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BMC Systems Biology|April 6, 2007
METANNOGEN: compiling features of biochemical reactions needed for the reconstruction of metabolic networksChristoph Gille, Sabrina Hoffmann, Hermann-Georg Holzhütter
BMC Systems Biology|April 6, 2007
Synthetic tetracycline-inducible regulatory networks: computer-aided design of dynamic phenotypesVassilios Sotiropoulos, Yiannis N Kaznessis
BMC Systems Biology|October 24, 2008
Using a 3D virtual muscle model to link gene expression changes during myogenesis to protein spatial location in muscleAshley J Waardenberg, Antonio Reverter, Christine A Wells, et al.
BMC Systems Biology|September 1, 2007
Modeling gene expression regulatory networks with the sparse vector autoregressive modelAndré Fujita, João R Sato, Humberto M Garay-Malpartida, et al.
BMC Systems Biology|February 25, 2015
Accurate multiple network alignment through context-sensitive random walkHyundoo Jeong, Byung-Jun Yoon
BMC Systems Biology|March 25, 2010
Linking toxicant physiological mode of action with induced gene expression changes in Caenorhabditis elegansSuresh Swain, Jodie F Wren, Stephen R Stürzenbaum, et al.
BMC Systems Biology|April 17, 2015
BioPreDyn-bench: a suite of benchmark problems for dynamic modelling in systems biologyAlejandro F Villaverde, David Henriques, Kieran Smallbone, et al.
BMC Systems Biology|April 17, 2015
Bicluster Sampled Coherence Metric (BSCM) provides an accurate environmental context for phenotype predictionsSamuel A Danziger, David J Reiss, Alexander V Ratushny, et al.
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