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• W2160591663 abstract "Abstract Motivation: Pathway diagrams from PubMed and World Wide Web (WWW) contain valuable highly curated information difficult to reach without tools specifically designed and customized for the biological semantics and high-content density of the images. There is currently no search engine or tool that can analyze pathway images, extract their pathway components (molecules, genes, proteins, organelles, cells, organs, etc.) and indicate their relationships. Results: Here, we describe a resource of pathway diagrams retrieved from article and web-page images through optical character recognition, in conjunction with data mining and data integration methods. The recognized pathways are integrated into the BiologicalNetworks research environment linking them to a wealth of data available in the BiologicalNetworks' knowledgebase, which integrates data from &gt;100 public data sources and the biomedical literature. Multiple search and analytical tools are available that allow the recognized cellular pathways, molecular networks and cell/tissue/organ diagrams to be studied in the context of integrated knowledge, experimental data and the literature. Availability: BiologicalNetworks software and the pathway repository are freely available at www.biologicalnetworks.org. Contact: baitaluk@sdsc.edu Supplementary information: Supplementary data are available at Bioinformatics online." @default.
• W2160591663 created "2016-06-24" @default.
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• W2160591663 date "2012-01-20" @default.
• W2160591663 modified "2023-09-23" @default.
• W2160591663 title "Mining and integration of pathway diagrams from imaging data" @default.
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• W2160591663 doi "https://doi.org/10.1093/bioinformatics/bts018" @default.
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