Network‐assisted protein identification and data interpretation in shotgun proteomics

Abstract Protein assembly and biological interpretation of the assembled protein lists are critical steps in shotgun proteomics data analysis. Although most biological functions arise from interactions among proteins, current protein assembly pipelines treat proteins as independent entities. Usually...

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Main Authors: Jing Li, Lisa J Zimmerman, Byung‐Hoon Park, David L Tabb, Daniel C Liebler, Bing Zhang
Format: Article
Language:English
Published: Springer Nature 2009-08-01
Series:Molecular Systems Biology
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Online Access:https://doi.org/10.1038/msb.2009.54
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author Jing Li
Lisa J Zimmerman
Byung‐Hoon Park
David L Tabb
Daniel C Liebler
Bing Zhang
author_facet Jing Li
Lisa J Zimmerman
Byung‐Hoon Park
David L Tabb
Daniel C Liebler
Bing Zhang
author_sort Jing Li
collection DOAJ
description Abstract Protein assembly and biological interpretation of the assembled protein lists are critical steps in shotgun proteomics data analysis. Although most biological functions arise from interactions among proteins, current protein assembly pipelines treat proteins as independent entities. Usually, only individual proteins with strong experimental evidence, that is, confident proteins, are reported, whereas many possible proteins of biological interest are eliminated. We have developed a clique‐enrichment approach (CEA) to rescue eliminated proteins by incorporating the relationship among proteins as embedded in a protein interaction network. In several data sets tested, CEA increased protein identification by 8–23% with an estimated accuracy of 85%. Rescued proteins were supported by existing literature or transcriptome profiling studies at similar levels as confident proteins and at a significantly higher level than abandoned ones. Applying CEA on a breast cancer data set, rescued proteins coded by well‐known breast cancer genes. In addition, CEA generated a network view of the proteins and helped show the modular organization of proteins that may underpin the molecular mechanisms of the disease.
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spelling doaj-art-005d5917d4eb49008cfa75f73fb682132025-08-24T11:59:11ZengSpringer NatureMolecular Systems Biology1744-42922009-08-015111110.1038/msb.2009.54Network‐assisted protein identification and data interpretation in shotgun proteomicsJing Li0Lisa J Zimmerman1Byung‐Hoon Park2David L Tabb3Daniel C Liebler4Bing Zhang5Department of Biomedical Informatics, Vanderbilt University School of MedicineDepartment of Biochemistry, Vanderbilt University School of MedicineOak Ridge National LaboratoryDepartment of Biomedical Informatics, Vanderbilt University School of MedicineDepartment of Biomedical Informatics, Vanderbilt University School of MedicineDepartment of Biomedical Informatics, Vanderbilt University School of MedicineAbstract Protein assembly and biological interpretation of the assembled protein lists are critical steps in shotgun proteomics data analysis. Although most biological functions arise from interactions among proteins, current protein assembly pipelines treat proteins as independent entities. Usually, only individual proteins with strong experimental evidence, that is, confident proteins, are reported, whereas many possible proteins of biological interest are eliminated. We have developed a clique‐enrichment approach (CEA) to rescue eliminated proteins by incorporating the relationship among proteins as embedded in a protein interaction network. In several data sets tested, CEA increased protein identification by 8–23% with an estimated accuracy of 85%. Rescued proteins were supported by existing literature or transcriptome profiling studies at similar levels as confident proteins and at a significantly higher level than abandoned ones. Applying CEA on a breast cancer data set, rescued proteins coded by well‐known breast cancer genes. In addition, CEA generated a network view of the proteins and helped show the modular organization of proteins that may underpin the molecular mechanisms of the disease.https://doi.org/10.1038/msb.2009.54cliquedata interpretationprotein identificationprotein interaction networkshotgun proteomics
spellingShingle Jing Li
Lisa J Zimmerman
Byung‐Hoon Park
David L Tabb
Daniel C Liebler
Bing Zhang
Network‐assisted protein identification and data interpretation in shotgun proteomics
Molecular Systems Biology
clique
data interpretation
protein identification
protein interaction network
shotgun proteomics
title Network‐assisted protein identification and data interpretation in shotgun proteomics
title_full Network‐assisted protein identification and data interpretation in shotgun proteomics
title_fullStr Network‐assisted protein identification and data interpretation in shotgun proteomics
title_full_unstemmed Network‐assisted protein identification and data interpretation in shotgun proteomics
title_short Network‐assisted protein identification and data interpretation in shotgun proteomics
title_sort network assisted protein identification and data interpretation in shotgun proteomics
topic clique
data interpretation
protein identification
protein interaction network
shotgun proteomics
url https://doi.org/10.1038/msb.2009.54
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