The authors have declared that no competing interests exist.
Reproducibility of experiments is a basic requirement for science. Minimum Information
(MI) guidelines have proved a helpful means of enabling reuse of existing work in modern
biology. The Minimum Information Required in the Annotation of Models (MIRIAM)
guidelines promote the exchange and reuse of biochemical computational models. However,
information about a model alone is not sufficient to enable its efficient reuse in a
computational setting. Advanced numerical algorithms and complex modeling workflows used
in modern computational biology make reproduction of simulations difficult. It is
therefore essential to define the core information necessary to perform simulations of
those models. The Minimum Information About a Simulation Experiment (MIASE, Glossary in
A simulation description that provides all information listed by the MIASE guidelines.
A mathematical representation of a biological system that can be manipulated and experimented upon (simulated).
Set of formal statements describing the structure of the components of a modeled system, whether entities or events, encoded in a computer-readable form.
The closeness between independent simulations performed with the same methods on identical models with the same experimental setup.
The closeness between independent simulations performed with the same methods on identical models but with a different experimental setup.
A numerical procedure performed on a model that aims to reproduce the spatial and temporal evolution (the behavior) of the system represented by the model, under prescribed conditions.
A set of procedures, including simulations, to be performed on a model or a group of models, in order to obtain a certain set of given numerical results.
The rise of systems biology as a new paradigm of biological research has put
computational modeling under the spotlight. In cell biology
Although generic, this framework for modeling and simulation applies well to the field
of computational modeling and simulation of biological processes, where models are
created and simulated as testable hypotheses in order to determine whether or not they
are compatible with experimental data or expected future observations; their
analysis supports the design of additional experiments and helps in the synthesis of
engineered biological systems. The acceptance of the computationally aided systems
biology approach has led to the creation of models at an ever increasing rate, as shown
by the rapid growth of model databases. Because of the size of the systems considered,
and their multi-scale aspects (both temporal and spatial), modeling activity in
integrative systems biology requires researchers to leverage new approaches from prior
work. Initiatives to establish standards for describing models and simulations have
already been advocated in 1969, e.g., to “establish a standard form of what a
model should be like, how it should be described and documented […]. This
is intended in part to facilitate communication of information about models, which may
be difficult owing to their complexity”
Such an endeavor requires the model descriptions (specifying the mathematical
expressions and parameters for a given model) to be stored and exchanged in a way that
allows for their efficient reuse
Standardization plays a central role in facilitating the exchange and interpretation of
the outcomes of scientific research, and in particular of computational modeling
The model, when instantiated within a suitable simulation environment, must be able to reproduce all relevant results given in the reference description that can readily be simulated.
While mentioning the need for result reproducibility, MIRIAM does not set out to cover the information needed to simulate the models.
As a consequence, it is still necessary to define the core information that needs to be made available to the users of existing models, so that they can perform defined simulations on those models. Once encoded in a computer readable format, these simulation experiment recipes can be downloaded along with the models, either from public resources or publisher Web sites. This will not only allow one to store descriptions of simulation experiments and reproduce them, but also foster their exchange between co-workers, research groups, and even between simulation tools. In this paper, we describe the minimum information that must be provided to make the description of a simulation experiment available to others. Experiment descriptions that provide all necessary information specified in the guidelines are considered MIASE compliant.
MIASE sets out to define minimum requirements for simulation descriptions. It covers the simulation procedures, and allows for the experiments to be reproduced. The particular focus of MIASE is on life science applications.
One of the difficulties in applying common guidelines to multiple simulation methods
is that the definitions of model and simulation vary, and there is an ill-defined
line between the two concepts. This conceptual entanglement is sometimes at the core
of mathematical and computational approaches, as with executable biology
Reporting guidelines describe how to report clearly and unambiguously what has been
done, by describing the entities involved in the experiment. They are not, on the
contrary, meant to describe which experimental approaches are correct, or how an
experiment should be performed
The scope of MIASE is limited to the
The MIASE guidelines apply to simulation descriptions of biological systems that could be (but are not necessarily) written with ordinary and partial differential equations. For the time being, and as a consequence of the fact that the effort was launched in the systems biology community, the MIASE guidelines are applicable to the simulation of mathematical models of biochemical and physiological systems. However, MIASE principles are general and should appeal to other communities. It can be expected that MIASE compliance will be directly applicable to a wider range of simulation experiments, such as the ones performed in computational neuroscience or ecological modeling. MIASE could even be extended to cover other areas of mathematical modeling in the life sciences, e.g., process algebra.
MIASE is composed of rules, summarized in
All models used in the experiment must be identified, accessible, and fully described.
The description of the simulation experiment must be provided together with the models necessary for the experiment, or with a precise and unambiguous way of accessing those models.
The models required for the simulations must be provided with all governing equations, parameter values, and necessary conditions (initial state and/or boundary conditions).
If a model is not encoded in a standard format, then the model code must be made available to the user. If a model is not encoded in an open format or code, its full description must be provided, sufficient to re-implement it.
Any modification of a model (pre-processing) required before the execution of a step of the simulation experiment must be described.
A precise description of the simulation steps and other procedures used by the experiment must be provided.
All simulation steps must be clearly described, including the simulation algorithms to be used, the models on which to apply each simulation, the order of the simulation steps, and the data processing to be done between the simulation steps.
All information needed for the correct implementation of the necessary simulation steps must be included through precise descriptions or references to unambiguous information sources.
If a simulation step is performed using a computer program for which source code is not available, all information needed to reproduce the simulation, and not just repeat it, must be provided, including the algorithms used by the original software and any information necessary to implement them, such as the discretization and integration methods.
If it is known that a simulation step will produce different results when performed in a different simulation environment or on a different computational platform, an explanation must be given of how the model has to be run with the specified environment/platform in order to achieve the purpose of the experiment.
All information necessary to obtain the desired numerical results must be provided.
All post-processing steps applied on the raw numerical results of simulation steps in order to generate the final results have to be described in detail. That includes the identification of data to process, the order in which changes were applied, and also the nature of changes.
If the expected insights depend on the relation between different results, such as a plot of one against another, the results to be compared have to be specified.
Biomedical sciences are witnessing the birth of a new era, comparable to physical engineering two centuries ago. The practice of systems biology, and its applied siblings synthetic biology and cell reprogramming, will require the use of modeling and simulations as a routine procedure. Investigations into the behavior of complex biological systems are increasingly predicated on comparing simulations to observations. The simulations must be reproduced and/or modified in controlled ways. Precise descriptions of the procedures involved is the first and mandatory step in any standardization effort.
Scientists involved in the simulation of biological processes at different scales and
with different approaches, together with maintainers of standards in systems biology,
developed MIASE through several physical meetings and online discussions (see
The systematic application of MIASE rules will allow the reproduction of simulations, and therefore the verification of simulation results. Such transparency is necessary to evaluate the quality of scientific activity. It will also improve the sharing of simulation procedures and promotion of the collaborative development and use of models.
Detailed description of the MIASE Guidelines, with a discussion of all the rules, and a workflow depicting the description of the different steps of a simulation experiment.
(0.19 MB PDF)
Three examples of MIASE-compliant descriptions of different simulation experiments ran on the same model.
(0.48 MB PDF)
Authors are grateful to James Bassingthwaighte, Igor Goryanin, Fedor Kolpakov, and Benjamin Zaitlen for discussions and comments on the manuscript.
The publication of this Perspective is not an endorsement by PLoS of MIASE, but rather encouragement to have an active dialog around the development of a standard.