ArticleNucleic acids research2014
Systematic identification of transcriptional regulatory modules from protein-protein interaction networks.
Article in Nucleic acids research, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 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.
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.
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Who cites it
19 citing papers in PubMed, 30 citations in OpenAlex.
- Assessment of community efforts to advance network-based prediction of protein-protein interactions.Nature communications · 2023Article
- Distinct MUNC lncRNA structural domains regulate transcription of different promyogenic factors.Cell reports · 2022Article
- Tracing TET1 expression in prostate cancer: discovery of malignant cells with a distinct oncogenic signature.Clinical epigenetics · 2021Article
- Classification of protein-protein association rates based on biophysical informatics.BMC bioinformatics · 2021Article
- Integrating binding and expression data to predict transcription factors combined function.BMC genomics · 2020Article
- Using Coarse-Grained Simulations to Characterize the Mechanisms of Protein-Protein Association.Biomolecules · 2020Article
- Targeted-Gene Sequencing to Catch Triple Negative Breast Cancer Heterogeneity before and after Neoadjuvant Chemotherapy.Cancers · 2019Article
- A Central Edge Selection Based Overlapping Community Detection Algorithm for the Detection of Overlapping Structures in Protein⁻Protein Interaction Networks.Molecules (Basel, Switzerland) · 2018Article
- Transcriptional network analysis in frontal cortex in Lewy body diseases with focus on dementia with Lewy bodies.Brain pathology (Zurich, Switzerland) · 2018Article
- Article
- Predicting Protein-protein Association Rates using Coarse-grained Simulation and Machine Learning.Scientific reports · 2017Article
- Inferring condition-specific targets of human TF-TF complexes using ChIP-seq data.BMC genomics · 2017Article
- Driver gene classification reveals a substantial overrepresentation of tumor suppressors among very large chromatin-regulating proteins.Scientific reports · 2016Article
- Genomic analysis of LPS-stimulated myeloid cells identifies a common pro-inflammatory response but divergent IL-10 anti-inflammatory responses.Scientific reports · 2015Article
- Decomposing the space of protein quaternary structures with the interface fragment pair library.BMC bioinformatics · 2015Article
- The female gametophyte: an emerging model for cell type-specific systems biology in plant development.Frontiers in plant science · 2015Review
- Discovering distinct functional modules of specific cancer types using protein-protein interaction networks.BioMed research international · 2015Article
- From blastocyst to gastrula: gene regulatory networks of embryonic stem cells and early mouse embryogenesis.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2014Review
- Identifying transcription factor complexes and their roles.Bioinformatics (Oxford, England) · 2014Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 3 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Transcription factors (TFs) combine with co-factors to form transcriptional regulatory modules (TRMs) that regulate gene expression programs with spatiotemporal specificity. Here we present a novel and generic method (rTRM) for the reconstruction of TRMs that integrates genomic information from TF binding, cell type-specific gene expression and protein-protein interactions. rTRM was applied to reconstruct the TRMs specific for embryonic stem cells (ESC) and hematopoietic stem cells (HSC), neural progenitor cells, trophoblast stem cells and distinct types of terminally differentiated CD4(+) T cells. The ESC and HSC TRM predictions were highly precise, yielding 77 and 96 proteins, of which ∼75% have been independently shown to be involved in the regulation of these cell types. Furthermore, rTRM successfully identified a large number of bridging proteins with known roles in ESCs and HSCs, which could not have been identified using genomic approaches alone, as they lack the ability to bind specific DNA sequences. This highlights the advantage of rTRM over other methods that ignore PPI information, as proteins need to interact with other proteins to form complexes and perform specific functions. The prediction and experimental validation of the co-factors that endow master regulatory TFs with the capacity to select specific genomic sites, modulate the local epigenetic profile and integrate multiple signals will provide important mechanistic insights not only into how such TFs operate, but also into abnormal transcriptional states leading to disease.
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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 Socratic graph.