Simulation Experiment Description Research Articles

Curating models from BioModels: Developing a workflow for creating OMEX files.

The reproducibility of computational biology models can be greatly facilitated by widely adopted standards and public repositories. We examined 50 models from the BioModels Database and attempted to validate the original curation and correct some of them if necessary. For each model, we reproduced these published results using Tellurium. Once reproduced we manually created a new set of files, with the model information stored by the Systems Biology Markup Language (SBML), and simulation instructions stored by the Simulation Experiment Description Markup Language (SED-ML), and everything included in an Open Modeling EXchange (OMEX) file, which could be used with a variety of simulators to reproduce the same results. On the one hand, the reproducibility procedure of 50 models developed a manual workflow that we would use to build an automatic platform to help users more easily curate and verify models in the future. On the other hand, these exercises allowed us to find the limitations and possible enhancement of the current curation and tooling to verify and curate models.

The systems biology simulation core library.

SummaryStudying biological systems generally relies on computational modeling and simulation, e.g., model-driven discovery and hypothesis testing. Progress in standardization efforts led to the development of interrelated file formats to exchange and reuse models in systems biology, such as SBML, the Simulation Experiment Description Markup Language (SED-ML) or the Open Modeling EXchange format. Conducting simulation experiments based on these formats requires efficient and reusable implementations to make them accessible to the broader scientific community and to ensure the reproducibility of the results. The Systems Biology Simulation Core Library (SBSCL) provides interpreters and solvers for these standards as a versatile open-source API in JavaTM. The library simulates even complex bio-models and supports deterministic Ordinary Differential Equations; Stochastic Differential Equations; constraint-based analyses; recent SBML and SED-ML versions; exchange of results, and visualization of in silico experiments; open modeling exchange formats (COMBINE archives); hierarchically structured models; and compatibility with standard testing systems, including the Systems Biology Test Suite and published models from the BioModels and BiGG databases.Availability and implementationSBSCL is freely available at https://draeger-lab.github.io/SBSCL/ and via Maven Central.Supplementary information Supplementary data are available at Bioinformatics online.

Simulation Experiment Description Markup Language (SED-ML) Level 1 Version 3 (L1V3).

The creation of computational simulation experiments to inform modern biological research poses challenges to reproduce, annotate, archive, and share such experiments. Efforts such as SBML or CellML standardize the formal representation of computational models in various areas of biology. The Simulation Experiment Description Markup Language (SED-ML) describes what procedures the models are subjected to, and the details of those procedures. These standards, together with further COMBINE standards, describe models sufficiently well for the reproduction of simulation studies among users and software tools. The Simulation Experiment Description Markup Language (SED-ML) is an XML-based format that encodes, for a given simulation experiment, (i) which models to use; (ii) which modifications to apply to models before simulation; (iii) which simulation procedures to run on each model; (iv) how to post-process the data; and (v) how these results should be plotted and reported. SED-ML Level 1 Version 1 (L1V1) implemented support for the encoding of basic time course simulations. SED-ML L1V2 added support for more complex types of simulations, specifically repeated tasks and chained simulation procedures. SED-ML L1V3 extends L1V2 by means to describe which datasets and subsets thereof to use within a simulation experiment.

SED-ML web tools: generate, modify and export standard-compliant simulation studies

The Simulation Experiment Description Markup Language (SED-ML) is a standardized format for exchanging simulation studies independently of software tools. We present the SED-ML Web Tools, an online application for creating, editing, simulating and validating SED-ML documents. The Web Tools implement all current SED-ML specifications and, thus, support complex modifications and co-simulation of models in SBML and CellML formats. Ultimately, the Web Tools lower the bar on working with SED-ML documents and help users create valid simulation descriptions. http://sysbioapps.dyndns.org/SED-ML_Web_Tools/ . fbergman@caltech.edu .

