{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,15]],"date-time":"2025-10-15T17:29:43Z","timestamp":1760549383271},"reference-count":13,"publisher":"Oxford University Press (OUP)","issue":"14","license":[{"start":{"date-parts":[[2016,10,2]],"date-time":"2016-10-02T00:00:00Z","timestamp":1475366400000},"content-version":"vor","delay-in-days":1215,"URL":"http:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2013,7,15]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Summary: Pathway Processor 2.0 is a web application designed to analyze high-throughput datasets, including but not limited to microarray and next-generation sequencing, using a pathway centric logic. In addition to well-established methods such as the Fisher\u2019s test and impact analysis, Pathway Processor 2.0 offers innovative methods that convert gene expression into pathway expression, leading to the identification of differentially regulated pathways in a dataset of choice.<\/jats:p>\n               <jats:p>Availability and implementation: Pathway Processor 2.0 is available as a web service at http:\/\/compbiotoolbox.fmach.it\/pathwayProcessor\/. Sample datasets to test the functionality can be used directly from the application.<\/jats:p>\n               <jats:p>Contact: \u00a0duccio.cavalieri@fmach.it<\/jats:p>\n               <jats:p>Supplementary information: \u00a0Supplementary data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/btt292","type":"journal-article","created":{"date-parts":[[2013,6,6]],"date-time":"2013-06-06T00:44:12Z","timestamp":1370479452000},"page":"1825-1826","source":"Crossref","is-referenced-by-count":5,"title":["Pathway Processor 2.0: a web resource for pathway-based analysis of high-throughput data"],"prefix":"10.1093","volume":"29","author":[{"given":"Luca","family":"Beltrame","sequence":"first","affiliation":[{"name":"1 Translational Genomics Unit, Department of Oncology, Istituto di Ricerche Farmacologiche \u2018Mario Negri\u2019 IRCCS, Via La Masa 19, 20159 Milano, Italy and 2Research and Innovation Center, Edmund Mach Foundation, Via E Mach 1, 8010 S. Michele all\u2019Adige, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Luca","family":"Bianco","sequence":"additional","affiliation":[{"name":"1 Translational Genomics Unit, Department of Oncology, Istituto di Ricerche Farmacologiche \u2018Mario Negri\u2019 IRCCS, Via La Masa 19, 20159 Milano, Italy and 2Research and Innovation Center, Edmund Mach Foundation, Via E Mach 1, 8010 S. Michele all\u2019Adige, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Paolo","family":"Fontana","sequence":"additional","affiliation":[{"name":"1 Translational Genomics Unit, Department of Oncology, Istituto di Ricerche Farmacologiche \u2018Mario Negri\u2019 IRCCS, Via La Masa 19, 20159 Milano, Italy and 2Research and Innovation Center, Edmund Mach Foundation, Via E Mach 1, 8010 S. Michele all\u2019Adige, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Duccio","family":"Cavalieri","sequence":"additional","affiliation":[{"name":"1 Translational Genomics Unit, Department of Oncology, Istituto di Ricerche Farmacologiche \u2018Mario Negri\u2019 IRCCS, Via La Masa 19, 20159 Milano, Italy and 2Research and Innovation Center, Edmund Mach Foundation, Via E Mach 1, 8010 S. Michele all\u2019Adige, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2013,6,5]]},"reference":[{"key":"2023012810452311200_btt292-B1","doi-asserted-by":"crossref","first-page":"1600","DOI":"10.1093\/bioinformatics\/btl140","article-title":"Improved scoring of functional groups from gene expression data by decorrelating go graph structure","volume":"22","author":"Alexa","year":"2006","journal-title":"Bioinformatics"},{"key":"2023012810452311200_btt292-B2","doi-asserted-by":"crossref","first-page":"e4128","DOI":"10.1371\/journal.pone.0004128","article-title":"Using pathway signatures as means of identifying similarities among microarray experiments","volume":"4","author":"Beltrame","year":"2009","journal-title":"PLoS One"},{"key":"2023012810452311200_btt292-B3","doi-asserted-by":"crossref","first-page":"1537","DOI":"10.1101\/gr.6202607","article-title":"A systems biology approach for pathway level analysis","volume":"17","author":"Draghici","year":"2007","journal-title":"Genome Res."},{"key":"2023012810452311200_btt292-B4","doi-asserted-by":"crossref","first-page":"1121","DOI":"10.1101\/gr.226602","article-title":"Pathway processor: a tool for integrating whole-genome expression results into metabolic networks","volume":"12","author":"Grosu","year":"2002","journal-title":"Genome Res."},{"key":"2023012810452311200_btt292-B5","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1186\/1471-2105-14-7","article-title":"GSVA: gene set variation analysis for microarray and RNA-seq data","volume":"14","author":"Haenzelmann","year":"2013","journal-title":"BMC Bioinformatics"},{"key":"2023012810452311200_btt292-B6","doi-asserted-by":"crossref","first-page":"e1002375","DOI":"10.1371\/journal.pcbi.1002375","article-title":"Ten years of pathway analysis: current approaches and outstanding challenges","volume":"8","author":"Khatri","year":"2012","journal-title":"PLoS Comput. 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