Case studies: applying network controllability in cancer
Kanhaiya, K., Czeizler, E., Gratie, C., Ion, P.: Controlling directed protein interaction networks in cancer. Technical Report 1155, Turku Centre for Computer Science (2016)
Target structural network controllability method that is the core of this pipeline
Czeizler, E., Gratie, C., Chiu, W.K., Kanhaiya, K., Petre, I.: Target controllability of linear networks. In: Bartocci, E., Lio, P., Paoletti, N. (eds.) Computational Methods in Systems Biology. Lecture Notes in Bioinformatics, vol. 9859, pp. 67--81. Springer, (2016)
The original paper inspiring our research direction: method to identify the set of driver nodes with the time-dependent control that can guide the system's entire dynamics.
Liu, Y.-Y., Slotine, J.-J., Barabasi, A.-L.: Controllability of complex networks. Nature 473(7346), 167--173 (2011). doi:10.1038/nature10011
Anduril pipeline framework: the underlying framework for our backend analysis pipeline
Ovaska, K., Laakso, M., Haapa-Paananen, S., Louhimo, R., Chen, P., Aittoaki, V., Valo, E.: Large-scale data integration framework provides a comprehensive view on glioblastoma multiforme. Genome medicine 2(9), 65 (2010). doi:10.1186/gm186
Moksiskaan - the tool to integrate pathway data from different sources into comprehensive biomolecular networks
Laakso, M., Hautaniemi, S.: Integrative platform to translate gene sets to networks. Bioinformatics 26, 1802--1803 (2010). doi:10.1093/bioinformatics/btq277