Objective Whole-cell (WC) modeling is a promising tool for biological research, bioengineering, and medicine. However, substantial work remains to create accurate, comprehensive models of complex cells. Methods We organized the 2015 Whole-Cell Modeling Summer School to teach WC modeling and evaluate the need for new WC modeling standards and software by recoding a recently published WC model in SBML. Results Our analysis revealed several challenges to representing WC models using the current standards. Conclusion We, therefore, propose several new WC modeling standards, software, and databases. Significance We anticipate that these new standards and software will enable more comprehensive models.

Toll-like receptors (TLRs) recognize pathogen-associated molecular patterns (PAMPs) and stimulate the innate immune response through the production of cytokines. The innate immune response depends on the timing of encountering PAMPs, suggesting a short-term “memory.” In particular, activation of TLR3 appears to prime macrophages for the subsequent activation of TLR7, which leads to synergistically increased production of cytokines. By developing a calibrated mathematical model for the kinetics of TLR3 and TLR7 pathway crosstalk and providing experimental validation, we demonstrated the involvement of the Janus-activated kinase (JAK)–signal transducer and activator of transcription (STAT) pathway in controlling the synergistic production of cytokines. Signaling through this pathway played a dual role: It mediated the synergistic production of cytokines, thus boosting the immune response, and it also maintained homeostasis to avoid an excessive inflammatory response. Thus, we propose that the JAK-STAT pathway provides a cytokine rheostat mechanism, which enables macrophages to fine-tune their responses to multiple, temporally separated infection events involving the TLR3 and TLR7 pathways.

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The source code is freely available at http://www.comp.nus.edu.sg/~rpsysbio/pada-gpu/

Supplementary data are available at Bioinformatics online.

This paper evaluates the difference between human pathway curation and current NLP systems. We propose graph analysis methods for quantifying the gap between human curated pathway maps and the output of state-of-the-art automatic NLP systems. Evaluation is performed on the popular mTOR pathway. Based on analyzing where current systems perform well and where they fail, we identify possible avenues for progress.

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This paper describes an an open-source software system for the automatic conversion of NLP event representations to system biology structured data interchange formats such as SBML and BioPAX. It is part of a larger effort to make results of the NLP community available for system biology pathway modelers.