ArticleScientific reports2016
Systems view of adipogenesis via novel omics-driven and tissue-specific activity scoring of network functional modules.
Article in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Article
- Stages of preadipocyte differentiation: biomarkers and pathways for extracellular structural remodeling.Hereditas · 2022Article
- Transcriptome-wide association study identifies multiple genes associated with childhood body mass index.International journal of obesity (2005) · 2021Article
- History and Future Perspectives on the Discipline of Quantitative Systems Pharmacology Modeling and Its Applications.Frontiers in physiology · 2021Review
- DNA methylation during human adipogenesis and the impact of fructose.Genes & nutrition · 2020Article
- Regulatory Crosstalk of Doxorubicin, Estradiol and TNFα Combined Treatment in Breast Cancer-derived Cell Lines.Scientific reports · 2019Article
- The Power of LC-MS Based Multiomics: Exploring Adipogenic Differentiation of Human Mesenchymal Stem/Stromal Cells.Molecules (Basel, Switzerland) · 2019Article
- Systematic exploration of cell morphological phenotypes associated with a transcriptomic query.Nucleic acids research · 2018Article
- Co-Expression Network Analysis of AMPK and Autophagy Gene Products during Adipocyte Differentiation.International journal of molecular sciences · 2018Article
- Exploring the cellular network of metabolic flexibility in the adipose tissue.Genes & nutrition · 2018Review
- Combined use of protein biomarkers and network analysis unveils deregulated regulatory circuits in Duchenne muscular dystrophy.PloS one · 2018Article
- Graphical Modeling Meets Systems Pharmacology.Gene regulation and systems biology · 2017Article
Corrections and comments
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The investigation of the complex processes involved in cellular differentiation must be based on unbiased, high throughput data processing methods to identify relevant biological pathways. A number of bioinformatics tools are available that can generate lists of pathways ranked by statistical significance (i.e. by p-value), while ideally it would be desirable to functionally score the pathways relative to each other or to other interacting parts of the system or process. We describe a new computational method (Network Activity Score Finder - NASFinder) to identify tissue-specific, omics-determined sub-networks and the connections with their upstream regulator receptors to obtain a systems view of the differentiation of human adipocytes. Adipogenesis of human SBGS pre-adipocyte cells in vitro was monitored with a transcriptomic data set comprising six time points (0, 6, 48, 96, 192, 384 hours). To elucidate the mechanisms of adipogenesis, NASFinder was used to perform time-point analysis by comparing each time point against the control (0 h) and time-lapse analysis by comparing each time point with the previous one. NASFinder identified the coordinated activity of seemingly unrelated processes between each comparison, providing the first systems view of adipogenesis in culture. NASFinder has been implemented into a web-based, freely available resource associated with novel, easy to read visualization of omics data sets and network modules.
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