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  • Review Article
  • Published:

Software for systems biology: from tools to integrated platforms

Nature Reviews Genetics volume 12, pages 821–832 (2011)Cite this article

Subjects

Key Points

  • Software is crucial for biological research, has an impact on research productivity and enables researchers to explore massive databases and knowledge-bases.

  • The workflow in systems biology generally consists of iterative cycles of: experiments; data acquisition and analysis; modelling; and computational analysis. Each of these processes is supported by software tools.

  • Standardization and interoperability are crucial for the efficient use of software tools and data resources.

  • A software platform enables various software tools, data resources and knowledge sources to be accessible in a consistent manner. This dramatically improves the productivity of research and reduces potential errors in the workflow.

  • In the future, software platforms and data or knowledge resources need to be supported through community-wide efforts. However, this requires a broader understanding of social dynamics, psychology and the economics of research activities; additionally, platforms need to be supported by user-friendly software tools.

Abstract

Understanding complex biological systems requires extensive support from software tools. Such tools are needed at each step of a systems biology computational workflow, which typically consists of data handling, network inference, deep curation, dynamical simulation and model analysis. In addition, there are now efforts to develop integrated software platforms, so that tools that are used at different stages of the workflow and by different researchers can easily be used together. This Review describes the types of software tools that are required at different stages of systems biology research and the current options that are available for systems biology researchers. We also discuss the challenges and prospects for modelling the effects of genetic changes on physiology and the concept of an integrated platform.

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Figure 1: Workflow of computational tasks in systems biology.
Figure 2: An example application of the High-Definition Physiology Project.

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Acknowledgements

This work is, in part, supported by funding from the HD-Physiology Project of the Japan Society for the Promotion of Science (JSPS) to the Okinawa Institute of Science and Technology (OIST). Additional support is from a Canon Foundation Grant, the International Strategic Collaborative Research Program (BBSRC-JST) of the Japan Science and Technology Agency (JST), the Exploratory Research for Advanced Technology (ERATO) programme of JST to the Systems Biology Institute (SBI) and from a strategic cooperation partnership between the Luxembourg Centre for Systems Biomedicine and SBI.

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Authors and Affiliations

  1. The Systems Biology Institute, 5F Falcon Building, 5-6-9 Shirokanedai, Minato, Tokyo, 108-0071, Japan

    Samik Ghosh, Yukiko Matsuoka & Hiroaki Kitano

  2. JST ERATO Kawaoka Infection-induced Host Response Project, 4-6-1 Shirokanedai, Minato, Tokyo, 108-8639, Japan

    Yukiko Matsuoka

  3. Okinawa Institute of Science and Technology, 1919-1, Tancha, Onna-son, Kunigami, Okinawa, 904-0412, Japan

    Yoshiyuki Asai, Kun-Yi Hsin & Hiroaki Kitano

  4. Sony Computer Science Laboratories, Inc., 3-14-13 Higashi-Gotanda, Shinagawa, Tokyo, 141-0022, Japan

    Hiroaki Kitano

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  1. Samik Ghosh
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Supplementary information

Supplementary information S1 (table)

A comprehensive table of software tools and resources, including further information and Weblinks (XLS 52 kb)

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FURTHER INFORMATION

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BioCatalogue

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Glossary

Mutual information

A dimensionless quantity that measures the extent to which one random variable is informative about another variable. Zero mutual information between two random variables means that they are independent.

Meta-database

A database for storing metadata, which was originally defined as 'data about data', such as tags and keywords. The database is used for integrating independent distributed databases.

Ordinary differential equations

(ODEs). A type of differential equation involving functions of one independent variable, such as time, and derivatives of the functions with respect to the variable.

Partial differential equations

A type of differential equation involving functions of several independent variables, such as time and spatial axes (that is, x, y and z), and partial derivatives of the functions with respect to those variables.

Agent-based modelling

A class of computational models that simulate the interaction of agents to study their effects on a system. Agents are autonomous, decision-making entities that have heterogeneous characteristics; examples of agents are molecules or cells.

Process algebra

A mathematical modelling language for describing the behaviour of distributed systems.

Rule-based modelling

When used in biochemical science, this term refers to a way to model molecules and proteins as objects that interact with each other. The interactions are described as rules that define how the objects transform their attributes and the relationships between the objects.

Phase-space analysis

A way to analyse the dynamics of a system in a space (the phase-space), in which each of the possible states of the system is represented as a unique point.

Bifurcation analysis

A way to analyse the qualitative changes in the dynamics of a system that are caused by varying one or several parameter values continuously.

Homeodynamics

A concept that views an organism as a dynamical system; this concept emerged after the concept of homeostasis. Biological systems can be considered as homeodynamic: they can lose stability and show diverse behaviours, such as bi-stability, periodicity and chaotic dynamics.

Constraint-based reconstruction and analysis

(COBRA). A suite of methods to simulate, analyse and predict various phenotypes using genome-scale models. These methods are used particularly for metabolic networks.

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Ghosh, S., Matsuoka, Y., Asai, Y. et al. Software for systems biology: from tools to integrated platforms. Nat Rev Genet 12, 821–832 (2011). https://doi.org/10.1038/nrg3096

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