{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T09:03:53Z","timestamp":1790845433155,"version":"4.1.0"},"reference-count":45,"publisher":"MDPI AG","issue":"19","license":[{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Italian Ministry of University and Research","award":["PRIN2022: 2022Z2TE5P (DDS)"],"award-info":[{"award-number":["PRIN2022: 2022Z2TE5P (DDS)"]}]},{"name":"Italian Ministry of University and Research","award":["PRIN2022: 2022LNHZAP (PLM)"],"award-info":[{"award-number":["PRIN2022: 2022LNHZAP (PLM)"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Biology"],"abstract":"<jats:p>The demand for user-friendly applications to support biologists in analyzing high-throughput proteomics data remains a pressing challenge. Given the complexity and the multiple intermediate steps involved, this process is time-consuming and often requires specialized computational skills. To simplify and accelerate the exploration of proteomics data, we present PiProteline, an R package designed to operate on high-dimensional data matrices assembled from the output of any search engine commonly used in bottom-up proteomics experiments. In addition to data preprocessing and descriptive statistics, PiProteline enables label-free quantitation, functional enrichment, and systems biology analyses. It supports both unweighted and weighted protein\u2013protein interaction (PPI) network topological analyses for the identification of critical nodes, such as hubs and bottlenecks. By integrating multiple computational approaches, PiProteline accelerates the selection of potentially relevant protein signatures, providing insights into the molecular mechanisms characterizing the investigated systems. This information facilitates the formulation of new hypotheses and the design of targeted experiments, ultimately reducing costs and advancing translational medicine. PiProteline is available as an open-source R package via GitHub, as a Shiny application, and via Zenodo.<\/jats:p>","DOI":"10.3390\/biology15191723","type":"journal-article","created":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T08:19:08Z","timestamp":1790842748000},"page":"1723","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["PiProteline: An R Package for Integrated Proteomics Data Analysis, from Label-Free Quantitation to Systems Biology"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-5807-7827","authenticated-orcid":false,"given":"Andrea","family":"Lomagno","sequence":"first","affiliation":[{"name":"Department of Biomedical Science, Institute for Biomedical Technologies, National Research Council, F.lli Cervi 93, Segrate, 20054 Milan, Italy"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"conceptualization","vocabulary":"credit"},{"role":"methodology","vocabulary":"credit"},{"role":"formal-analysis","vocabulary":"credit"},{"role":"software","vocabulary":"credit"},{"role":"data-curation","vocabulary":"credit"},{"role":"writing-original-draft","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1128-5489","authenticated-orcid":false,"given":"Saleh","family":"Hamed","sequence":"additional","affiliation":[{"name":"Department of Biomedical Science, Institute for Biomedical Technologies, National Research Council, F.lli Cervi 93, Segrate, 20054 Milan, Italy"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"methodology","vocabulary":"credit"},{"role":"software","vocabulary":"credit"},{"role":"formal-analysis","vocabulary":"credit"},{"role":"data-curation","vocabulary":"credit"},{"role":"writing-original-draft","vocabulary":"credit"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1635-1350","authenticated-orcid":false,"given":"Ishak","family":"Yusuf","sequence":"additional","affiliation":[{"name":"Department of Biomedical Science, Institute for Biomedical Technologies, National Research Council, F.lli Cervi 93, Segrate, 20054 Milan, Italy"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"methodology","vocabulary":"credit"},{"role":"formal-analysis","vocabulary":"credit"},{"role":"writing-original-draft","vocabulary":"credit"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4364-0393","authenticated-orcid":false,"given":"Pietro Luigi","family":"Mauri","sequence":"additional","affiliation":[{"name":"Department of Biomedical Science, Institute for Biomedical Technologies, National Research Council, F.lli Cervi 93, Segrate, 20054 Milan, Italy"},{"name":"Institute of Experimental Endocrinology and Oncology \u201cG. Salvatore\u201d, National Research