ArticleBMC bioinformatics2009
POINeT: protein interactome with sub-network analysis and hub prioritization.
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 19 papers.
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Who cites it
19 citing papers in PubMed, 53 citations in OpenAlex.
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- Construction and analysis of the protein-protein interaction networks based on gene expression profiles of Parkinson's disease.PloS one · 2014Article
- Analysis of protein-protein interactions in cross-talk pathways reveals CRKL protein as a novel prognostic marker in hepatocellular carcinoma.Molecular & cellular proteomics : MCP · 2013Article
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- Tools for protein-protein interaction network analysis in cancer research.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2012Review
- Human protein reference database and human proteinpedia as discovery resources for molecular biotechnology.Molecular biotechnology · 2011Article
- Construction and analysis of the protein-protein interaction networks for schizophrenia, bipolar disorder, and major depression.BMC bioinformatics · 2011Article
- Gene expression-based chemical genomics identifies potential therapeutic drugs in hepatocellular carcinoma.PloS one · 2011Article
- Neuregulin 1-erbB4 pathway in schizophrenia: From genes to an interactome.Brain research bulletin · 2010Review
- Protein kinase target discovery from genome-wide messenger RNA expression profiling.The Mount Sinai journal of medicine, New YorkArticle
Corrections and comments
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Authors and funding
10 authors at 6 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundProtein-protein interactions (PPIs) are critical to every aspect of biological processes. Expansion of all PPIs from a set of given queries often results in a complex PPI network lacking spatiotemporal consideration. Moreover, the reliability of available PPI resources, which consist of low- and high-throughput data, for network construction remains a significant challenge. Even though a number of software tools are available to facilitate PPI network analysis, an integrated tool is crucial to alleviate the burden on querying across multiple web servers and software tools.
resultsWe have constructed an integrated web service, POINeT, to simplify the process of PPI searching, analysis, and visualization. POINeT merges PPI and tissue-specific expression data from multiple resources. The tissue-specific PPIs and the numbers of research papers supporting the PPIs can be filtered with user-adjustable threshold values and are dynamically updated in the viewer. The network constructed in POINeT can be readily analyzed with, for example, the built-in centrality calculation module and an integrated network viewer. Nodes in global networks can also be ranked and filtered using various network analysis formulas, i.e., centralities. To prioritize the sub-network, we developed a ranking filtered method (S3) to uncover potential novel mediators in the midbody network. Several examples are provided to illustrate the functionality of POINeT. The network constructed from four schizophrenia risk markers suggests that EXOC4 might be a novel marker for this disease. Finally, a liver-specific PPI network has been filtered with adult and fetal liver expression profiles.
conclusionThe functionalities provided by POINeT are highly improved compared to previous version of POINT. POINeT enables the identification and ranking of potential novel genes involved in a sub-network. Combining with tissue-specific gene expression profiles, PPIs specific to selected tissues can be revealed. The straightforward interface of POINeT makes PPI search and analysis just a few clicks away. The modular design permits further functional enhancement without hampering the simplicity. POINeT is available at (http://poinet.bioinformatics.tw/).
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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.