ReviewHuman genetics2008
Exploiting the proteome to improve the genome-wide genetic analysis of epistasis in common human diseases.
Review in Human genetics, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 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
42 citing papers in PubMed, 87 citations in OpenAlex.
- A set of serum proteomic biomarkers differentiates celiac children from age and human leukocyte antigen-matched healthy controls.Journal of pediatric gastroenterology and nutrition · 2026Article
- A Review of Feature Selection Methods for Machine Learning-Based Disease Risk Prediction.Frontiers in bioinformatics · 2022Review
- NETWORK-BASED GENOME WIDE STUDY OF HIPPOCAMPAL IMAGING PHENOTYPE IN ALZHEIMER'S DISEASE TO IDENTIFY FUNCTIONAL INTERACTION MODULES.Proceedings of the ... IEEE International Conference on Acoustics, Speech, and Signal Processing. ICASSP (Conference) · 2017Article
- Grid-based stochastic search for hierarchical gene-gene interactions in population-based genetic studies of common human diseases.BioData mining · 2017Article
- Human GRK4γ142V Variant Promotes Angiotensin II Type I Receptor-Mediated Hypertension via Renal Histone Deacetylase Type 1 Inhibition.Hypertension (Dallas, Tex. : 1979) · 2016Article
- An overview of the neurobiology of suicidal behaviors as one meta-system.Molecular psychiatry · 2015Review
- A survey about methods dedicated to epistasis detection.Frontiers in genetics · 2015Review
- Genetic analysis of an allergic rhinitis cohort reveals an intercellular epistasis between FAM134B and CD39.BMC medical genetics · 2014Article
- Genetic interactions found between calcium channel genes modulate amyloid load measured by positron emission tomography.Human genetics · 2014Article
- Article
- PPE38 of Mycobacterium marinum triggers the cross-talk of multiple pathways involved in the host response, as revealed by subcellular quantitative proteomics.Journal of proteome research · 2013Article
- Genetic variants and their interactions in disease risk prediction - machine learning and network perspectives.BioData mining · 2013Article
- eQTL Epistasis - Challenges and Computational Approaches.Frontiers in genetics · 2013Article
- Converging Evidence for Epistasis between ANK3 and Potassium Channel Gene KCNQ2 in Bipolar Disorder.Frontiers in genetics · 2013Article
- An omnibus permutation test on ensembles of two-locus analyses can detect pure epistasis and genetic heterogeneity in genome-wide association studies.SpringerPlus · 2013Article
- Interpreting noncoding genetic variation in complex traits and human disease.Nature biotechnology · 2012Review
- Integration of biological networks and pathways with genetic association studies.Human genetics · 2012Review
- Hierarchical modularity and the evolution of genetic interactomes across species.Molecular cell · 2012Article
- Wrapper-based selection of genetic features in genome-wide association studies through fast matrix operations.Algorithms for molecular biology : AMB · 2012Article
- Article
Corrections and comments
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Authors and funding
2 authors at 2 institutions in 1 country.
Funding
Abstract
One of the central goals of human genetics is the identification of loci with alleles or genotypes that confer increased susceptibility. The availability of dense maps of single-nucleotide polymorphisms (SNPs) along with high-throughput genotyping technologies has set the stage for routine genome-wide association studies that are expected to significantly improve our ability to identify susceptibility loci. Before this promise can be realized, there are some significant challenges that need to be addressed. We address here the challenge of detecting epistasis or gene-gene interactions in genome-wide association studies. Discovering epistatic interactions in high dimensional datasets remains a challenge due to the computational complexity resulting from the analysis of all possible combinations of SNPs. One potential way to overcome the computational burden of a genome-wide epistasis analysis would be to devise a logical way to prioritize the many SNPs in a dataset so that the data may be analyzed more efficiently and yet still retain important biological information. One of the strongest demonstrations of the functional relationship between genes is protein-protein interaction. Thus, it is plausible that the expert knowledge extracted from protein interaction databases may allow for a more efficient analysis of genome-wide studies as well as facilitate the biological interpretation of the data. In this review we will discuss the challenges of detecting epistasis in genome-wide genetic studies and the means by which we propose to apply expert knowledge extracted from protein interaction databases to facilitate this process. We explore some of the fundamentals of protein interactions and the databases that are publicly available.
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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.