Section Editors

  • Nitin Baliga, Institute for Systems Biology
  • Christina Chan, Michigan State University
  • Luonan Chen, Chinese Academy of Sciences
  • Sang Yup Lee, Korea Advanced Institute of Science and Technology
  • Pedro Mendes, Univ. of Manchester/Univ. Connecticut Health Center
  • Matteo Pellegrini, University of California, Los Angeles

Executive Editor

  • Tim Sands, BioMed Central


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  • Image attributed to: User KGH on Wikipedia, CC BY-SA 3.0

    Inferring urothelial cancer GRNs

    Genome-wide regulatory networks underling urothelial cancer, inferred by the BC3Net algorithm based on RNAseq, Bead and Oligo gene expression data, identified known associated genomic regions, and found similarity between functional subnetworks but gene interactions were highly dataset specific.

    BMC Systems Biology 2015, 9:21
  • Flux predictions at sub-optimal growth

    A new flux balance analysis method predicts internal cell fluxes of growth below optimal rates based on the optimization of protein cost at sub-optimal biomass objective levels, and simulations predict features of E.coli central carbon metabolism.

    BMC Systems Biology 2015, 9:18
  • Image attributed to: Tomomarusan on Wikipedia, CC-BY 2.5

    Optimizing ammonite forms

    Across ammonite genera, trade-offs between different shape phenotypes resulted in a small range of successful forms, that could be represented by a pyramid in the diagram of possible shape parameters, with each point representing an optimized archetype.

    BMC Systems Biology 2015, 9:12


BMC Systems Biology is an open access, peer-reviewed journal that considers articles on experimental and theoretical aspects of the function of biological systems at the molecular, cellular or organismal level, in particular those addressing the engineering of biological systems, network modeling, quantitative analyses and the integration of different levels of information.

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ISSN: 1752-0509