Council, Pietro Castellino 111, 80131 Naples, Italy"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"resources","vocabulary":"credit"},{"role":"writing-original-draft","vocabulary":"credit"},{"role":"funding-acquisition","vocabulary":"credit"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7143-6229","authenticated-orcid":false,"given":"Dario","family":"Di Silvestre","sequence":"additional","affiliation":[{"name":"Department of Biomedical Science, Institute for Biomedical Technologies, National Research Council, F.lli Cervi 93, Segrate, 20054 Milan, Italy"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"conceptualization","vocabulary":"credit"},{"role":"resources","vocabulary":"credit"},{"role":"writing-original-draft","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"},{"role":"supervision","vocabulary":"credit"},{"role":"funding-acquisition","vocabulary":"credit"}]}],"member":"1968","published-online":{"date-parts":[[2026,10,1]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"100561","DOI":"10.1016\/j.mcpro.2023.100561","article-title":"Multi-Omics Profiling for Health","volume":"22","author":"Babu","year":"2023","journal-title":"Mol. Cell. Proteom."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"nwaf278","DOI":"10.1093\/nsr\/nwaf278","article-title":"The coming era of proteomics-driven precision medicine","volume":"12","author":"Jiang","year":"2025","journal-title":"Natl. Sci. Rev."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"681","DOI":"10.1038\/nmeth0910-681","article-title":"Mass spectrometry in high-throughput proteomics: Ready for the big time","volume":"7","author":"Nilsson","year":"2010","journal-title":"Nat. Methods"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"14466","DOI":"10.1021\/acs.analchem.0c02513","article-title":"PASS-DIA: A Data-Independent Acquisition Approach for Discovery Studies","volume":"92","author":"Mun","year":"2020","journal-title":"Anal. Chem."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"369","DOI":"10.1007\/978-1-0716-4298-6_22","article-title":"Computational Tools and Methods for the Study of Systemic Amyloidosis at the Clinical and Molecular Level","volume":"Volume 2884","author":"Silvestre","year":"2025","journal-title":"Methods in Molecular Biology"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1016\/j.ddtec.2021.06.007","article-title":"Recent advances in mass-spectrometry based proteomics software, tools and databases","volume":"39","author":"Halder","year":"2021","journal-title":"Drug Discov. Today Technol."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"418","DOI":"10.1021\/acs.jproteome.3c00636","article-title":"WOMBAT-P: Benchmarking Label-Free Proteomics Data Analysis Workflows","volume":"23","author":"Hagemeijer","year":"2024","journal-title":"J. Proteome Res."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"2511","DOI":"10.1093\/bioinformatics\/btu200","article-title":"aLFQ: An R-package for estimating absolute protein quantities from label-free LC-MS\/MS proteomics data","volume":"30","author":"Rosenberger","year":"2014","journal-title":"Bioinformatics"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1092","DOI":"10.1021\/acs.jproteome.2c00441","article-title":"prolfqua: A Comprehensive R-Package for Proteomics Differential Expression Analysis","volume":"22","author":"Wolski","year":"2023","journal-title":"J. Proteome Res."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"vbad025","DOI":"10.1093\/bioadv\/vbad025","article-title":"promor: A comprehensive R package for label-free proteomics data analysis and predictive modeling","volume":"3","author":"Ranathunge","year":"2023","journal-title":"Bioinform. 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BMC Bioinform., 24.","DOI":"10.1186\/s12859-023-05360-7"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"vbab041","DOI":"10.1093\/bioadv\/vbab041","article-title":"protti: An R package for comprehensive data analysis of peptide- and protein-centric bottom-up proteomics data","volume":"2","author":"Quast","year":"2022","journal-title":"Bioinform. Adv."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"6","DOI":"10.1186\/s13637-017-0059-z","article-title":"From protein-protein interactions to protein co-expression networks: A new perspective to evaluate large-scale proteomic data","volume":"2017","author":"Vella","year":"2017","journal-title":"Eurasip J. Bioinform. Syst. Biol."