{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,5]],"date-time":"2026-02-05T21:14:22Z","timestamp":1770326062995,"version":"3.49.0"},"reference-count":11,"publisher":"Oxford University Press (OUP)","issue":"17","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2011,9,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Summary: Chromosomal patterns of genomic signals represent molecular fingerprints that may reveal how the local structural organization of a genome impacts the functional control mechanisms. Thus, the integrative analysis of multiple sources of genomic data and information deepens the resolution and enhances the interpretation of stand-alone high-throughput data. In this note, we present PREDA (Position RElated Data Analysis), an R package for detecting regional variations in genomics data. PREDA identifies relevant chromosomal patterns in high-throughput data using a smoothing approach that accounts for distance and density variability of genomics features. Custom-designed data structures allow efficiently managing diverse signals in different genomes. A variety of smoothing functions and statistics empower flexible and robust workflows. The modularity of package design allows an easy deployment of custom analytical pipelines. Tabular and graphical representations facilitate downstream biological interpretation of results.<\/jats:p>\n               <jats:p>Availability: \u00a0PREDA is available in Bioconductor and at http:\/\/www.xlab.unimo.it\/PREDA.<\/jats:p>\n               <jats:p>Contact: \u00a0silvio.bicciato@unimore.it<\/jats:p>\n               <jats:p>Supplementary information: \u00a0Supplementary information is available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/btr404","type":"journal-article","created":{"date-parts":[[2011,7,9]],"date-time":"2011-07-09T00:14:53Z","timestamp":1310170493000},"page":"2446-2447","source":"Crossref","is-referenced-by-count":23,"title":["<i>PREDA<\/i>: an R-package to identify regional variations in genomic data"],"prefix":"10.1093","volume":"27","author":[{"given":"Francesco","family":"Ferrari","sequence":"first","affiliation":[{"name":"1 Department of Biomedical Sciences, Center for Genome Research, University of Modena and Reggio Emilia, Modena, 2Department of Statistics, University of Milano-Bicocca and 3Department of Biomedical Sciences and Technologies, University of Milano, Milano, Italy"}]},{"given":"Aldo","family":"Solari","sequence":"additional","affiliation":[{"name":"1 Department of Biomedical Sciences, Center for Genome Research, University of Modena and Reggio Emilia, Modena, 2Department of Statistics, University of Milano-Bicocca and 3Department of Biomedical Sciences and Technologies, University of Milano, Milano, Italy"}]},{"given":"Cristina","family":"Battaglia","sequence":"additional","affiliation":[{"name":"1 Department of Biomedical Sciences, Center for Genome Research, University of Modena and Reggio Emilia, Modena, 2Department of Statistics, University of Milano-Bicocca and 3Department of Biomedical Sciences and Technologies, University of Milano, Milano, Italy"}]},{"given":"Silvio","family":"Bicciato","sequence":"additional","affiliation":[{"name":"1 Department of Biomedical Sciences, Center for Genome Research, University of Modena and Reggio Emilia, Modena, 2Department of Statistics, University of Milano-Bicocca and 3Department of Biomedical Sciences and Technologies, University of Milano, Milano, Italy"}]}],"member":"286","published-online":{"date-parts":[[2011,7,7]]},"reference":[{"key":"2023012511532104700_B1","doi-asserted-by":"crossref","first-page":"5057","DOI":"10.1093\/nar\/gkp520","article-title":"A computational procedure to identify significant overlap of differentially expressed and genomic imbalanced regions in cancer datasets","volume":"37","author":"Bicciato","year":"2009","journal-title":"Nucleic Acids Res."},{"key":"2023012511532104700_B2","doi-asserted-by":"crossref","first-page":"2658","DOI":"10.1093\/bioinformatics\/btl455","article-title":"A locally adaptive statistical procedure (lap) to identify differentially expressed chromosomal regions","volume":"22","author":"Callegaro","year":"2006","journal-title":"Bioinformatics"},{"key":"2023012511532104700_B3","doi-asserted-by":"crossref","first-page":"533","DOI":"10.1093\/nar\/gkn948","article-title":"Motif discovery in promoters of genes co-localized and co-expressed during myeloid cells differentiation","volume":"37","author":"Coppe","year":"2009","journal-title":"Nucleic Acids Res."},{"key":"2023012511532104700_B4","doi-asserted-by":"crossref","first-page":"264","DOI":"10.1186\/1471-2164-8-264","article-title":"Genomic expression during human myelopoiesis","volume":"8","author":"Ferrari","year":"2007","journal-title":"BMC Genomics"},{"key":"2023012511532104700_B5","first-page":"89","article-title":"Dependency detection with similarity constraints","volume-title":"Proceedings of the 2009 IEEE International Workshop on Machine Learning for Signal Processing XIX","author":"Lahti","year":"2009"},{"issue":"Suppl. 4","key":"2023012511532104700_B6","doi-asserted-by":"crossref","first-page":"S9","DOI":"10.1186\/1753-6561-3-S4-S9","article-title":"Microarray data mining using Bioconductor packages","volume":"3","author":"Nie","year":"2009","journal-title":"BMC Proc."},{"key":"2023012511532104700_B7","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1186\/1475-2859-6-37","article-title":"Complete gene expression profiling of Saccharopolyspora erythraea using genechip DNA microarrays","volume":"6","author":"Peano","year":"2007","journal-title":"Microb. 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