ArticleBioinformatics (Oxford, England)2013
Differential network analysis for the identification of condition-specific pathway activity and regulation.
Article in Bioinformatics (Oxford, England), 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.
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Who cites it
35 citing papers in PubMed, 72 citations in OpenAlex.
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- From time-series transcriptomics to gene regulatory networks: A review on inference methods.PLoS computational biology · 2023Review
- Single-cell gene set enrichment analysis and transfer learning for functional annotation of scRNA-seq data.NAR genomics and bioinformatics · 2023Article
- Rational Approach to Finding Genes Encoding Molecular Biomarkers: Focus on Breast Cancer.Genes · 2022Article
- CorDiffViz: an R package for visualizing multi-omics differential correlation networks.BMC bioinformatics · 2021Article
- Network Modeling in Biology: Statistical Methods for Gene and Brain Networks.Statistical science : a review journal of the Institute of Mathematical Statistics · 2021Article
- Generating Ensembles of Gene Regulatory Networks to Assess Robustness of Disease Modules.Frontiers in genetics · 2020Article
- PMINR: Pointwise Mutual Information-Based Network Regression - With Application to Studies of Lung Cancer and Alzheimer's Disease.Frontiers in genetics · 2020Article
- Integrated transcriptomics reveals master regulators of lung adenocarcinoma and novel repositioning of drug candidates.Cancer medicine · 2019Article
- A Machine Learning Method for Identifying Critical Interactions Between Gene Pairs in Alzheimer's Disease Prediction.Frontiers in neurology · 2019Article
- A Tool for Visualization and Analysis of Single-Cell RNA-Seq Data Based on Text Mining.Frontiers in genetics · 2019Article
- Differential gene regulatory networks in development and disease.Cellular and molecular life sciences : CMLS · 2018Review
- The DifferentialNet database of differential protein-protein interactions in human tissues.Nucleic acids research · 2018Article
- Detecting phenotype-driven transitions in regulatory network structure.NPJ systems biology and applications · 2018Article
- DiffGRN: differential gene regulatory network analysis.International journal of data mining and bioinformatics · 2018Article
- JDINAC: joint density-based non-parametric differential interaction network analysis and classification using high-dimensional sparse omics data.Bioinformatics (Oxford, England) · 2017Article
- The impact of microRNAs on transcriptional heterogeneity and gene co-expression across single embryonic stem cells.Nature communications · 2017Article
- Altered Pathway Analyzer: A gene expression dataset analysis tool for identification and prioritization of differentially regulated and network rewired pathways.Scientific reports · 2017Article
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
Abstract
motivationIdentification of differential expressed genes has led to countless new discoveries. However, differentially expressed genes are only a proxy for finding dysregulated pathways. The problem is to identify how the network of regulatory and physical interactions rewires in different conditions or in disease.
resultsWe developed a procedure named DINA (DIfferential Network Analysis), which is able to identify set of genes, whose co-regulation is condition-specific, starting from a collection of condition-specific gene expression profiles. DINA is also able to predict which transcription factors (TFs) may be responsible for the pathway condition-specific co-regulation. We derived 30 tissue-specific gene networks in human and identified several metabolic pathways as the most differentially regulated across the tissues. We correctly identified TFs such as Nuclear Receptors as their main regulators and demonstrated that a gene with unknown function (YEATS2) acts as a negative regulator of hepatocyte metabolism. Finally, we showed that DINA can be used to make hypotheses on dysregulated pathways during disease progression. By analyzing gene expression profiles across primary and transformed hepatocytes, DINA identified hepatocarcinoma-specific metabolic and transcriptional pathway dysregulation. AVAILABILITY: We implemented an on-line web-tool http://dina.tigem.it enabling the user to apply DINA to identify tissue-specific pathways or gene signatures. CONTACT: dibernardo@tigem.it SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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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.