{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,30]],"date-time":"2025-10-30T22:22:50Z","timestamp":1761862970303},"reference-count":14,"publisher":"Oxford University Press (OUP)","issue":"1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2011,1,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Motivation: Network-based representations of biological data have become an important way to analyze high-throughput data. To interpret the large amount of data that is produced by different high-throughput technologies, networks offer multifaceted aspects to analyze the data. As networks represent biological relationships within their structure, it turned out to be fruitful to analyze their topology. Therefore, we developed a freely available, open source R-package called Quantitative Analysis of Complex Networks (QuACN) to meet this challenge. QuACN contains different, information-theoretic and non-information-theoretic, topological network descriptors to analyze, classify and compare biological networks.<\/jats:p>\n               <jats:p>Availability: \u00a0QuACN is freely available under LGPL via CRAN (http:\/\/cran.r-project.org\/web\/packages\/QuACN\/).<\/jats:p>\n               <jats:p>Contact: \u00a0laurin.mueller@umit.at<\/jats:p>","DOI":"10.1093\/bioinformatics\/btq606","type":"journal-article","created":{"date-parts":[[2010,11,13]],"date-time":"2010-11-13T01:20:02Z","timestamp":1289611202000},"page":"140-141","source":"Crossref","is-referenced-by-count":49,"title":["<tt>QuACN<\/tt>: an R package for analyzing complex biological networks quantitatively"],"prefix":"10.1093","volume":"27","author":[{"given":"Laurin A. J.","family":"Mueller","sequence":"first","affiliation":[{"name":"1 Department of Biomedical Sciences and Engineering, Institute for Bioinformatics and Translational Research, University for Health Sciences, Medical Informatics and Technology (UMIT), Hall in Tirol and 2Biocenter, Division for Bioinformatics, Innsbruck Medical University, Innsbruck, Austria"}]},{"given":"Karl G.","family":"Kugler","sequence":"additional","affiliation":[{"name":"1 Department of Biomedical Sciences and Engineering, Institute for Bioinformatics and Translational Research, University for Health Sciences, Medical Informatics and Technology (UMIT), Hall in Tirol and 2Biocenter, Division for Bioinformatics, Innsbruck Medical University, Innsbruck, Austria"}]},{"given":"Andreas","family":"Dander","sequence":"additional","affiliation":[{"name":"1 Department of Biomedical Sciences and Engineering, Institute for Bioinformatics and Translational Research, University for Health Sciences, Medical Informatics and Technology (UMIT), Hall in Tirol and 2Biocenter, Division for Bioinformatics, Innsbruck Medical University, Innsbruck, Austria"}]},{"given":"Armin","family":"Graber","sequence":"additional","affiliation":[{"name":"1 Department of Biomedical Sciences and Engineering, Institute for Bioinformatics and Translational Research, University for Health Sciences, Medical Informatics and Technology (UMIT), Hall in Tirol and 2Biocenter, Division for Bioinformatics, Innsbruck Medical University, Innsbruck, Austria"}]},{"given":"Matthias","family":"Dehmer","sequence":"additional","affiliation":[{"name":"1 Department of Biomedical Sciences and Engineering, Institute for Bioinformatics and Translational Research, University for Health Sciences, Medical Informatics and Technology (UMIT), Hall in Tirol and 2Biocenter, Division for Bioinformatics, Innsbruck Medical University, Innsbruck, Austria"}]}],"member":"286","published-online":{"date-parts":[[2010,11,11]]},"reference":[{"key":"2023012511154752200_B1","first-page":"1695","article-title":"The igraph software package for complex network research","volume-title":"InterJournal","author":"Csardi","year":"2006"},{"key":"2023012511154752200_B2","doi-asserted-by":"crossref","first-page":"e8057","DOI":"10.1371\/journal.pone.0008057","article-title":"A large scale analysis of information-theoretic network complexity measures using chemical structures","volume":"4","author":"Dehmer","year":"2009","journal-title":"PLoS ONE"},{"key":"2023012511154752200_B3","doi-asserted-by":"crossref","first-page":"1655","DOI":"10.1021\/ci900060x","article-title":"On entropy-based molecular descriptors: statistical analysis of real and synthetic chemical structures","volume":"49","author":"Dehmer","year":"2009","journal-title":"J. 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