Systems biology uses a bioinformatics approach to analyze complete biological systems. It involves integrating various types of high-throughput experimental data as well as curated knowledge through techniques such as mathematical modeling, data mining, and network analysis to study systems-level properties and behaviors that emerge from complex interactions between biological components like genes, proteins, and metabolites. Key challenges include integrating large and heterogeneous datasets from multiple sources that use different formats and identifiers as well as developing computational models that require detailed quantitative knowledge about many system parameters. Text mining of the biomedical literature plays an important role by automatically extracting information about biological entities and their relationships to build networks and associations.
151. Acknowledgments
Protein Literature mining
networks Sune Frankild
Evangelos Pafilis
Christian von Mering
Janos Binder
Damian Szklarczyk
Kalliopi Tsafou
Michael Kuhn
Alberto Santos
Manuel Stark
Heiko Horn
Samuel Chaffron
Michael Kuhn
Chris Creevey
Nigel Brown
Jean Muller
Reinhardt Schneider
Tobias Doerks
Sean O’Donoghue
Philippe Julien
Alexander Roth
Milan Simonovic
Jan Korbel
Berend Snel
Martijn Huynen