Effects of Material Rheology and Die Walls Translational Motions on the Dynamics of Viscous Flow during Equal Channel Angular Extrusion through a Segal 2θ-Die: CFD 2D Solution of a Curl Transfer Equation

The present article is focused on a phenomenological description of a polymer workpiece Equal Channel Angular Extrusion (ECAE) through 2θ-dies of Segal and Iwahashi geometries with a channel intersection angle 2θ = 105° with fixed and movable external inlet and outlet die walls. The local flow dynamics, including the formation of macroscopic rotation and a dead zone appearance during the flow of plasticine, paraffin, and wax workpiece models through the subject die configuration was studied using physical simulation techniques. The present article utilizes a Computational Fluid Dynamics (CFD) numerical approach to a theoretical description of 2D viscous flow of incompressible Newtonian continuum through the stated die geometries. The boundary value problem for the Navier-Stokes equations in the curl transfer form for the local viscous flow was formulated and numerically solved with a finite-difference method. Theoretical CFD-derived plots with computational flow lines, dimensionless flow and curl functions, flow velocities, and tangential stresses for viscous material flow through the stated die geometries have been generated and described. As a first rheological approximation the derived computational results provide the theoretical description of physical simulation experiments and visualize the formation of ECAE-induced rotational modes of large deformations like macroscopic rotation and rotational inhomogeneity.

PhraSED-ML: A paraphrased, human-readable adaptation of SED-ML.

Model simulation exchange has been standardized with the Simulation Experiment Description Markup Language (SED-ML), but specialized software is needed to generate simulations in this format. Text-based languages allow researchers to create and modify experimental protocols quickly and easily, and export them to a common machine-readable format. phraSED-ML language allows modelers to use simple text commands to encode various elements of SED-ML (models, tasks, simulations, and results) in a format easy to read and modify. The library can translate this script to SED-ML for use in other softwares. phraSED-ML language specification, libphrasedml library, and source code are available under BSD license from http://phrasedml.sourceforge.net/ .

Simulation Experiment Description Markup Language (SED-ML) Level 1 Version 2

Summary The number, size and complexity of computational models of biological systems are growing at an ever increasing pace. It is imperative to build on existing studies by reusing and adapting existing models and parts thereof. The description of the structure of models is not sufficient to enable the reproduction of simulation results. One also needs to describe the procedures the models are subjected to, as recommended by the Minimum Information About a Simulation Experiment (MIASE) guidelines.This document presents Level 1 Version 2 of the Simulation Experiment Description Markup Language (SED-ML), a computer-readable format for encoding simulation and analysis experiments to apply to computational models. SED-ML files are encoded in the Extensible Markup Language (XML) and can be used in conjunction with any XML-based model encoding format, such as CellML or SBML. A SED-ML file includes details of which models to use, how to modify them prior to executing a simulation, which simulation and analysis procedures to apply, which results to extract and how to present them. Level 1 Version 2 extends the format by allowing the encoding of repeated and chained procedures.

Declarative Representation of Uncertainty in Mathematical Models

An important aspect of multi-scale modelling is the ability to represent mathematical models in forms that can be exchanged between modellers and tools. While the development of languages like CellML and SBML have provided standardised declarative exchange formats for mathematical models, independent of the algorithm to be applied to the model, to date these standards have not provided a clear mechanism for describing parameter uncertainty. Parameter uncertainty is an inherent feature of many real systems. This uncertainty can result from a number of situations, such as: when measurements include inherent error; when parameters have unknown values and so are replaced by a probability distribution by the modeller; when a model is of an individual from a population, and parameters have unknown values for the individual, but the distribution for the population is known. We present and demonstrate an approach by which uncertainty can be described declaratively in CellML models, by utilising the extension mechanisms provided in CellML. Parameter uncertainty can be described declaratively in terms of either a univariate continuous probability density function or multiple realisations of one variable or several (typically non-independent) variables. We additionally present an extension to SED-ML (the Simulation Experiment Description Markup Language) to describe sampling sensitivity analysis simulation experiments. We demonstrate the usability of the approach by encoding a sample model in the uncertainty markup language, and by developing a software implementation of the uncertainty specification (including the SED-ML extension for sampling sensitivty analyses) in an existing CellML software library, the CellML API implementation. We used the software implementation to run sampling sensitivity analyses over the model to demonstrate that it is possible to run useful simulations on models with uncertainty encoded in this form.

