Elsevier

Drug Discovery Today

Volume 19, Issue 2, February 2014, Pages 193-198
Drug Discovery Today

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Recent advances in modeling languages for pathway maps and computable biological networks

https://doi.org/10.1016/j.drudis.2013.12.011Get rights and content

Highlights

  • The importance of biological models to systems biology is discussed.

  • The principal role and desired characteristics of modeling languages in the development of biological models are discussed.

  • OpenBEL, PySB and BCML – three new and very different modeling languages are discussed in some detail.

As our theories of systems biology grow more sophisticated, the models we use to represent them become larger and more complex. Languages necessarily have the expressivity and flexibility required to represent these models in ways that support high-resolution annotation, and provide for simulation and analysis that are sophisticated enough to allow researchers to master their data in the proper context. These languages also need to facilitate model sharing and collaboration, which is currently best done by using uniform data structures (such as graphs) and language standards. In this brief review, we discuss three of the most recent systems biology modeling languages to appear: BEL, PySB and BCML, and examine how they meet these needs.

Section snippets

Languages, models and systems biology

Systems biology is a multidisciplinary approach to biological and biomedical research that focuses on the complex interactions characteristic of biological systems, often with the aim of discovering the emergent properties of such systems that have proven difficult to elucidate using more reductionist approaches (http://en.wikipedia.org/wiki/Systems_biology). The components of such systems are interdependent and in a state of constant change, and their behaviors depend on their context in situ

Standard languages for biological network analysis

One of the most important uses for standard languages in systems biology is modeling and analyzing biological networks. High-throughput molecular profiling techniques have proven to be effective tools for analyzing biological systems but, because they typically generate long and unadorned lists of analytes (genes, proteins, metabolites, among others), they represent a significant challenge to the researchers tasked with interpreting the results of these experiments [9]. To make analysis

Recent advances in network biology modeling languages

Modeling languages of various kinds have played key parts in biology and chemistry for decades. BioPAX, for example, is a popular language for representing and sharing pathway knowledge [17]. Systems Biology Markup Language (SBML) is an XML-based language for describing and quantifying biological models for use in software [18]. PSI-MI, the Proteomics Standards Initiative Molecular Interaction XML format, is used for data exchange in proteomics [19]. BioPAX, PSI-MI and SBML are compared in [20]

Concluding remarks

The models we use to represent theories of systems biology grow ever larger and more complex as the theories themselves are enriched by continuing research. Recently, more of languages used to express these models have been designed to help model builders take better advantage of information technology, by providing better facilities for data annotation and semantics, analytics, inference, and programmatic simulation. They have also been designed to leverage uniform data structures (such as

Conflicts of interest

T.S. was formerly Chief Technology Officer of the OpenBEL Project, an independent non-profit organization focused on the OpenBEL knowledge engineering platform for the life sciences (http://openbel.org).

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