ArticleAmerican journal of physiology. Lung cellular and molecular physiology2019
Integration of transcriptomic and proteomic data identifies biological functions in cell populations from human infant lung.
Article in American journal of physiology. Lung cellular and molecular physiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
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Who cites it
26 citing papers in PubMed.
- Spatial transcriptomics of developing human lungs defines cellular phenotypes associated with age, lineage and location.Scientific reports · 2026Article
- Multi-omics to study chronic respiratory diseases and viral infections.European respiratory review : an official journal of the European Respiratory Society · 2026Review
- The evolving pathophysiology of bronchopulmonary dysplasia.Physiological reviews · 2026Review
- Multi-omics analysis reveals discordant proteome and transcriptome responses in larval guts of Frankliniella occidentalis infected with an orthotospovirus.Insect molecular biology · 2025Article
- Histopathology of Diabetic Nephropathy: Beyond Glomerular Basement Membrane Thickening.Cureus · 2025Review
- Fungal Coculture: Unlocking the Potential for Efficient Bioconversion of Lignocellulosic Biomass.Journal of fungi (Basel, Switzerland) · 2025Review
- Cell Population-resolved Multiomics Atlas of the Developing Lung.American journal of respiratory cell and molecular biology · 2025Article
- Artificial Intelligence and Neuroscience: Transformative Synergies in Brain Research and Clinical Applications.Journal of clinical medicine · 2025Review
- Review
- Single-Cell Transcriptomic Profiling Identifies Molecular Phenotypes of Newborn Human Lung Cells.Genes · 2024Article
- Viral afterlife: SARS-CoV-2 as a reservoir of immunomimetic peptides that reassemble into proinflammatory supramolecular complexes.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- LungMAP Portal Ecosystem: Systems-level Exploration of the Lung.American journal of respiratory cell and molecular biology · 2024Article
- Systematic proteomics profiling of lysine crotonylation of the lung at Pseudoglandular and Canalicular phases in human fetus.Proteome science · 2023Article
- Article
- Regionally distinct progenitor cells in the lower airway give rise to neuroendocrine and multiciliated cells in the developing human lung.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- Mutation-class dependent signatures outweigh disease-associated processes in cystic fibrosis cells.Cell & bioscience · 2023Article
- Integrated transcriptome-proteome analyses of human stem cells reveal source-dependent differences in their regenerative signature.Stem cell reports · 2023Article
- R-SPONDIN2Developmental cell · 2022Article
- Molecular Modelling Hurdle in the Next-Generation Sequencing Era.International journal of molecular sciences · 2022Article
- Three-dimensional feature matching improves coverage for single-cell proteomics based on ion mobility filtering.Cell systems · 2022Article
Corrections and comments
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Authors and funding
14 authors.
Funding
Abstract
Systems biology uses computational approaches to integrate diverse data types to understand cell and organ behavior. Data derived from complementary technologies, for example transcriptomic and proteomic analyses, are providing new insights into development and disease. We compared mRNA and protein profiles from purified endothelial, epithelial, immune, and mesenchymal cells from normal human infant lung tissue. Signatures for each cell type were identified and compared at both mRNA and protein levels. Cell-specific biological processes and pathways were predicted by analysis of concordant and discordant RNA-protein pairs. Cell clustering and gene set enrichment comparisons identified shared versus unique processes associated with transcriptomic and/or proteomic data. Clear cell-cell correlations between mRNA and protein data were obtained from each cell type. Approximately 40% of RNA-protein pairs were coherently expressed. While the correlation between RNA and their protein products was relatively low (Spearman rank coefficient
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