LifeBrush: Painting, simulating, and visualizing dense biomolecular environments

Davison, Timothy; Samavati, Faramarz; Jacob, Christian

doi:10.1016/j.cag.2019.05.006

Cited by 16 publications

(10 citation statements)

References 17 publications

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“…The advantage of VR is that it makes easier for non-expert users to navigate the computer environment. From simply walking around the visualization to quite literally grabbing the model and turning it around, it offers very intuitive and new means of looking at molecular models [80] , [81] . Unity also provides real-time visual feedback to the user.…”

Section: Discussionmentioning

confidence: 99%

Multiscale modelling of the extracellular matrix

Wong

Crowet

Dauchez

et al. 2022

Matrix Biology Plus

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Section: Discussionmentioning

confidence: 99%

Multiscale modelling of the extracellular matrix

Wong

Crowet

Dauchez

et al. 2022

Matrix Biology Plus

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“…The main challenge for experimental systems like CellPAINT and LifeBrush is that new software using non‐standard inputs for building parameterized models requires part of the mesoscale simulation workflow to be software developer‐lead, that is, every new molecular agent and its interactomics (e.g., interaction networks) needs new software to be developed. Increasingly sophisticated 3D VR toolkits of molecules, structures, and phenomena, with the ability for users to place them into their model, 181 will emerge as new molecules and functionality are added.…”

Section: Visualization and Model Building For The Biological Mesoscalementioning

confidence: 99%

Moving in the mesoscale: Understanding the mechanics of cytoskeletal molecular motors by combining mesoscale simulations with imaging

Gravett

Cocking

Curd

et al. 2021

WIREs Comput Mol Sci

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Rapid advances in experimental biophysical techniques are generating a wealth of information about the mechanical operation of the cellular cytoskeleton and its motors. However, each of these tools typically provides only a limited piece of a highly complex puzzle. There is a need to develop new computational tools that can integrate these data together into a central model.Here we discuss the experimental advances alongside the computational tools, and propose how these could be developed to successfully combine the emerging structural and dynamic experimental data on cytoskeletal motors. We consider examples of both single motors and arrays of motors within a biological cell.

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“…Whereas the overwhelming part of protein visualization so far may have focused on displaying existing models, the future may focus more intensely on methods to visually create complex molecular landscapes from scratch. Novel technology may be instrumental to this task [70][71][72][73].…”

Section: Future Trends?mentioning

confidence: 99%

Visualizing protein structures — tools and trends

Martinez

Chavent

Baaden

2020

Biochemical Society Transactions

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Molecular visualization is fundamental in the current scientific literature, textbooks and dissemination materials. It provides an essential support for presenting results, reasoning on and formulating hypotheses related to molecular structure. Tools for visual exploration of structural data have become easily accessible on a broad variety of platforms thanks to advanced software tools that render a great service to the scientific community. These tools are often developed across disciplines bridging computer science, biology and chemistry. This mini-review was written as a short and compact overview for scientists who need to visualize protein structures and want to make an informed decision which tool they should use. Here, we first describe a few ‘Swiss Army knives’ geared towards protein visualization for everyday use with an existing large user base, then focus on more specialized tools for peculiar needs that are not yet as broadly known. Our selection is by no means exhaustive, but reflects a diverse snapshot of scenarios that we consider informative for the reader. We end with an account of future trends and perspectives.

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LifeBrush: Painting, simulating, and visualizing dense biomolecular environments

Cited by 16 publications

References 17 publications

Multiscale modelling of the extracellular matrix

Multiscale modelling of the extracellular matrix

Moving in the mesoscale: Understanding the mechanics of cytoskeletal molecular motors by combining mesoscale simulations with imaging

Visualizing protein structures — tools and trends

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