ArticleDatabase : the journal of biological databases and curation2011
ppiTrim: constructing non-redundant and up-to-date interactomes.
Article in Database : the journal of biological databases and curation, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- IHP-PING-generating integrated human protein-protein interaction networks on-the-fly.Briefings in bioinformatics · 2021Article
- Mechanism-based disease similarity.Journal of rare diseases research & treatment · 2016Article
- Heterogeneous Network Edge Prediction: A Data Integration Approach to Prioritize Disease-Associated Genes.PLoS computational biology · 2015Article
- DeCoaD: determining correlations among diseases using protein interaction networks.BMC research notes · 2015Article
- iCTNet2: integrating heterogeneous biological interactions to understand complex traits.F1000Research · 2015Article
- Identification of core T cell network based on immunome interactome.BMC systems biology · 2014Article
- Relating diseases by integrating gene associations and information flow through protein interaction network.PloS one · 2014Article
- Building a hierarchical organization of protein complexes out of protein association data.PloS one · 2014Article
- Digenic inheritance in medical genetics.Journal of medical genetics · 2013Review
- iRefR: an R package to manipulate the iRefIndex consolidated protein interaction database.BMC bioinformatics · 2011Article
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Authors and funding
2 authors.
Funding
Abstract
Robust advances in interactome analysis demand comprehensive, non-redundant and consistently annotated data sets. By non-redundant, we mean that the accounting of evidence for every interaction should be faithful: each independent experimental support is counted exactly once, no more, no less. While many interactions are shared among public repositories, none of them contains the complete known interactome for any model organism. In addition, the annotations of the same experimental result by different repositories often disagree. This brings up the issue of which annotation to keep while consolidating evidences that are the same. The iRefIndex database, including interactions from most popular repositories with a standardized protein nomenclature, represents a significant advance in all aspects, especially in comprehensiveness. However, iRefIndex aims to maintain all information/annotation from original sources and requires users to perform additional processing to fully achieve the aforementioned goals. Another issue has to do with protein complexes. Some databases represent experimentally observed complexes as interactions with more than two participants, while others expand them into binary interactions using spoke or matrix model. To avoid untested interaction information buildup, it is preferable to replace the expanded protein complexes, either from spoke or matrix models, with a flat list of complex members. To address these issues and to achieve our goals, we have developed ppiTrim, a script that processes iRefIndex to produce non-redundant, consistently annotated data sets of physical interactions. Our script proceeds in three stages: mapping all interactants to gene identifiers and removing all undesired raw interactions, deflating potentially expanded complexes, and reconciling for each interaction the annotation labels among different source databases. As an illustration, we have processed the three largest organismal data sets: yeast, human and fruitfly. While ppiTrim can resolve most apparent conflicts between different labelings, we also discovered some unresolvable disagreements mostly resulting from different annotation policies among repositories. Database URL: http://www.ncbi.nlm.nih.gov/CBBresearch/Yu/downloads/ppiTrim.html.
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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.