ArticleBMC bioinformatics2009
Inferring protein function by domain context similarities in protein-protein interaction networks.
Article in BMC bioinformatics, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 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
12 citing papers in PubMed, 36 citations in OpenAlex.
- DA-HGL: a domain-augmented heterogeneous graph learning framework for protein function prediction.Briefings in bioinformatics · 2025Article
- Article
- Protein function annotation based on heterogeneous biological networks.BMC bioinformatics · 2022Article
- A tensor-based bi-random walks model for protein function prediction.BMC bioinformatics · 2022Article
- NPF:network propagation for protein function prediction.BMC bioinformatics · 2020Article
- Article
- Identification of Antifungal Targets Based on Computer Modeling.Journal of fungi (Basel, Switzerland) · 2018Review
- Ceratocystis cacaofunesta genome analysis reveals a large expansion of extracellular phosphatidylinositol-specific phospholipase-C genes (PI-PLC).BMC genomics · 2018Article
- An efficient method for protein function annotation based on multilayer protein networks.Human genomics · 2016Article
- Improving protein function prediction using domain and protein complexes in PPI networks.BMC systems biology · 2014Article
- Networked-based characterization of extracellular matrix proteins from adult mouse pulmonary and aortic valves.Journal of proteome research · 2011Article
- Inference of surface membrane factors of HIV-1 infection through functional interaction networks.PloS one · 2010Article
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 1 institution in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundGenome sequencing projects generate massive amounts of sequence data but there are still many proteins whose functions remain unknown. The availability of large scale protein-protein interaction data sets makes it possible to develop new function prediction methods based on protein-protein interaction (PPI) networks. Although several existing methods combine multiple information resources, there is no study that integrates protein domain information and PPI networks to predict protein functions.
resultsThe domain context similarity can be a useful index to predict protein function similarity. The prediction accuracy of our method in yeast is between 63%-67%, which outperforms the other methods in terms of ROC curves.
conclusionThis paper presents a novel protein function prediction method that combines protein domain composition information and PPI networks. Performance evaluations show that this method outperforms existing methods.
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.