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"bbaf146","DOI":"10.1093\/bib\/bbaf146","article-title":"CoPPIs algorithm: A tool to unravel protein cooperative strategies in pathophysiological conditions","volume":"26","author":"Lomagno","year":"2025","journal-title":"Brief. Bioinform."},{"key":"ref_17","unstructured":"Wickham, H. (2026, September 01). Easily Install and Load the \u2019Tidyverse\u2019 [R Package Tidyverse Version 2.0.0]. CRAN: Contributed Packages. Available online: https:\/\/cran.r-project.org\/web\/packages\/tidyverse\/index.html."},{"key":"ref_18","unstructured":"Rezwani, M. (2026, September 01). User-Friendly R Interface to Biologic Web Services\u2019 API [R Package Rbioapi Version 0.8.2]. CRAN: Contributed Packages. Available online: https:\/\/cran.r-project.org\/web\/packages\/rbioapi\/index.html."},{"key":"ref_19","unstructured":"Cs\u00e1rdi, G., Nepusz, T., M\u00fcller, K., Horv\u00e1t, S., Traag, V., Zanini, F., and Noom, D. (2026, September 01). igraph for R: R Interface of the Igraph Library for Graph Theory and Network Analysis. Available online: https:\/\/zenodo.org\/records\/21404613."},{"key":"ref_20","unstructured":"Chang, W., Cheng, J., Allaire, J., Sievert, C., Schloerke, B., Xie, Y., Allen, J., McPherson, J., Dipert, A., and Borges, B. (2026, September 01). Web Application Framework for R [R Package Shiny Version 1.11.1]. CRAN: Contributed Packages. Available online: https:\/\/cran.r-project.org\/web\/packages\/shiny\/index.html."},{"key":"ref_21","unstructured":"Perrier, V., Meyer, F., and Granjon, D. (2026, September 01). Custom Inputs Widgets for Shiny [R Package Shiny Widgets Version 0.9.0]. CRAN: Contributed Packages. Available online: https:\/\/cran.r-project.org\/web\/packages\/shinyWidgets\/index.html."},{"key":"ref_22","unstructured":"Xie, Y., Cheng, J., Tan, X., and Aden-Buie, G. (2026, September 01). A Wrapper of the JavaScript Library `DataTables\u2019 [R Package DT Version 0.34.0]. CRAN: Contributed Packages. Available online: https:\/\/cran.r-project.org\/web\/packages\/DT\/index.html."},{"key":"ref_23","unstructured":"Wickham, H., Chang, W., Henry, L., Pedersen, T.L., Takahashi, K., Wilke, C., Woo, K., Yutani, H., Dunnington, D., and van den Brand, T. (2026, September 01). Create Elegant Data Visualisations Using the Grammar of Graphics [R Package Ggplot2 Version 4.0.0]. CRAN: Contributed Packages 2025. Available online: https:\/\/cran.r-project.org\/web\/packages\/ggplot2\/index.html."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"33","DOI":"10.1038\/s41531-024-00645-x","article-title":"Large-scale proteomics analysis of five brain regions from Parkinson\u2019s disease patients with a GBA1 mutation","volume":"10","author":"Blumenreich","year":"2024","journal-title":"npj Park. Dis."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"3497","DOI":"10.1021\/acs.jproteome.1c00143","article-title":"Comparative Evaluation of MaxQuant and Proteome Discoverer MS1-Based Protein Quantification Tools","volume":"20","author":"Palomba","year":"2021","journal-title":"J. Proteome Res."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"137076","DOI":"10.1155\/2015\/137076","article-title":"freeQuant: A Mass Spectrometry Label-Free Quantification Software Tool for Complex Proteome Analysis","volume":"2015","author":"Deng","year":"2015","journal-title":"Sci. World J."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Testa, L., Klei, L., Rengle, A., Yocum, A., Lewis, D.A., Devlin, B., Roeder, K., and MacDonald, M.L. (2026). Estimating protein isoform abundances with PAQu. bioRxiv.","DOI":"10.64898\/2026.04.20.719668"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1487","DOI":"10.1074\/mcp.M500084-MCP200","article-title":"Comparison of Label-free Methods for Quantifying Human Proteins by Shotgun Proteomics","volume":"4","author":"Old","year":"2005","journal-title":"Mol. Cell. Proteom."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"D638","DOI":"10.1093\/nar\/gkac1000","article-title":"The STRING database in 2023: Protein\u2013protein association networks and functional enrichment analyses for any sequenced genome of interest","volume":"51","author":"Szklarczyk","year":"2022","journal-title":"Nucleic Acids Res."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"840518","DOI":"10.1155\/2010\/840518","article-title":"Mass spectrometry-based label-free quantitative proteomics","volume":"2010","author":"Zhu","year":"2010","journal-title":"J. Biomed. Biotechnol."