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Neuronize v2: Bridging the Gap Between Existing Proprietary Tools to Optimize Neuroscientific Workflows
Knowledge about neuron morphology is key to understanding brain structure and function. There are a variety of software tools that are used to segment and trace the neuron morphology. However, these tools usually utilize proprietary formats. This causes interoperability problems since the informatio...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7646287/ https://www.ncbi.nlm.nih.gov/pubmed/33192345 http://dx.doi.org/10.3389/fnana.2020.585793 |
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author | Velasco, Ivan Toharia, Pablo Benavides-Piccione, Ruth Fernaud-Espinosa, Isabel Brito, Juan P. Mata, Susana DeFelipe, Javier Pastor, Luis Bayona, Sofia |
author_facet | Velasco, Ivan Toharia, Pablo Benavides-Piccione, Ruth Fernaud-Espinosa, Isabel Brito, Juan P. Mata, Susana DeFelipe, Javier Pastor, Luis Bayona, Sofia |
author_sort | Velasco, Ivan |
collection | PubMed |
description | Knowledge about neuron morphology is key to understanding brain structure and function. There are a variety of software tools that are used to segment and trace the neuron morphology. However, these tools usually utilize proprietary formats. This causes interoperability problems since the information extracted with one tool cannot be used in other tools. This article aims to improve neuronal reconstruction workflows by facilitating the interoperability between two of the most commonly used software tools—Neurolucida (NL) and Imaris (Filament Tracer). The new functionality has been included in an existing tool—Neuronize—giving rise to its second version. Neuronize v2 makes it possible to automatically use the data extracted with Imaris Filament Tracer to generate a tracing with dendritic spine information that can be read directly by NL. It also includes some other new features, such as the ability to unify and/or correct inaccurately-formed meshes (i.e., dendritic spines) and to calculate new metrics. This tool greatly facilitates the process of neuronal reconstruction, bridging the gap between existing proprietary tools to optimize neuroscientific workflows. |
format | Online Article Text |
id | pubmed-7646287 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-76462872020-11-13 Neuronize v2: Bridging the Gap Between Existing Proprietary Tools to Optimize Neuroscientific Workflows Velasco, Ivan Toharia, Pablo Benavides-Piccione, Ruth Fernaud-Espinosa, Isabel Brito, Juan P. Mata, Susana DeFelipe, Javier Pastor, Luis Bayona, Sofia Front Neuroanat Neuroscience Knowledge about neuron morphology is key to understanding brain structure and function. There are a variety of software tools that are used to segment and trace the neuron morphology. However, these tools usually utilize proprietary formats. This causes interoperability problems since the information extracted with one tool cannot be used in other tools. This article aims to improve neuronal reconstruction workflows by facilitating the interoperability between two of the most commonly used software tools—Neurolucida (NL) and Imaris (Filament Tracer). The new functionality has been included in an existing tool—Neuronize—giving rise to its second version. Neuronize v2 makes it possible to automatically use the data extracted with Imaris Filament Tracer to generate a tracing with dendritic spine information that can be read directly by NL. It also includes some other new features, such as the ability to unify and/or correct inaccurately-formed meshes (i.e., dendritic spines) and to calculate new metrics. This tool greatly facilitates the process of neuronal reconstruction, bridging the gap between existing proprietary tools to optimize neuroscientific workflows. Frontiers Media S.A. 2020-10-06 /pmc/articles/PMC7646287/ /pubmed/33192345 http://dx.doi.org/10.3389/fnana.2020.585793 Text en Copyright © 2020 Velasco, Toharia, Benavides-Piccione, Fernaud-Espinosa, Brito, Mata, DeFelipe, Pastor and Bayona. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Neuroscience Velasco, Ivan Toharia, Pablo Benavides-Piccione, Ruth Fernaud-Espinosa, Isabel Brito, Juan P. Mata, Susana DeFelipe, Javier Pastor, Luis Bayona, Sofia Neuronize v2: Bridging the Gap Between Existing Proprietary Tools to Optimize Neuroscientific Workflows |
title | Neuronize v2: Bridging the Gap Between Existing Proprietary Tools to Optimize Neuroscientific Workflows |
title_full | Neuronize v2: Bridging the Gap Between Existing Proprietary Tools to Optimize Neuroscientific Workflows |
title_fullStr | Neuronize v2: Bridging the Gap Between Existing Proprietary Tools to Optimize Neuroscientific Workflows |
title_full_unstemmed | Neuronize v2: Bridging the Gap Between Existing Proprietary Tools to Optimize Neuroscientific Workflows |
title_short | Neuronize v2: Bridging the Gap Between Existing Proprietary Tools to Optimize Neuroscientific Workflows |
title_sort | neuronize v2: bridging the gap between existing proprietary tools to optimize neuroscientific workflows |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7646287/ https://www.ncbi.nlm.nih.gov/pubmed/33192345 http://dx.doi.org/10.3389/fnana.2020.585793 |
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