Here, Matthew Turk considers the tradeoffs and drawbacks between providing a full stack, versus components, when vertically integrating developments into scientific software.

Vertical Integration

Exploring the value management critical success factors for sustainable residential building – A structural equation modelling approach

This article introduces SESSL (Simulation Experiment Specification via a Scala Layer), an embedded domain-specific language for simulation experiments. It serves as an additional software layer between users and simulation systems and is implemented in Scala. SESSL supports multiple simulation systems and offers various features (e.g., for experiment design, performance analysis, result reporting, and simulation-based optimization). It supports “cutting-edge” experiments by allowing to add custom code, enables a reuse of functionality across simulation systems, and improves the reproducibility of simulation experiments.

SESSL: A domain-specific language for simulation experiments

Canonical WNT/β-catenin signaling is a central pathway in embryonic development, but it is also connected to a number of cancers and developmental disorders. Here we apply a combined in-vitro and in-silico approach to investigate the spatio-temporal regulation of WNT/β-catenin signaling during the early neural differentiation process of human neural progenitors cells (hNPCs), which form a new prospect for replacement therapies in the context of neurodegenerative diseases. Experimental measurements indicate a second signal mechanism, in addition to canonical WNT signaling, being involved in the regulation of nuclear β-catenin levels during the cell fate commitment phase of neural differentiation. We find that the biphasic activation of β-catenin signaling observed experimentally can only be explained through a model that combines Reactive Oxygen Species (ROS) and raft dependent WNT/β-catenin signaling. Accordingly after initiation of differentiation endogenous ROS activates DVL in a redox-dependent manner leading to a transient activation of down-stream β-catenin signaling, followed by continuous auto/paracrine WNT signaling, which crucially depends on lipid rafts. Our simulation studies further illustrate the elaborate spatio-temporal regulation of DVL, which, depending on its concentration and localization, may either act as direct inducer of the transient ROS/β-catenin signal or as amplifier during continuous auto-/parcrine WNT/β-catenin signaling. In addition we provide the first stochastic computational model of WNT/β-catenin signaling that combines membrane-related and intracellular processes, including lipid rafts/receptor dynamics as well as WNT- and ROS-dependent β-catenin activation. The model’s predictive ability is demonstrated under a wide range of varying conditions for in-vitro and in-silico reference data sets. Our in-silico approach is realized in a multi-level rule-based language, that facilitates the extension and modification of the model. Thus, our results provide both new insights and means to further our understanding of canonical WNT/β-catenin signaling and the role of ROS as intracellular signaling mediator.

/pdf/spatio-temporal-model-of-endogenous-ros-and-raft-dependent-4vkmemeuxx.pdf

Spatio-temporal model of endogenous ROS and raft-dependent WNT/beta-catenin signaling driving cell fate commitment in human neural progenitor cells.

Dry-lab experimentation is being increasingly used to complement wet-lab experimentation. However, conducting dry-lab experiments is a challenging endeavor that requires the combination of diverse techniques. JAMES II, a plug-in-based open source modeling and simulation framework, facilitates the exploitation and configuration of these techniques. The different aspects that form an experiment are made explicit to facilitate repeatability and reuse. Each of those influences the performance and the quality of the simulation experiment. Common experimentation pitfalls and current challenges are discussed along the way.

Flexible experimentation in the modeling and simulation framework JAMES II—implications for computational systems biology

Model validation is essential in modeling and simulation. It “finalizes” the modeling process, and provides the base for reliable experiments with the model, and thus to gain trustworthy insights of the system under study. Diverse techniques have been developed addressing different needs and are used during different phases in the modeling and simulation life cycle. Experimental model validation depends on the execution of the model. Thus, the peculiarities of the simulation engine might influence the results of experiments and thus have to be taken into account. Execution also underlies some techniques of software validation which can be adopted for experimental model validation. New approaches apply model checking techniques for trace inspections, and emphasize the importance of an explicit description of requirements. All of this implies new requirements for systems intended to support experimental model validation.

A Discussion on Experimental Model Validation

Human neural progenitor cells (hNPCs) form a new prospect for replacement therapies in the context of neurodegenerative diseases. The Wnt/-catenin signaling pathway is known to be involved in the differentiation process of hNPCs. RVM cells form a common cell model of hNPCs for in vitro investigation. Previous observations in RVM cells raise the question of whether observed kinetics of the Wnt/-catenin pathway in later differentiation phases are subject to self-induced signaling. However, a concern when investigating RVM cells is that experimental results are possibly biased by the asynchrony of cells w.r.t. the cell cycle. 

In this paper, we present, based on experimental data, a computational modeling study on the Wnt/-catenin signaling pathway in RVM cell populations asynchronously distributed w.r.t. to their cell cycle phases. Therefore, we derive a stochastic model of the pathway in single cells from the reference model in literature and extend it by means of cell populations and cell cycle asynchrony. Based on this, we show that the impact of the cell cycle asynchrony on wet-lab results that average over cell populations is negligible. We then further extend our model and the thus-obtained simulation results provide additional evidence that self-induced Wnt signaling occurs in RVM cells. We further report on significant stochastic effects that directly result from model parameters provided in literature and contradict experimental observations.

/pdf/elucidating-the-sources-of-b-catenin-dynamics-in-human-3gorf8tirb.pdf

Elucidating the sources of β-catenin dynamics in human neural progenitor cells.

Stochastic simulations may require many replications until their results are statistically significant. Each replication corresponds to a standalone simulation job, so that these can be computed in parallel. This paper presents a grid-inspired approach to distribute such independent jobs over a set of computing resources that host simulation services, all of which are managed by a central master service. Our method is fully integrated with alternative ways of distributed simulation in JAMES II, hides all execution details from the user, and supports the coarse-grained parallel execution of any sequential simulator available in JAMES II. A thorough performance analysis of the new execution mode illustrates its efficiency.

A Grid-Inspired Mechanism for Coarse-Grained Experiment Execution

Distributed simulation can speed up the execution of models significantly. We introduce a new simulation algorithm and present partitioning and load balancing techniques that are tailored to the efficient distributed execution of PDEVS. We base our elaborations on the idea of minimizing interprocessor communication, since this is a major bottleneck in distributed PDEVS simulation. Additionally, experimental results are provided which compare the performance of this new approach to alternative algorithms.

Parallel and distributed simulation of parallel DEVS models

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