Mining and integration of pathway diagrams from imaging data

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 > 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.