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piNET: a versatile web platform for downstream analysis and visualization of proteomics data

Rapid progress in proteomics and large-scale profiling of biological systems at the protein level necessitates the continued development of efficient computational tools for the analysis and interpretation of proteomics data. Here, we present the piNET server that facilitates integrated annotation,...

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Autores principales: Shamsaei, Behrouz, Chojnacki, Szymon, Pilarczyk, Marcin, Najafabadi, Mehdi, Niu, Wen, Chen, Chuming, Ross, Karen, Matlock, Andrea, Muhlich, Jeremy, Chutipongtanate, Somchai, Zheng, Jie, Turner, John, Vidović, Dušica, Jaffe, Jake, MacCoss, Michael, Wu, Cathy, Pillai, Ajay, Ma’ayan, Avi, Schürer, Stephan, Kouril, Michal, Medvedovic, Mario, Meller, Jarek
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7319557/
https://www.ncbi.nlm.nih.gov/pubmed/32469073
http://dx.doi.org/10.1093/nar/gkaa436
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author Shamsaei, Behrouz
Chojnacki, Szymon
Pilarczyk, Marcin
Najafabadi, Mehdi
Niu, Wen
Chen, Chuming
Ross, Karen
Matlock, Andrea
Muhlich, Jeremy
Chutipongtanate, Somchai
Zheng, Jie
Turner, John
Vidović, Dušica
Jaffe, Jake
MacCoss, Michael
Wu, Cathy
Pillai, Ajay
Ma’ayan, Avi
Schürer, Stephan
Kouril, Michal
Medvedovic, Mario
Meller, Jarek
author_facet Shamsaei, Behrouz
Chojnacki, Szymon
Pilarczyk, Marcin
Najafabadi, Mehdi
Niu, Wen
Chen, Chuming
Ross, Karen
Matlock, Andrea
Muhlich, Jeremy
Chutipongtanate, Somchai
Zheng, Jie
Turner, John
Vidović, Dušica
Jaffe, Jake
MacCoss, Michael
Wu, Cathy
Pillai, Ajay
Ma’ayan, Avi
Schürer, Stephan
Kouril, Michal
Medvedovic, Mario
Meller, Jarek
author_sort Shamsaei, Behrouz
collection PubMed
description Rapid progress in proteomics and large-scale profiling of biological systems at the protein level necessitates the continued development of efficient computational tools for the analysis and interpretation of proteomics data. Here, we present the piNET server that facilitates integrated annotation, analysis and visualization of quantitative proteomics data, with emphasis on PTM networks and integration with the LINCS library of chemical and genetic perturbation signatures in order to provide further mechanistic and functional insights. The primary input for the server consists of a set of peptides or proteins, optionally with PTM sites, and their corresponding abundance values. Several interconnected workflows can be used to generate: (i) interactive graphs and tables providing comprehensive annotation and mapping between peptides and proteins with PTM sites; (ii) high resolution and interactive visualization for enzyme-substrate networks, including kinases and their phospho-peptide targets; (iii) mapping and visualization of LINCS signature connectivity for chemical inhibitors or genetic knockdown of enzymes upstream of their target PTM sites. piNET has been built using a modular Spring-Boot JAVA platform as a fast, versatile and easy to use tool. The Apache Lucene indexing is used for fast mapping of peptides into UniProt entries for the human, mouse and other commonly used model organism proteomes. PTM-centric network analyses combine PhosphoSitePlus, iPTMnet and SIGNOR databases of validated enzyme-substrate relationships, for kinase networks augmented by DeepPhos predictions and sequence-based mapping of PhosphoSitePlus consensus motifs. Concordant LINCS signatures are mapped using iLINCS. For each workflow, a RESTful API counterpart can be used to generate the results programmatically in the json format. The server is available at http://pinet-server.org, and it is free and open to all users without login requirement.
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spelling pubmed-73195572020-07-01 piNET: a versatile web platform for downstream analysis and visualization of proteomics data Shamsaei, Behrouz Chojnacki, Szymon Pilarczyk, Marcin Najafabadi, Mehdi Niu, Wen Chen, Chuming Ross, Karen Matlock, Andrea Muhlich, Jeremy Chutipongtanate, Somchai Zheng, Jie Turner, John Vidović, Dušica Jaffe, Jake MacCoss, Michael Wu, Cathy Pillai, Ajay Ma’ayan, Avi Schürer, Stephan Kouril, Michal Medvedovic, Mario Meller, Jarek Nucleic Acids Res Web Server Issue Rapid progress in proteomics and large-scale profiling of biological systems at the protein level necessitates the continued development of efficient computational tools for the analysis and interpretation of proteomics data. Here, we present the piNET server that facilitates integrated annotation, analysis and visualization of quantitative proteomics data, with emphasis on PTM networks and integration with the LINCS library of chemical and genetic perturbation signatures in order to provide further mechanistic and functional insights. The primary input for the server consists of a set of peptides or proteins, optionally with PTM sites, and their corresponding abundance values. Several interconnected workflows can be used to generate: (i) interactive graphs and tables providing comprehensive annotation and mapping between peptides and proteins with PTM sites; (ii) high resolution and interactive visualization for enzyme-substrate networks, including kinases and their phospho-peptide targets; (iii) mapping and visualization of LINCS signature connectivity for chemical inhibitors or genetic knockdown of enzymes upstream of their target PTM sites. piNET has been built using a modular Spring-Boot JAVA platform as a fast, versatile and easy to use tool. The Apache Lucene indexing is used for fast mapping of peptides into UniProt entries for the human, mouse and other commonly used model organism proteomes. PTM-centric network analyses combine PhosphoSitePlus, iPTMnet and SIGNOR databases of validated enzyme-substrate relationships, for kinase networks augmented by DeepPhos predictions and sequence-based mapping of PhosphoSitePlus consensus motifs. Concordant LINCS signatures are mapped using iLINCS. For each workflow, a RESTful API counterpart can be used to generate the results programmatically in the json format. The server is available at http://pinet-server.org, and it is free and open to all users without login requirement. Oxford University Press 2020-07-02 2020-05-29 /pmc/articles/PMC7319557/ /pubmed/32469073 http://dx.doi.org/10.1093/nar/gkaa436 Text en © The Author(s) 2020. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Web Server Issue
Shamsaei, Behrouz
Chojnacki, Szymon
Pilarczyk, Marcin
Najafabadi, Mehdi
Niu, Wen
Chen, Chuming
Ross, Karen
Matlock, Andrea
Muhlich, Jeremy
Chutipongtanate, Somchai
Zheng, Jie
Turner, John
Vidović, Dušica
Jaffe, Jake
MacCoss, Michael
Wu, Cathy
Pillai, Ajay
Ma’ayan, Avi
Schürer, Stephan
Kouril, Michal
Medvedovic, Mario
Meller, Jarek
piNET: a versatile web platform for downstream analysis and visualization of proteomics data
title piNET: a versatile web platform for downstream analysis and visualization of proteomics data
title_full piNET: a versatile web platform for downstream analysis and visualization of proteomics data
title_fullStr piNET: a versatile web platform for downstream analysis and visualization of proteomics data
title_full_unstemmed piNET: a versatile web platform for downstream analysis and visualization of proteomics data
title_short piNET: a versatile web platform for downstream analysis and visualization of proteomics data
title_sort pinet: a versatile web platform for downstream analysis and visualization of proteomics data
topic Web Server Issue
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7319557/
https://www.ncbi.nlm.nih.gov/pubmed/32469073
http://dx.doi.org/10.1093/nar/gkaa436
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