited by 51,888
Regression shrinkage and selection via the lasso
Tibshirani, R. (1996) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1996.tb02080.x · Cited by 51,482
KEGG: Kyoto Encyclopedia of Genes and Genomes
Kanehisa, M. (2000) · Nucleic Acids Research · doi:10.1093/nar/28.1.27 · Cited by 37,077
KEGG: Kyoto Encyclopedia of Genes and Genomes
Ogata, H., Goto, S., Sato, K., Fujibuchi, W., Bono, H., & Kanehisa, M. (1999) · Nucleic Acids Research · doi:10.1093/nar/27.1.29 · Cited by 31,232
WGCNA: an R package for weighted correlation network analysis
Langfelder, P., & Horvath, S. (2008) · BMC Bioinformatics · doi:10.1186/1471-2105-9-559 · Cited by 27,252
Reducing the dimensionality of data with neural networks
Hinton, G. E., & Salakhutdinov, R. R. (2006) · Science · doi:10.1126/science.1127647 · Cited by 20,928
Multiple Imputation for Nonresponse in Surveys
Rubin, D. B. (1987) · Wiley Series in Probability and Statistics · doi:10.1002/9780470316696 · Cited by 20,701
Szklarczyk, D., Gable, A. L., Lyon, D., Junge, A., Wyder, S., Huerta-Cepas, J., Simonovic, M., Doncheva, N. T., Morris, J. H., Bork, P., et al. (2019) · Nucleic Acids Research · doi:10.1093/nar/gky1131 · Cited by 17,749
Cited by
New software tools, databases, and resources in metabolomics: updates from 2020
Misra, B. B. (2021) · Metabolomics · doi:10.1007/s11306-021-01796-1 · Cited by 227
Ai, X., Yu, P., Li, X., Lai, X., Yang, M., Liu, F., Luan, F., & Meng, X. (2023) · International Journal of Biological Macromolecules · doi:10.1016/j.ijbiomac.2023.123211 · Cited by 91
Rosato, B. E., D'Onofrio, V., Marra, R., Nostroso, A., Esposito, F. M., Iscaro, A., Lasorsa, V. A., Capasso, M., Iolascon, A., Russo, R., et al. (2025) · American Journal of Hematology · doi:10.1002/ajh.27523 · Cited by 12
Perspectives in computational mass spectrometry: recent developments and key challenges
Sachsenberg, T., Pino, L. K., Brunet, M., Bludau, I., Kohlbacher, O., Vizcaino, J. A., & Bittremieux, W. (2024) · Bioinformatics Advances · doi:10.1093/bioadv/vbaf301 · Cited by 6
Metadata
- Authors
- Wörheide, M. A., Krumsiek, J., Kastenmüller, G., & Arnold, M.
- Venue
- Analytica Chimica Acta
- Publisher
- Elsevier BV
- Published
- 2021-01
- Volume
- 1141
- Pages
- 144-162
- ISSN
- 0003-2670 (ISSN-L)
- OpenAlex
- W3094386380
- Cited by
- 334
- References
- 224
- FWCI
- 7.88
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Multi-omics integration in biomedical research – A metabolomics-centric review. https://app.cochat.ai/papers/10.1016/j.aca.2020.10.038
- The paper
- Wörheide, M. A., Krumsiek, J., Kastenmüller, G., & Arnold, M. (2021). Multi-omics integration in biomedical research – A metabolomics-centric review. Analytica Chimica Acta. https://doi.org/10.1016/j.aca.2020.10.038
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
