Increasingly, proteomic profiling efforts involve identification and quantification of specific proteoforms that may exhibit distinct activities and functions, including those resulting from protein post-translational modifications (PTMs) ( 8). Further downstream analysis is subsequently performed to facilitate biological interpretation of such obtained quantitative results, with its own distinct set of challenges ( 6), and an interdependent ecosystem of databases, tools and resources for proteomics research ( 7).
In this context, many methods and data processing tools have been developed for the identification and quantification of peptides and proteins from biological samples using mass spectrometry-based approaches ( 4–6). Methods and tools for computational proteomics data analysis evolve constantly in order to match rapid advances in proteomics and enabled by them large scale efforts aiming to profile biological systems at the protein level ( 1–3).
#Peptideshaker ptm color free#
The server is available at, and it is free and open to all users without login requirement. For each workflow, a RESTful API counterpart can be used to generate the results programmatically in the json format. Concordant LINCS signatures are mapped using iLINCS. 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. 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. piNET has been built using a modular Spring-Boot JAVA platform as a fast, versatile and easy to use tool.
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. The primary input for the server consists of a set of peptides or proteins, optionally with PTM sites, and their corresponding abundance values. 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. 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.
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