ArticleGenome biology2010
A human functional protein interaction network and its application to cancer data analysis.
Article in Genome biology, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 381 papers, 2 of them syntheses that pooled it.
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
381 citing papers in PubMed, 2 syntheses or guidelines pooled it, 712 citations in OpenAlex.
- Medication-Related Osteonecrosis of the Jaw: A Systematic Review and a Bioinformatic Analysis.International journal of molecular sciences · 2023Pooled it
- New Insights on the Regulatory Gene Network Disturbed in Central Areolar Choroidal Dystrophy-Beyond Classical Gene Candidates.Frontiers in genetics · 2022Pooled it
- Adjuvant Effect of Molecular Iodine in Conventional Chemotherapy for Breast Cancer. Randomized Pilot Study.Nutrients · 2019Trial
- In vivo effects of dexamethasone on blood gene expression in ataxia telangiectasia.Molecular and cellular biochemistry · 2018Trial
- GWAS of Tau-Neurodegeneration Mismatch Identifies New Risk Loci for Susceptibility to Tau.CNS neuroscience & therapeutics · 2026Article
- Accelerating Leigh syndrome drug discovery through deep learning screening in brain organoids.Nature communications · 2026Article
- Transcriptomic data and biomedical literature synergize in finding pharmacologic gene regulators.bioRxiv : the preprint server for biology · 2026Article
- MELGene: knowledge-enhanced multimodel ensemble learning for disease-gene association prediction.Briefings in bioinformatics · 2026Article
- Identification of cancer mini-drivers by deciphering selective landscape in the cancer genome.Briefings in bioinformatics · 2026Article
- Genome-wide association study of atopic and autoimmune comorbidities in alopecia areata.Frontiers in immunology · 2026Article
- DriverSub-SVM: a machine learning approach for cancer subtype classification by integrating patient-specific and global driver genes.BMC bioinformatics · 2025Article
- Application of Large Language Models for Annotating Genes into Reactome Pathways.bioRxiv : the preprint server for biology · 2025Article
- Systems-Level Integration of Multi-Omics Identifies Genetic Modifiers of TANGO2 Deficiency Disorder.Biomolecules · 2025Article
- Contrasting cannabinoid receptor 2 (CB2R)-mediated responses in two different models of Blood Brain Barrier in the context of HIV.Research square · 2025Article
- Harnessing plasma transcriptomics for non-invasive cancer biomarker identification: a comprehensive review.Discover oncology · 2025Review
- Serum proteome analysis detects early molecular signatures of disease progression in IgA nephropathy.Clinical kidney journal · 2025Article
- Transcriptomic profiling of endothelial progenitor cells in post-COVID-19 patients: Insights at 3 and 6-month post-infection.iScience · 2025Article
- Network centric identification of PI3K/Akt hub proteins as key oncogenic drivers and therapeutic targets.Scientific reports · 2025Article
- Cross-Tissue Specificity of Pediatric DNA Methylation Associated With Cumulative Family Stress.Developmental psychobiology · 2025Article
- MLGCN-Driver: a cancer driver gene identification method based on multi-layer graph convolutional neural network.BMC bioinformatics · 2025Article
321 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
3 authors at 3 institutions in 2 countries.
Funding
Abstract
backgroundOne challenge facing biologists is to tease out useful information from massive data sets for further analysis. A pathway-based analysis may shed light by projecting candidate genes onto protein functional relationship networks. We are building such a pathway-based analysis system.
resultsWe have constructed a protein functional interaction network by extending curated pathways with non-curated sources of information, including protein-protein interactions, gene coexpression, protein domain interaction, Gene Ontology (GO) annotations and text-mined protein interactions, which cover close to 50% of the human proteome. By applying this network to two glioblastoma multiforme (GBM) data sets and projecting cancer candidate genes onto the network, we found that the majority of GBM candidate genes form a cluster and are closer than expected by chance, and the majority of GBM samples have sequence-altered genes in two network modules, one mainly comprising genes whose products are localized in the cytoplasm and plasma membrane, and another comprising gene products in the nucleus. Both modules are highly enriched in known oncogenes, tumor suppressors and genes involved in signal transduction. Similar network patterns were also found in breast, colorectal and pancreatic cancers.
conclusionsWe have built a highly reliable functional interaction network upon expert-curated pathways and applied this network to the analysis of two genome-wide GBM and several other cancer data sets. The network patterns revealed from our results suggest common mechanisms in the cancer biology. Our system should provide a foundation for a network or pathway-based analysis platform for cancer and other diseases.
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.