About: Modeling in the Time of COVID-19: Statistical and Rule-based Mesoscale Models

Facets (new session)
Description
Metadata
Settings
- owl:sameAs
- Inference Rule:

About: Modeling in the Time of COVID-19: Statistical and Rule-based Mesoscale Models Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : wasabi.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
title	Modeling in the Time of COVID-19: Statistical and Rule-based Mesoscale Models
Creator	Nguyen, Ngan Goodsell, David Alharbi, Ruwayda Autin, Ludovic Klein, Tobias Luo, Deng Maritan, Martina Mindek, Peter Strnad, Ondřej Viola, Ivan Wonka, Peter
source	ArXiv
abstract	We present a new technique for rapid modeling and construction of scientifically accurate mesoscale biological models. Resulting 3D models are based on few 2D microscopy scans and the latest knowledge about the biological entity represented as a set of geometric relationships. Our new technique is based on statistical and rule-based modeling approaches that are rapid to author, fast to construct, and easy to revise. From a few 2D microscopy scans, we learn statistical properties of various structural aspects, such as the outer membrane shape, spatial properties and distribution characteristics of the macromolecular elements on the membrane. This information is utilized in 3D model construction. Once all imaging evidence is incorporated in the model, additional information can be incorporated by interactively defining rules that spatially characterize the rest of the biological entity, such as mutual interactions among macromolecules, their distances and orientations to other structures. These rules are defined through an intuitive 3D interactive visualization and modeling feedback loop. We demonstrate the utility of our approach on a use case of the modeling procedure of the SARS-CoV-2 virus particle ultrastructure. Its first complete atomistic model, which we present here, can steer biological research to new promising directions in fighting spread of the virus.
has issue date	2020-05-01(xsd:dateTime)
has license	arxiv
sha1sum (hex)	7bf2d8b9801b612da3ab73bae942dcedd7d27e7d
resource representing a document's title	Modeling in the Time of COVID-19: Statistical and Rule-based Mesoscale Models
resource representing a document's body	covid:7bf2d8b9801b612da3ab73bae942dcedd7d27e7d#body_text
is schema:about of	named entity 'RULE-BASED' named entity 'SARS-CoV-2' named entity 'membrane proteins' named entity 'randomly selected' named entity 'coronavirus' named entity 'NTD' named entity 'bounding sphere' named entity 'normal vector' named entity 'HR2' named entity 'RNA' named entity 'cytoplasmic domain' named entity 'RNA-binding' named entity 'procedural modeling' named entity 'genome' named entity 'NTD' named entity 'ellipse' named entity 'molecular assembly' named entity 'stiffness' named entity 'conformations' named entity 'truncated normal distribution' named entity 'cellular receptors' named entity 'membrane proteins' named entity 'nucleotides' named entity 'algorithm' named entity 'guanine' named entity 'SARS-CoV-2' named entity 'ellipse' named entity 'PDB' named entity 'phosphate' named entity 'lipids' named entity 'procedural modeling' named entity 'nucleocapsid' named entity 'zoonotic' named entity 'microscopy' named entity 'hierarchical structure' named entity 'pentamer' named entity 'bending stiffness' named entity 'uracil' named entity 'cryoelectron microscopy' named entity 'spike (S) protein' named entity 'virion' named entity 'lipid membrane' named entity 'molecular structures' named entity 'statistical learning' named entity 'biological models' named entity 'objective function' named entity 'RNA' named entity 'polyline' named entity 'protein' named entity 'human-readable' named entity 'NMR' named entity 'homology modeling' named entity 'emerging viruses' named entity 'standard deviation' named entity 'user experience' named entity 'homology modeling' named entity 'SARS-CoV-2' named entity 'procedural modeling' named entity 'cytosine' named entity 'adenine' named entity 'cryoEM' named entity 'protein assembly' named entity 'triangular mesh' named entity 'capsids' named entity 'protein conformation' named entity 'dimers' named entity 'RNA' named entity 'nucleocapsid' named entity 'viruses' named entity 'virion' named entity 'SARS' named entity 'RNA' named entity 'NTD' named entity 'probability' named entity 'probability' named entity 'ellipse' named entity 'nucleoprotein'

Faceted Search & Find service v1.13.91 as of Mar 24 2020

Alternative Linked Data Documents: Sponger | ODE Content Formats:

RDF

ODATA

Microdata

About

OpenLink Virtuoso version 07.20.3229 as of Jul 10 2020, on Linux (x86_64-pc-linux-gnu), Single-Server Edition (94 GB total memory)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2025 OpenLink Software