ArticleBMC genomics2012
atBioNet--an integrated network analysis tool for genomics and biomarker discovery.
Article in BMC genomics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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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.
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Who cites it
13 citing papers in PubMed.
- Exploring the Novel Computational Drug Target and Associated Key Pathways of Oral Cancer.Current issues in molecular biology · 2022Article
- From protein-protein interactions to protein co-expression networks: a new perspective to evaluate large-scale proteomic data.EURASIP journal on bioinformatics & systems biology · 2017Review
- Protein-protein interaction analysis to identify biomarker networks for endometriosis.Experimental and therapeutic medicine · 2017Article
- In silico identification of potential key regulatory factors in smoking-induced lung cancer.BMC medical genomics · 2017Article
- Network-Based Protein Biomarker Discovery Platforms.Genomics & informatics · 2016Review
- Biological Networks for Cancer Candidate Biomarkers Discovery.Cancer informatics · 2016Review
- Applications of systems approaches in the study of rheumatic diseases.The Korean journal of internal medicine · 2015Review
- Decoding Cellular Dynamics in Epidermal Growth Factor Signaling Using a New Pathway-Based Integration Approach for Proteomics and Transcriptomics Data.Frontiers in genetics · 2015Article
- Pathway and network approaches for identification of cancer signature markers from omics data.Journal of Cancer · 2015Review
- Epigenetic landscape correlates with genetic subtype but does not predict outcome in childhood acute lymphoblastic leukemia.Epigenetics · 2015Article
- NetworkAnalyst--integrative approaches for protein-protein interaction network analysis and visual exploration.Nucleic acids research · 2014Article
- Structure and dynamics of molecular networks: a novel paradigm of drug discovery: a comprehensive review.Pharmacology & therapeutics · 2013Review
- Navigating traditional chinese medicine network pharmacology and computational tools.Evidence-based complementary and alternative medicine : eCAM · 2013Article
Corrections and comments
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Authors and funding
15 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundLarge amounts of mammalian protein-protein interaction (PPI) data have been generated and are available for public use. From a systems biology perspective, Proteins/genes interactions encode the key mechanisms distinguishing disease and health, and such mechanisms can be uncovered through network analysis. An effective network analysis tool should integrate different content-specific PPI databases into a comprehensive network format with a user-friendly platform to identify key functional modules/pathways and the underlying mechanisms of disease and toxicity.
resultsatBioNet integrates seven publicly available PPI databases into a network-specific knowledge base. Knowledge expansion is achieved by expanding a user supplied proteins/genes list with interactions from its integrated PPI network. The statistically significant functional modules are determined by applying a fast network-clustering algorithm (SCAN: a Structural Clustering Algorithm for Networks). The functional modules can be visualized either separately or together in the context of the whole network. Integration of pathway information enables enrichment analysis and assessment of the biological function of modules. Three case studies are presented using publicly available disease gene signatures as a basis to discover new biomarkers for acute leukemia, systemic lupus erythematosus, and breast cancer. The results demonstrated that atBioNet can not only identify functional modules and pathways related to the studied diseases, but this information can also be used to hypothesize novel biomarkers for future analysis.
conclusionatBioNet is a free web-based network analysis tool that provides a systematic insight into proteins/genes interactions through examining significant functional modules. The identified functional modules are useful for determining underlying mechanisms of disease and biomarker discovery. It can be accessed at: http://www.fda.gov/ScienceResearch/BioinformaticsTools/ucm285284.htm.
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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.