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Network-centric analysis of co-fractionated protein complex profiles using SECAT

The Size-Exclusion Chromatography Analysis Toolkit (SECAT) elucidates protein complex dynamics using co-fractionated bottom-up mass spectrometry (CF-MS) data. Here, we present a protocol for the network-centric analysis and interpretation of CF-MS profiles using SECAT. We describe the technical step...

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Detalles Bibliográficos
Autores principales: Bokor, Benjamin J., Gorhe, Darvesh, Jovanovic, Marko, Rosenberger, George
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10199247/
https://www.ncbi.nlm.nih.gov/pubmed/37182203
http://dx.doi.org/10.1016/j.xpro.2023.102293
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author Bokor, Benjamin J.
Gorhe, Darvesh
Jovanovic, Marko
Rosenberger, George
author_facet Bokor, Benjamin J.
Gorhe, Darvesh
Jovanovic, Marko
Rosenberger, George
author_sort Bokor, Benjamin J.
collection PubMed
description The Size-Exclusion Chromatography Analysis Toolkit (SECAT) elucidates protein complex dynamics using co-fractionated bottom-up mass spectrometry (CF-MS) data. Here, we present a protocol for the network-centric analysis and interpretation of CF-MS profiles using SECAT. We describe the technical steps for preprocessing, scoring, semi-supervised machine learning, and quantification, including common pitfalls and their solutions. We further provide guidance for data export, visualization, and the interpretation of SECAT results to discover dysregulated proteins and interactions, supporting new hypotheses and biological insights. For complete details on the use and execution of this protocol, please refer to Rosenberger et al. (2020).(1)
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spelling pubmed-101992472023-05-21 Network-centric analysis of co-fractionated protein complex profiles using SECAT Bokor, Benjamin J. Gorhe, Darvesh Jovanovic, Marko Rosenberger, George STAR Protoc Protocol The Size-Exclusion Chromatography Analysis Toolkit (SECAT) elucidates protein complex dynamics using co-fractionated bottom-up mass spectrometry (CF-MS) data. Here, we present a protocol for the network-centric analysis and interpretation of CF-MS profiles using SECAT. We describe the technical steps for preprocessing, scoring, semi-supervised machine learning, and quantification, including common pitfalls and their solutions. We further provide guidance for data export, visualization, and the interpretation of SECAT results to discover dysregulated proteins and interactions, supporting new hypotheses and biological insights. For complete details on the use and execution of this protocol, please refer to Rosenberger et al. (2020).(1) Elsevier 2023-05-12 /pmc/articles/PMC10199247/ /pubmed/37182203 http://dx.doi.org/10.1016/j.xpro.2023.102293 Text en © 2023 The Authors https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Protocol
Bokor, Benjamin J.
Gorhe, Darvesh
Jovanovic, Marko
Rosenberger, George
Network-centric analysis of co-fractionated protein complex profiles using SECAT
title Network-centric analysis of co-fractionated protein complex profiles using SECAT
title_full Network-centric analysis of co-fractionated protein complex profiles using SECAT
title_fullStr Network-centric analysis of co-fractionated protein complex profiles using SECAT
title_full_unstemmed Network-centric analysis of co-fractionated protein complex profiles using SECAT
title_short Network-centric analysis of co-fractionated protein complex profiles using SECAT
title_sort network-centric analysis of co-fractionated protein complex profiles using secat
topic Protocol
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10199247/
https://www.ncbi.nlm.nih.gov/pubmed/37182203
http://dx.doi.org/10.1016/j.xpro.2023.102293
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