ArticlePloS one2010
DEGAS: de novo discovery of dysregulated pathways in human diseases.
Article in PloS one, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 67 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
67 citing papers in PubMed, 123 citations in OpenAlex.
- A Framework for Benchmarking Pathway Reconstruction Algorithms.bioRxiv : the preprint server for biology · 2026Article
- A statistical physics approach for disease module detection.Genome research · 2022Article
- De novo identification of maximally deregulated subnetworks based on multi-omics data with DeRegNet.BMC bioinformatics · 2022Article
- Drug repositioning by merging active subnetworks validated in cancer and COVID-19.Scientific reports · 2021Article
- Pathways to Parkinson's disease: a spotlight on 14-3-3 proteins.NPJ Parkinson's disease · 2021Review
- 14-3-3 Proteins: Novel Pharmacological Targets in Neurodegenerative Diseases.Trends in pharmacological sciences · 2021Review
- Molecular networks in Network Medicine: Development and applications.Wiley interdisciplinary reviews. Systems biology and medicine · 2020Review
- Identifying Drug Sensitivity Subnetworks with NETPHIX.iScience · 2020Article
- Finding disease modules for cancer and COVID-19 in gene co-expression networks with the Core&Peel method.Scientific reports · 2020Article
- Identification of conserved evolutionary trajectories in tumors.Bioinformatics (Oxford, England) · 2020Article
- A comparison of mechanistic signaling pathway activity analysis methods.Briefings in bioinformatics · 2019Review
- Combinatorial Detection of Conserved Alteration Patterns for Identifying Cancer Subnetworks.GigaScience · 2019Article
- Towards a data-integrated cell.Nature communications · 2019Article
- Article
- Module-detection approaches for the integration of multilevel omics data highlight the comprehensive response of Aspergillus fumigatus to caspofungin.BMC systems biology · 2018Article
- Identification of pathways significantly associated with spondyloarthropathy/ankylosing spondylitis using the sub‑pathway method.Molecular medicine reports · 2018Article
- 14-3-3 Proteins Reduce Cell-to-Cell Transfer and Propagation of Pathogenic α-Synuclein.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2018Article
- ModuleDiscoverer: Identification of regulatory modules in protein-protein interaction networks.Scientific reports · 2018Article
- G2019S LRRK2 Increases Stress Susceptibility Through Inhibition of DAF-16 Nuclear Translocation in a 14-3-3 Associated-Manner inFrontiers in neuroscience · 2018Article
- Network-Based Coverage of Mutational Profiles Reveals Cancer Genes.Cell systems · 2017Article
7 more citing papers are in PubMed but not listed here.
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
No grant is acknowledged in the PubMed record.
Abstract
backgroundMolecular studies of the human disease transcriptome typically involve a search for genes whose expression is significantly dysregulated in sick individuals compared to healthy controls. Recent studies have found that only a small number of the genes in human disease-related pathways show consistent dysregulation in sick individuals. However, those studies found that some pathway genes are affected in most sick individuals, but genes can differ among individuals. While a pathway is usually defined as a set of genes known to share a specific function, pathway boundaries are frequently difficult to assign, and methods that rely on such definition cannot discover novel pathways. Protein interaction networks can potentially be used to overcome these problems. METHODOLOGY/PRINCIPAL
findingsWe present DEGAS (DysrEgulated Gene set Analysis via Subnetworks), a method for identifying connected gene subnetworks significantly enriched for genes that are dysregulated in specimens of a disease. We applied DEGAS to seven human diseases and obtained statistically significant results that appear to home in on compact pathways enriched with hallmarks of the diseases. In Parkinson's disease, we provide novel evidence for involvement of mRNA splicing, cell proliferation, and the 14-3-3 complex in the disease progression. DEGAS is available as part of the MATISSE software package (http://acgt.cs.tau.ac.il/matisse). CONCLUSIONS/SIGNIFICANCE: The subnetworks identified by DEGAS can provide a signature of the disease potentially useful for diagnosis, pinpoint possible pathways affected by the disease, and suggest targets for drug intervention.
Indexed as
Identifiers
What OpenQuestion holds
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.