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@@ -64,6 +64,139 @@ <h1>Publications</h1>
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<h2>OpenWorm: overview and recent advances in integrative biological simulation of Caenorhabditis elegans</h2>
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10 September 2018, Phil. Trans. R. Soc. B, DOI: 10.1098/rstb.2017.0382
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Gopal P. Sarma, Chee Wai Lee, Tom Portegys, Vahid Ghayoomie, Travis Jacobs, Bradly Alicea, Matteo Cantarelli, Michael Currie, Richard C. Gerkin, Shane Gingell, Padraig Gleeson, Richard Gordon, Ramin M. Hasani, Giovanni Idili, Sergey Khayrulin, David Lung, Andrey Palyanov, Mark Watts and Stephen D. Larson </p>
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The adoption of powerful software tools and computational methods from the software industry by the scientific research
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community has resulted in a renewed interest in integrative, large-scale biological simulations. These typically involve
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the development of computational platforms to combine diverse, process-specific models into a coherent whole. The OpenWorm
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Foundation is an independent research organization working towards an integrative simulation of the nematode Caenorhabditis
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elegans, with the aim of providing a powerful new tool to understand how the organism's behaviour arises from its fundamental
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biology. In this perspective, we give an overview of the history and philosophy of OpenWorm, descriptions of the constituent
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sub-projects and corresponding open-science management practices, and discuss current achievements of the project and future
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directions.
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<a href="https://royalsocietypublishing.org/doi/10.1098/rstb.2017.0382" target="_blank">Read more</a>.
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<h2>Towards systematic, data-driven validation of a collaborative, multi-scale model of Caenorhabditis elegans</h2>
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10 September 2018, Phil. Trans. R. Soc. B, DOI: 10.1098/rstb.2017.0381
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Richard C. Gerkin, Russell J. Jarvis and Sharon M. Crook
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The OpenWorm Project is an international open-source collaboration to create a multi-scale model of the organism
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Caenorhabditis elegans. At each scale, including subcellular, cellular, network and behaviour, this project employs
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one or more computational models that aim to recapitulate the corresponding biological system at that scale.
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This requires that the simulated behaviour of each model be compared with experimental data both as the model is
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continuously refined and as new experimental data become available. Here we report the use of SciUnit, a software framework
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for model validation, to attempt to achieve these goals. During project development, each model is continuously subjected to
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data-driven ‘unit tests’ that quantitatively summarize model-data agreement, identifying modelling progress and highlighting
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particular aspects of each model that fail to adequately reproduce known features of the biological organism and its components.
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This workflow is publicly visible via both GitHub and a web application and accepts community contributions to ensure that modelling
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goals are transparent and well-informed.
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<a href="https://royalsocietypublishing.org/doi/10.1098/rstb.2017.0381" target="_blank">Read more</a>.
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<h2>Geppetto: a reusable modular open platform for exploring neuroscience data and models</h2>
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10 September 2018, Phil. Trans. R. Soc. B, DOI: 10.1098/rstb.2017.0380
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Matteo Cantarelli, Boris Marin, Adrian Quintana, Matt Earnshaw, Robert Court, Padraig Gleeson, Salvador Dura-Bernal, R. Angus Silver and Giovanni Idili
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Geppetto is an open-source platform that provides generic middleware infrastructure for building both online and desktop tools
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for visualizing neuroscience models and data and managing simulations. Geppetto underpins a number of neuroscience applications,
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including Open Source Brain (OSB), Virtual Fly Brain (VFB), NEURON-UI and NetPyNE-UI. OSB is used by researchers to create and visualize
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computational neuroscience models described in NeuroML and simulate them through the browser. VFB is the reference hub for Drosophila
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melanogaster neural anatomy and imaging data including neuropil, segmented neurons, microscopy stacks and gene expression pattern data.
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Geppetto is also being used to build a new user interface for NEURON, a widely used neuronal simulation environment, and for NetPyNE, a
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Python package for network modelling using NEURON. Geppetto defines domain agnostic abstractions used by all these applications to represent
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their models and data and offers a set of modules and components to integrate, visualize and control simulations in a highly accessible way.
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The platform comprises a backend which can connect to external data sources, model repositories and simulators together with a highly
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customizable frontend.
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<a href="https://royalsocietypublishing.org/doi/10.1098/rstb.2017.0380" target="_blank">Read more</a>.
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<h2>c302: a multiscale framework for modelling the nervous system of Caenorhabditis elegans</h2>
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10 September 2018, Phil. Trans. R. Soc. B, DOI: 10.1098/rstb.2017.0379
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</p>
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Padraig Gleeson, David Lung, Radu Grosu, Ramin Hasani and Stephen D. Larson
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The OpenWorm project has the ambitious goal of producing a highly detailed in silico model of the nematode Caenorhabditis elegans.
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A crucial part of this work will be a model of the nervous system encompassing all known cell types and connections. The appropriate
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level of biophysical detail required in the neuronal model to reproduce observed high-level behaviours in the worm has yet to be determined.
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For this reason, we have developed a framework, c302, that allows different instances of neuronal networks to be generated incorporating
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varying levels of anatomical and physiological detail, which can be investigated and refined independently or linked to other tools
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developed in the OpenWorm modelling toolchain.
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<a href="https://royalsocietypublishing.org/doi/10.1098/rstb.2017.0379" target="_blank">Read more</a>.
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<h2>Three-dimensional simulation of the Caenorhabditis elegans body and muscle cells in liquid and gel environments for behavioural analysis</h2>
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10 September 2018, Phil. Trans. R. Soc. B, DOI: 10.1098/rstb.2017.0376
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Andrey Palyanov, Sergey Khayrulin and Stephen D. Larson
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To better understand how a nervous system controls the movements of an organism, we have created a three-dimensional computational
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biomechanical model of the Caenorhabditis elegans body based on real anatomical structure. The body model is created with a particle
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system–based simulation engine known as Sibernetic, which implements the smoothed particle–hydrodynamics algorithm. The model includes
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an elastic body-wall cuticle subject to hydrostatic pressure. This cuticle is then driven by body-wall muscle cells that contract and
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relax, whose positions and shape are mapped from C. elegans anatomy, and determined from light microscopy and electron micrograph data.
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We show that by using different muscle activation patterns, this model is capable of producing C. elegans-like behaviours,
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including crawling and swimming locomotion in environments with different viscosities, while fitting multiple additional known biomechanical
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properties of the animal.
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<a href="https://royalsocietypublishing.org/doi/10.1098/rstb.2017.0376" target="_blank">Read more</a>.
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<h2>Application of smoothed particle hydrodynamics to modeling mechanisms of biological tissue</h2>
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