Automatic pathway building in biological association networks

Background: Scientific literature is a source of the most reliable and comprehensive knowledge about molecular interaction networks. Formalization of this knowledge is necessary for computational analysis and is achieved by automatic fact extraction using various text-mining algorithms. Most of these techniques suffer from high false positive rates and redundancy of the extracted information. The extracted facts form a large network with no pathways defined. Results: We describe the methodology for automatic curation of Biological Association Networks (BANs) derived by a natural language processing technology called Medscan. The curated data is used for automatic pathway reconstruction. The algorithm for the reconstruction of signaling pathways is also described and validated by comparison with manually curated pathways and tissuespecific gene expression profiles. Conclusion: Biological Association Networks extracted by MedScan technology contain sufficient information for constructin...

• Type: Journal
• Year: 2006
• Where: BMCBI
• Authors: Anton Yuryev, Zufar Mulyukov, Ekaterina Kotelnikova, Sergei Maslov, Sergei Egorov, Alexander Nikitin, Nikolai Daraselia, Ilya Mazo
• Keywords: Biological Association Networks, BMCBI 2006, Free Demo Version, Medscan Technology