SED-ED, a workflow editor for computational biology experiments written in SED-ML

The simulation experiment description markup language (SED-ML) is a new community data standard to encode computational biology experiments in a computer-readable XML format. Its widespread adoption will require the development of software support to work with SED-ML files. Here, we describe a software tool, SED-ED, to view, edit, validate and annotate SED-ML documents while shielding end-users from the underlying XML representation. SED-ED supports modellers who wish to create, understand and further develop a simulation description provided in SED-ML format. SED-ED is available as a standalone Java application, as an Eclipse plug-in and as an SBSI (www.sbsi.ed.ac.uk) plug-in, all under an MIT open-source license. Source code is at https://sed-ed-sedmleditor.googlecode.com/svn. The application itself is available from https://sourceforge.net/projects/jlibsedml/files/SED-ED/.

Experimental results for the allocation of buffers in closed serial production lines

In this paper, the description and results of simulation experiments investigating buffer allocation in closed serial production lines are presented. The production lines studied consist of either reliable or unreliable workstations, and have asynchronous movement of jobs. The experimental results are used to demonstrate a buffer allocation decomposition result for closed production lines, and also provide evidence that optimal buffer allocations in closed lines are less sensitive to bottleneck severity than in open production lines. Another key finding is that buffer allocation decisions have more impact in closed reliable production lines than in closed unreliable production lines.

Reproducible computational biology experiments with SED-ML--the Simulation Experiment Description Markup Language.

BackgroundThe increasing use of computational simulation experiments to inform modern biological research creates new challenges to annotate, archive, share and reproduce such experiments. The recently published Minimum Information About a Simulation Experiment (MIASE) proposes a minimal set of information that should be provided to allow the reproduction of simulation experiments among users and software tools.ResultsIn this article, we present the Simulation Experiment Description Markup Language (SED-ML). SED-ML encodes in a computer-readable exchange format the information required by MIASE to enable reproduction of simulation experiments. It has been developed as a community project and it is defined in a detailed technical specification and additionally provides an XML schema. The version of SED-ML described in this publication is Level 1 Version 1. It covers the description of the most frequent type of simulation experiments in the area, namely time course simulations. SED-ML documents specify which models to use in an experiment, modifications to apply on the models before using them, which simulation procedures to run on each model, what analysis results to output, and how the results should be presented. These descriptions are independent of the underlying model implementation. SED-ML is a software-independent format for encoding the description of simulation experiments; it is not specific to particular simulation tools. Here, we demonstrate that with the growing software support for SED-ML we can effectively exchange executable simulation descriptions.ConclusionsWith SED-ML, software can exchange simulation experiment descriptions, enabling the validation and reuse of simulation experiments in different tools. Authors of papers reporting simulation experiments can make their simulation protocols available for other scientists to reproduce the results. Because SED-ML is agnostic about exact modeling language(s) used, experiments covering models from different fields of research can be accurately described and combined.

Kinetic Simulation Algorithm Ontology

AbstractTo enable the accurate and repeatable execution of a computational simulation task, it is important to identify both the algorithm used and the initial setup. These minimum information requirements are described by the MIASE guidelines. Since the details of some algorithms are not always publicly available, and many are implemented only in a limited number of simulation tools, it is crucial to identify alternative algorithms with similar characteristics that may be used to provide comparable results in an equivalent simulation experiment. The Kinetic Simulation Algorithm Ontology (KiSAO) was developed to address this issue by describing existing algorithms and their inter-relationships through their characteristics and parameters. The use of KiSAO in conjunction with simulation descriptions, such as SED-ML, will allow simulation software to automatically choose the best algorithm available to perform a simulation. The availability of algorithm parameters, together with their type may permit the automatic generation of user-interfaces to configure simulators. To enable making queries to KiSAO programmaticaly, from simulation experiment description editors and simulation tools, a java library libKiSAO was implemented.

Java support for SED-ML

AbstractThis presentation describes Java support for the SED-ML simulation experiment description language. Firstly, a Java API library for low-level manipulations of the SED-ML object model, and secondly a SED-ML editor, SED-ED, for visualizing and editing SED-ML workflows

SED-ML Script Language

AbstractThe Simulation Experiment Description Markup Language (SED-ML) is a XML format describing simulation experiments, so that they can be easily exchanged independent of software tools that created them. This document describes the SED-ML Script, a Python based shorthand that makes it easy to create / edit SED-ML documents.

Simulation Experiment Description Markup Language (SED-ML) : Level 1 Version 1

The Simulation Experiment Description Markup Language (SED-ML) is an XML-based format for encoding simulation experiments, following the requirements defined in the MIASE guidelines. SED-ML allows one to define the model to use, the experimental task to run, and which result to produce.

