ReviewJournal of proteomics2010
It's the machine that matters: Predicting gene function and phenotype from protein networks.
Review in Journal of proteomics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 61 papers, 1 of them a synthesis 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
61 citing papers in PubMed, 1 synthesis or guideline pooled it, 126 citations in OpenAlex.
- Pooled it
- Predicting functions of uncharacterized gene products from microbial communities.Nature biotechnology · 2026Article
- A protein interactome for the last eukaryotic common ancestor illuminates the biochemical basis of modern genetic diseases.Cell genomics · 2026Article
- Revisiting co-expression-based automated function prediction in yeast with neural networks and updated Gene Ontology annotations.PloS one · 2026Article
- Advances in ciliary proteomics - towards cracking the hidden proteome code of cilia.Journal of cell science · 2025Review
- Prioritizing drug targets by perturbing biological network response functions.PLoS computational biology · 2024Article
- Ancient eukaryotic protein interactions illuminate modern genetic traits and disorders.bioRxiv : the preprint server for biology · 2024Article
- Protein-protein interactions: Methods, databases, and applications in virus-host study.World journal of virology · 2021Review
- Article
- hu.MAP 2.0: integration of over 15,000 proteomic experiments builds a global compendium of human multiprotein assemblies.Molecular systems biology · 2021Article
- uKIN Combines New and Prior Information with Guided Network Propagation to Accurately Identify Disease Genes.Cell systems · 2020Article
- Network Analysis of Murine Cortical Dynamics Implicates Untuned Neurons in Visual Stimulus Coding.Cell reports · 2020Article
- BiomeNet: a database for construction and analysis of functional interaction networks for any species with a sequenced genome.Bioinformatics (Oxford, England) · 2020Article
- Network Diffusion Promotes the Integrative Analysis of Multiple Omics.Frontiers in genetics · 2020Review
- HumanNet v2: human gene networks for disease research.Nucleic acids research · 2019Article
- Quantitative proteomic analysis of prostate tissue specimens identifies deregulated protein complexes in primary prostate cancer.Clinical proteomics · 2019Article
- Predicting Parkinson's Disease Genes Based on Node2vec and Autoencoder.Frontiers in genetics · 2019Article
- Gene module analysis of juvenile myelomonocytic leukemia and screening of anticancer drugs.Oncology reports · 2018Article
- Genomic data integration systematically biases interactome mapping.PLoS computational biology · 2018Article
- Topological estimation of signal flow in complex signaling networks.Scientific reports · 2018Article
1 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
2 authors at 1 institution in 1 country.
Funding
Abstract
Increasing knowledge about the organization of proteins into complexes, systems, and pathways has led to a flowering of theoretical approaches for exploiting this knowledge in order to better learn the functions of proteins and their roles underlying phenotypic traits and diseases. Much of this body of theory has been developed and tested in model organisms, relying on their relative simplicity and genetic and biochemical tractability to accelerate the research. In this review, we discuss several of the major approaches for computationally integrating proteomics and genomics observations into integrated protein networks, then applying guilt-by-association in these networks in order to identify genes underlying traits. Recent trends in this field include a rising appreciation of the modular network organization of proteins underlying traits or mutational phenotypes, and how to exploit such protein modularity using computational approaches related to the internet search algorithm PageRank. Many protein network-based predictions have recently been experimentally confirmed in yeast, worms, plants, and mice, and several successful approaches in model organisms have been directly translated to analyze human disease, with notable recent applications to glioma and breast cancer prognosis.
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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.