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"342","DOI":"10.4238\/vol7-2gmr426","article-title":"Identifying differences in protein expression levels by spectral counting and feature selection","volume":"7","author":"Carvalho","year":"2008","journal-title":"Genet. Mol. Res. GMR"},{"key":"ref_32","unstructured":"Buderer, N.M., and Brannan, G.D. (2024). Comparing the Means of Independent Groups: ANOVA, ANCOVA, MANOVA, and MANCOVA. StatPearls, StatPearls Publishing."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"406","DOI":"10.1016\/j.immuni.2016.01.028","article-title":"The Proteomic Landscape of Human Ex Vivo Regulatory and Conventional T Cells Reveals Specific Metabolic Requirements","volume":"44","author":"Procaccini","year":"2016","journal-title":"Immunity"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"bbad002","DOI":"10.1093\/bib\/bbad002","article-title":"A review on longitudinal data analysis with random forest","volume":"24","author":"Hu","year":"2023","journal-title":"Brief. Bioinform."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"530","DOI":"10.1038\/nprot.2017.147","article-title":"Proteome-wide identification of ubiquitin interactions using UbIA-MS","volume":"13","author":"Zhang","year":"2018","journal-title":"Nat. Protoc."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"e47","DOI":"10.1093\/nar\/gkv007","article-title":"limma powers differential expression analyses for RNA-sequencing and microarray studies","volume":"43","author":"Ritchie","year":"2015","journal-title":"Nucleic Acids Res."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1016\/j.euprot.2015.02.002","article-title":"Detecting significant changes in protein abundance","volume":"7","author":"Kammers","year":"2015","journal-title":"EuPA Open Proteom."},{"key":"ref_38","unstructured":"Fraenkel, J.R., Wallen, N.E., and Hyun, H.H. (2011). How to Design and Evaluate Research in Education, McGraw-Hill Humanities\/Social Sciences\/Languages."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"D730","DOI":"10.1093\/nar\/gkae1113","article-title":"The STRING database in 2025: Protein networks with directionality of regulation","volume":"53","author":"Szklarczyk","year":"2025","journal-title":"Nucleic Acids Res."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"100452","DOI":"10.1016\/j.mcpro.2022.100452","article-title":"Mass Spectrometry\u2013Based Proteomics Analysis of Human Substantia Nigra From Parkinson\u2019s Disease Patients Identifies Multiple Pathways Potentially Involved in the Disease","volume":"22","author":"Jang","year":"2023","journal-title":"Mol. Cell. Proteom."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1186\/s13024-023-00676-7","article-title":"Mitochondrial dysfunction in Parkinson\u2019s disease\u2014A key disease hallmark with therapeutic potential","volume":"18","author":"Henrich","year":"2023","journal-title":"Mol. Neurodegener."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"901","DOI":"10.1038\/s41586-025-08584-0","article-title":"Mass-spectrometry-based proteomics: From single cells to clinical applications","volume":"638","author":"Guo","year":"2025","journal-title":"Nature"},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"(2025). EATRIS-Plus Multi-omics working group and Stakeholders. Multi-omics Quality Assessment in Personalized Medicine Through European Infrastructure for Translational Medicine (EATRIS): An Overview. Phenomics, 5, 311\u2013325.","DOI":"10.1007\/s43657-024-00170-0"},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Vincent, A.T., and Charette, S.J. (2015). Who qualifies to be a bioinformatician?. Front. Genet., 6.","DOI":"10.3389\/fgene.2015.00164"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"20058","DOI":"10.1021\/acs.analchem.5c01812","article-title":"A New Approach to Large Multiomics Data Integration","volume":"97","author":"Dexter","year":"2025","journal-title":"Anal. Chem."}],"container-title":["Biology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2079-7737\/15\/19\/1723\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T08:52:54Z","timestamp":1790844774000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2079-7737\/15\/19\/1723"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,10,1]]},"references-count":45,"journal-issue":{"issue":"19","published-online":{"date-parts":[[2026,10]]}},"alternative-id":["biology15191723"],"URL":"https:\/\/doi.org\/10.3390\/biology15191723","relation":{},"ISSN":["2079-7737"],"issn-type":[{"value":"2079-7737","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,10,1]]}}}