ArticleBiostatistics (Oxford, England)2012
Transcriptional and metabolic data integration and modeling for identification of active pathways.
Article in Biostatistics (Oxford, England), 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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.
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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.
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Who cites it
10 citing papers in PubMed, 48 citations in OpenAlex.
- Transcriptomics- and metabolomics-based integration analyses revealed the potential pharmacological effects and functional pattern of in vivo Radix Paeoniae Alba administration.Chinese medicine · 2020Article
- Review of Statistical Learning Methods in Integrated Omics Studies (An Integrated Information Science).Bioinformatics and biology insights · 2018Review
- Pathway crosstalk effects: Shrinkage and disentanglement using a Bayesian hierarchical model.Statistics in biosciences · 2016Article
- The discordant method: a novel approach for differential correlation.Bioinformatics (Oxford, England) · 2016Article
- Hierarchical Feature Selection Incorporating Known and Novel Biological Information: Identifying Genomic Features Related to Prostate Cancer Recurrence.Journal of the American Statistical Association · 2016Article
- A non-negative matrix factorization method for detecting modules in heterogeneous omics multi-modal data.Bioinformatics (Oxford, England) · 2016Article
- Biodiversity of Intestinal Lactic Acid Bacteria in the Healthy Population.Advances in experimental medicine and biology · 2016Review
- Comparative analysis and modeling of the severity of steatohepatitis in DDC-treated mouse strains.PloS one · 2014Article
- Inter-individual differences in response to dietary intervention: integrating omics platforms towards personalised dietary recommendations.The Proceedings of the Nutrition Society · 2013Article
- A global approach to analysis and interpretation of metabolic data for plant natural product discovery.Natural product reports · 2013Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 3 institutions in 2 countries.
Funding
Abstract
With the growing availability of omics data generated to describe different cells and tissues, the modeling and interpretation of such data has become increasingly important. Pathways are sets of reactions involving genes, metabolites, and proteins highlighting functional modules in the cell. Therefore, to discover activated or perturbed pathways when comparing two conditions, for example two different tissues, it is beneficial to use several types of omics data. We present a model that integrates transcriptomic and metabolomic data in order to make an informed pathway-level decision. Since metabolites can be seen as end-points of perturbations happening at the gene level, the gene expression data constitute the explanatory variables in a sparse regression model for the metabolite data. Sophisticated model selection procedures are developed to determine an appropriate model. We demonstrate that the transcript profiles can be used to informatively explain the metabolite data from cancer cell lines. Simulation studies further show that the proposed model offers a better performance in identifying active pathways than, for example, enrichment methods performed separately on the transcript and metabolite data.
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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.