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Network biology: Large-scale data and text mining
This document discusses network biology and large-scale text mining. It describes using computational predictions, experimental data, and text mining to build protein interaction networks for various species from databases with different formats and quality. It also discusses using named entity recognition, expansion rules, and flexible matching to extract information from millions of abstracts and articles to identify relationships between biological entities like proteins, complexes, pathways, tissues, compartments, and diseases. The extracted information is integrated into web interfaces and services to allow visualization and exploration of the biological networks and relationships.
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- 91. Acknowledgments STRING Christian von Mering Damian Szklarczyk Michael Kuhn ManuelStark Samuel Chaffron Chris Creevey Jean Muller Tobias Doerks Philippe Julien Alexander Roth Milan Simonovic Jan Korbel Berend Snel Martijn Huynen Peer Bork Text mining Sune Frankild Evangelos Pafilis Kalliopi Tsafou Alberto Santos Janos Binder Heiko Horn Michael Kuhn Nigel Brown Reinhardt Schneider Sean O’ Donoghue