BMC Systems Biology

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
Matteo Pellegrini, University of California, Los Angeles

Executive Editor

Tim Sands, BioMed Central

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Articles

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Model of ER dependent gene expression

A minimal mechanistic model of estrogen receptor alpha-dependent gene expression, predicts complex non-linear effects in transcriptional response to natural hormone 17 beta-estradiol and its external competitor tamoxifen under a range of biologically plausible parameter values.

BMC Systems Biology 2012, 6:138
From improved codon usage to increased expression

A novel method for codon usage optimization in artificial gene synthesis, optimizing use of both individual codon usage and codon context approaches, is predicted to lead to improved in vitro heterologous protein expression in biotechnology applications.

BMC Systems Biology 2012, 6:134
R package for signaling network training

CellNOptR is an R based software package for the training of signaling networks extracted from prior knowledge using experimental data, which extends the existing CellNetOptimizer MATLAB package with further logical formalisms.

BMC Systems Biology 2012, 6:133
Wiring genetic NAND/NOR gates

A novel genetic circuit is proposed and computationally tested that can be dynamically reconfigured to serve as either a NAND or NOR genetic logic gate in either single cells or cell populations.

BMC Systems Biology 2012, 6:126
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Comments

Problem with PDF anf HTML versions prior to October 20, 2012

Comment on: Kirouac et al. BMC Systems Biology 2012, 6:29
\"...but what is available for biological researchers?\"

Comment on: Rohn et al. BMC Systems Biology 2012, 6:33
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Comment on: Rohn et al. BMC Systems Biology 2012, 6:33

Hot topic

Simulations of stressosome activation emphasize allosteric interactions between RsbR and RsbT

Liebal UW, Millat T, Marles-Wright J, Lewis RJ and Wolkenhauer O

BMC Systems Biology 2013, 7:3

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Scope

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.

It is journal policy to publish work deemed by peer reviewers to be a coherent and sound addition to scientific knowledge and to put less emphasis on interest levels, provided that the research constitutes a useful contribution to the field.

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