The Simularium Viewer: an interactive online tool for sharing spatiotemporal biological models

Lyons, Blair; Isaac, Eric; Choi, Na Hyung; Thao, Pa Chia; Domingus, Justin; Iwasa, Janet; Leonard, Andrew N.; Riel-Mehan, Megan; Rodgers, Emily; Schaefbauer, Lisa M.; Toloudis, Daniel; Waltner, Olivia; Wilhelm, Lyndsay; Johnson, Graham

doi:10.1038/s41592-022-01442-1

Cited by 8 publications

(5 citation statements)

References 10 publications

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“…But perhaps the greatest insight that we gained from the workshop was that successful visualization of condensates is not a trivial task, and provides an exciting challenge for future work. A key step will be the development of new visualization tools that enable researchers to readily visualize and share dynamic, complex, and multidimensional data ( Lyons et al. , 2022 ).…”

Section: Discussionmentioning

confidence: 99%

Depicting a cellular space occupied by condensates

Liu,

Riggi,

Lee

et al. 2023

MBoC

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Section: Discussionmentioning

confidence: 99%

Depicting a cellular space occupied by condensates

Liu,

Riggi,

Lee

et al. 2023

MBoC

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“…To help bridge the gap to other tools, we provide functionality that transforms output data into other formats. In collaboration with a team at the Allen Institute for Cell Science, the Studio can generate data (File → Export → Simularium) for their Simularium [13] viewer (simularium.allencell.org/viewer) shown in Figure 16. The trade-offs of providing functionality in the Studio versus using other tools, especially for visualization, is something we have struggled with from the beginning and we strive to maintain a balance.…”

Section: Interfacing To Other Toolsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

PhysiCell Studio: a graphical tool to make agent-based modeling more accessible

Heiland,

Bergman,

Lyons

et al. 2023

Preprint

Self Cite

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Defining a multicellular model can be challenging. There may be hundreds of parameters that specify the attributes and behaviors of objects. Hopefully the model will be defined using some format specification, e.g., a markup language, that will provide easy model sharing (and a minimal step toward reproducibility). PhysiCell is an open source, physics-based multicellular simulation framework with an active and growing user community. It uses XML to define a model and, traditionally, users needed to manually edit the XML to modify the model. PhysiCell Studio is a tool to make this task easier. It provides a graphical user interface that allows editing the XML model definition, including the creation and deletion of fundamental objects, e.g., cell types and substrates in the microenvironment. It also lets users build their model by defining initial conditions and biological rules, run simulations, and view results interactively. PhysiCell Studio has evolved over multiple workshops and academic courses in recent years which has led to many improvements. Its design and development has benefited from an active undergraduate and graduate research program. Like PhysiCell, the Studio is open source software and contributions from the community are encouraged.

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“…Given time and effort, a motivated researcher will manage to find the right combination of package versions and Python version that will be compatible, but this level of difficulty is both a significant barrier to use and common in open-source scientific software generally (8). An increasingly common way to address the challenges of running open-source scientific software is by implementing the methods of the software in a web application (9,10). Here we present a new web application named MANGEM (Multimodal Analysis of Neuronal Gene Expression, Electrophysiology and Morphology), developed to address the challenges researchers may experience in using existing methods of aligning and analyzing multi-modal single-cell data.…”

Section: Introductionmentioning

confidence: 99%

MANGEM: a web app for Multimodal Analysis of Neuronal Gene expression, Electrophysiology and Morphology

Olson

Kalafut

Wang

2023

Preprint

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Single-cell techniques have enabled the acquisition of multi-modal data, particularly for neurons, to characterize cellular functions. Patch-seq, for example, combines patch-clamp recording, cell imaging, and single-cell RNA-seq to obtain electrophysiology, morphology, and gene expression data from a single neuron. While these multi-modal data offer potential insights into neuronal functions, they can be heterogeneous and noisy. To address this, machine-learning methods have been used to align cells from different modalities onto a low-dimensional latent space, revealing multi-modal cell clusters. However, the use of those methods can be challenging for biologists and neuroscientists without computational expertise and also requires suitable computing infrastructure for computationally expensive methods. To address these issues, we developed a cloud-based web application, MANGEM (Multimodal Analysis of Neuronal Gene expression, Electrophysiology, and Morphology) at https://ctc.waisman.wisc.edu/mangem. MANGEM provides a step-by-step accessible and user-friendly interface to machine-learning alignment methods of neuronal multi-modal data while enabling real-time visualization of characteristics of raw and aligned cells. It can be run asynchronously for large-scale data alignment, provides users with various downstream analyses of aligned cells and visualizes the analytic results such as identifying multi-modal cell clusters of cells and detecting correlated genes with electrophysiological and morphological features. We demonstrated the usage of MANGEM by aligning Patch-seq multimodal data of neuronal cells in the mouse visual cortex.

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The Simularium Viewer: an interactive online tool for sharing spatiotemporal biological models

Cited by 8 publications

References 10 publications

Depicting a cellular space occupied by condensates

Depicting a cellular space occupied by condensates

PhysiCell Studio: a graphical tool to make agent-based modeling more accessible

MANGEM: a web app for Multimodal Analysis of Neuronal Gene expression, Electrophysiology and Morphology

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