ReviewCurrent opinion in genetics & development2013
Genotype to phenotype via network analysis.
Review in Current opinion in genetics & development, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 71 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
71 citing papers in PubMed.
- Mapping cross-domain drivers of Alzheimer's disease risk through integrated network analysis.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026Article
- Network resilience of the human interactome to pan-cancer mutations reveals conserved pathway vulnerabilities.iScience · 2026Article
- Network-based framework for studying etiology and phenotypic diversity in primary ciliopathies.Genome biology · 2026Article
- Mapping cross-domain drivers of Alzheimer's disease risk through integrated network analysis.bioRxiv : the preprint server for biology · 2025Article
- Systematic identification of structure-specific protein-protein interactions.Molecular systems biology · 2024Article
- The Extent of Edgetic Perturbations in the Human Interactome Caused by Population-Specific Mutations.Biomolecules · 2023Article
- otargen: GraphQL-based R package for tidy data accessing and processing from Open Targets Genetics.Bioinformatics (Oxford, England) · 2023Article
- Network expansion of genetic associations defines a pleiotropy map of human cell biology.Nature genetics · 2023Article
- Article
- Integrative pathway and network analysis provide insights on flooding-tolerance genes in soybean.Scientific reports · 2023Article
- Hierarchical association of COPD to principal genetic components of biological systems.PloS one · 2023Article
- Translational Bioinformatics for Human Reproductive Biology Research: Examples, Opportunities and Challenges for a Future Reproductive Medicine.International journal of molecular sciences · 2022Review
- Topsy-Turvy: integrating a global view into sequence-based PPI prediction.Bioinformatics (Oxford, England) · 2022Article
- Article
- A Visual Phenotype-Based Differential Diagnosis Process for Rare Diseases.Interdisciplinary sciences, computational life sciences · 2022Article
- Disease-specific interactome alterations via epichaperomics: the case for Alzheimer's disease.The FEBS journal · 2022Review
- Manifold medicine: A schema that expands treatment dimensionality.Drug discovery today · 2022Article
- Subtypes of relapsing-remitting multiple sclerosis identified by network analysis.Frontiers in digital health · 2022Article
- Systems biology approaches to unravel the molecular and genetic architecture of Alzheimer's disease and related tauopathies.Neurobiology of disease · 2021Review
- Genetic dissection of complex traits using hierarchical biological knowledge.PLoS computational biology · 2021Article
11 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.
Funding
Abstract
A prime objective of genomic medicine is the identification of disease-causing mutations and the mechanisms by which such events result in disease. As most disease phenotypes arise not from single genes and proteins but from a complex network of molecular interactions, a priori knowledge about the molecular network serves as a framework for biological inference and data mining. Here we review recent developments at the interface of biological networks and mutation analysis. We examine how mutations may be treated as a perturbation of the molecular interaction network and what insights may be gained from taking this perspective. We review work that aims to transform static networks into rich context-dependent networks and recent attempts to integrate non-coding RNAs into such analysis. Finally, we conclude with an overview of the many challenges and opportunities that lie ahead.
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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.