Bakgrunn og aktiviteter
During the last few years, network approaches have shown great promise as new tools to analyze and understand complex systems. In biology, network formulations of a system naturally appear in situations ranging from food webs in ecology to biochemical interactions in molecular biology. In particular in the cell, the variety of interactions between genes, proteins and metabolites are well captured by a complex network description. My research is focused on developing both general and specific methods to understand the principles behind the design and organization of biological systems. Most of the work is theoretical and computational in nature, but I am also involved in smaller experimental efforts.
For the seventh year in a row, NTNU is competing in the international Genetically Engineered Machine competition (iGEM) with a team! Our 2013 team was featured on the popular science TV show for NRK (Norwegian Public Broadcasting), Schrödingers Katt.
- General information about the NTNU iGEM participation
- Follow team updates: https://twitter.com/ntnuigem
- Almaas E, Kulkarni RV, Stroud D. 2002. Characterizing the structure of small-world networks. Phys. Rev. Lett. 88, 098101.
- Almaas E, Kovacs B, Vicsek T, Oltvai ZN, Barabasi AL. 2004. Global organization of metabolic fluxes in the bacterium Escherichia coli. Nature 427, 839.
- Almaas E. 2007. Biological impacts and context of network biology. J. Exp. Biol. 210, 1548.
- Motter AE, Gulbahce N, Almaas E, Barabasi AL. 2008. Predicting synthetic rescues in metabolic networks. Mol. Syst. Biol. 4, 168.
- Ghim CM, Almaas E. 2009. Two component genetic switch as a synthetic module with tunable stability. Phys. Rev. Lett. 103, 028101.
- Nowick K, Gernat T, Almaas E, Stubbs L. 2009. Differences in human and chimpanzee gene expression patterns define an evolving network of transcription factors in brain. Proc Natl Acad Sci 106, 22358.
- Navid A, Almaas E. (2012). Genome-level transcription data of Yersinia pestis analyzed with a new metabolic constraint-based aproach. BMC Systems Biology 6, 150.
- MacGillivray M, Ko A, Gruber E, Sawyer M, Almaas E, Holder A. (2017). Robust analysis of fluxes in genome-scale metabolic pathways. Scientific Reports 7, 268.