Simulation Experiment Description Markup Language (SED-ML) : Level 1 Version 1

AbstractThe Simulation Experiment Description Markup Language (SED-ML) is an XML-based format for encoding simulation experiments, following the requirements defined in the MIASE guidelines. SED-ML allows one to define the model to use, the experimental task to run, and which result to produce.

The Simulation Experiment Description Markup Language - Update

AbstractThis presentation gives a brief overview of the Simulation Experiment Description Markup Language L1V1 as well as an introduction to LibSedML (http://libsedml.sf.net) a library for reading and writing SED-ML documents.

Uwagi o testach Jarque’a-Bera

The paper involves a description of simulation experiments aimed at determining the size of Jargue-Bera tests for skewness and kurtosis, as well as selected modifications of those tests. All experiments refer to four different families of probability distributions and consist of one thousand runs each.

Reconstructability analysis: Aims, results, open problems

AbstractThe term ‘reconstructability analysis’ has evolved as a generic term for all aspects of a methodology whose aim is to deal with problems associated with the relationship between systems perceived as wholes and their various subsystems (i.e. parts of the wholes). This article is a state‐of‐the‐art report on reconstructability analysis (RA). It contains a description of problems that are studied under RA, a summary of main results obtained within RA, an outline of some important issues associated with RA that require further research, and an up‐to‐date bibliography of RA.After a general discussion of the issues associated with the whole/part relationship and an overview of the aims of RA, the article describes results obtained for two problems that are subjects of study in RA. One of the problems, called an identification problem, is concerned with inferences about an unknown overall system from a given set of its subsystems. A deductive inference from the given subsystems results in the set of all overall systems which yield those very subsystems; it is called a reconstruction family. The ability to identify the true overall system is measured by an identifiability quotient that is inversely proportional to the relative size of the reconstruction family. A selection of one overall system from the reconstruction family requires an inductive inference. It is argued that the selected system should be unbiased and a simple procedure for determining it (called a join procedure) is described.The second problem, called a reconstruction problem, is concerned with the determination of such subsystems, as small as possible, from which the overall system can be reconstructed to an acceptable degree of approximation. The approximation is measured by an information distance between the given and reconstructed overall systems. The reconstruction problem involves a number of computational difficulties. Some approaches to overcoming these difficulties are discussed. The article also contains a description of simulation experiments which contributed toward the determination of some fundamental characteristics of RA for the reconstruction problem.

Stratospheric free chlorine measured by balloon‐borne in situ resonance fluorescence

Eight balloon‐borne in situ measurements of ClO in the stratosphere are presented. Six of the observations, which were carried out close to local noon, are compared with recent model calculations at the appropriate latitude (32°N), altitude (25–45 km), and solar zenith angle interval (10° < χ < 55°). The ClO mixing ratio by volume observed on four flights between the autumnal equinox and the winter solstice (September 20, October 25, December 2, and December 8, 1977)is found to exhibit little variability, defining an envelope which decreases from 0.5 to 1.1 ppb at 42 km to 10 to 50 ppt at 25 km. Two observations in July (July 28, 1976, and July 14, 1977) indicate significantly higher mixing ratios, the former increasing from 0.8 ppb at 42 km to 1.8 ppb at 36 km and then decreasing to 0.1 ppb at 24 km in reasonable agreement with calculations using 2.2 ppb total chlorine and 8 ppm H2O at the stratopause. The latter summer observation exhibits a serious divergence from calculated densities above 32 km, reaching 7 ppb in a layer between 35 and 40 km. Emphasis is given to a description of laboratory simulation experiments done in parallel with the stratospheric observations and to techniques used for determining the absolute sensitivity of the instrument. Results of the in situ observations are compared with recent results from the laser heterodyne and microwave limb scanning remote sensing methods. The simultaneous observations of [ClO] and [O3] on July 14, 1977, are used in conjunction with a formulation of odd oxygen chemistry in terms of rate limiting steps to deduce that either (a) the [ClO] or [O3] observation is wrong, (b) the observed chlorine was injected into the stratosphere in a period short in comparison with the chemical response time of ozone, or (c) there are important mechanistic steps missing from stratospheric chlorine‐ozone photochemistry.