{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,10]],"date-time":"2026-02-10T18:34:27Z","timestamp":1770748467975,"version":"3.50.0"},"reference-count":49,"publisher":"SAGE Publications","issue":"6","license":[{"start":{"date-parts":[[2015,8,10]],"date-time":"2015-08-10T00:00:00Z","timestamp":1439164800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Journal of Intelligent &amp; Fuzzy Systems"],"published-print":{"date-parts":[[2015,8,10]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>We evaluate a version of the recently-proposed classification system named Optimized Dissimilarity Space Embedding (ODSE) that operates in the input space of sequences of generic objects. The ODSE system has been originally presented as a classification system for patterns represented as labeled graphs. However, since ODSE is founded on the dissimilarity space representation of the input data, the classifier can be easily adapted to any input domain where it is possible to define a meaningful dissimilarity measure. Here we demonstrate the effectiveness of the ODSE classifier for sequences by considering an application dealing with the recognition of the solubility degree of the Escherichia coli proteome. Solubility, or analogously aggregation propensity, is an important property of protein molecules, which is intimately related to the mechanisms underlying the chemico-physical process of folding. Each protein of our dataset is initially associated with a solubility degree and it is represented as a sequence of symbols, denoting the 20 amino acid residues. The herein obtained computational results, which we stress that have been achieved with no context-dependent tuning of the ODSE system, confirm the validity and generality of the ODSE-based approach for structured data classification.<\/jats:p>","DOI":"10.3233\/ifs-151550","type":"journal-article","created":{"date-parts":[[2015,8,21]],"date-time":"2015-08-21T15:56:04Z","timestamp":1440172564000},"page":"2725-2733","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":1,"title":["Classifying sequences by the optimized dissimilarity space embedding approach: A case study on the solubility analysis of the E. coli proteome"],"prefix":"10.1177","volume":"28","author":[{"given":"Lorenzo","family":"Livi","sequence":"first","affiliation":[{"name":"Department of Computer Science, Ryerson University, Toronto, ON, Canada"}]},{"given":"Antonello","family":"Rizzi","sequence":"additional","affiliation":[{"name":"Department of Information Engineering, Electronics, and Telecommunications, SAPIENZA University of Rome, via Eudossiana, Rome, Italy"}]},{"given":"Alireza","family":"Sadeghian","sequence":"additional","affiliation":[{"name":"Department of Information Engineering, Electronics, and Telecommunications, SAPIENZA University of Rome, via Eudossiana, Rome, Italy"}]}],"member":"179","published-online":{"date-parts":[[2015,8,10]]},"reference":[{"key":"e_1_3_1_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jmb.2011.12.005"},{"key":"e_1_3_1_3_1","first-page":"1293","article-title":"Applying Dissimilarity Representation to Off-Line Signature Verification","author":"Batista L","year":"2010","unstructured":"BatistaLGrangerESabourinR2010Applying Dissimilarity Representation to Off-Line Signature VerificationIn Proceedings of the 2010 20th International Conference on Pattern Recognition, ICPR12931297ISBN 978-0-7695-4109-9","journal-title":"In Proceedings of the 2010 20th International Conference on Pattern Recognition, ICPR"},{"key":"e_1_3_1_4_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00500-013-1065-z"},{"key":"e_1_3_1_5_1","first-page":"1","article-title":"Two density-based k-means initialization algorithms for non-metric data clustering","author":"Bianchi FM","year":"2015","unstructured":"BianchiFMLiviLRizziA2015Two density-based k-means initialization algorithms for non-metric data clusteringPattern Analysis and Applications19ISSN 1433-7541","journal-title":"Pattern Analysis and Applications"},{"key":"e_1_3_1_6_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0031-3203(04)00162-1"},{"key":"e_1_3_1_7_1","first-page":"177","article-title":"Prototype Selection for Dissimilarity Representation by a Genetic Algorithm","author":"Cala\u00f1a Y","year":"2010","unstructured":"Cala\u00f1aYReyesEAlzateMDuinRPW2010Prototype Selection for Dissimilarity Representation by a Genetic AlgorithmIn Proceedings of the 20th International Conference on Pattern Recognition177180","journal-title":"In Proceedings of the 20th International Conference on Pattern Recognition"},{"key":"e_1_3_1_8_1","first-page":"410","article-title":"Automatic Classification of Graphs by Symbolic Histograms, GRC\n\u201907, IEEE Computer Society","author":"Del Vescovo G","year":"2007","unstructured":"Del VescovoGRizziA2007Automatic Classification of Graphs by Symbolic Histograms, GRC \u201907, IEEE Computer SocietyIn Proceedings of the 2007 IEEE International Conference on Granular Computing410416ISBN 0-7695-3032-X","journal-title":"In Proceedings of the 2007 IEEE International Conference on Granular Computing"},{"key":"e_1_3_1_9_1","doi-asserted-by":"publisher","DOI":"10.1109\/GrC.2007.141"},{"key":"e_1_3_1_10_1","doi-asserted-by":"publisher","DOI":"10.1126\/science.1219021"},{"key":"e_1_3_1_11_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.patrec.2011.04.019"},{"key":"e_1_3_1_12_1","doi-asserted-by":"publisher","DOI":"10.1063\/1.881414"},{"key":"e_1_3_1_13_1","doi-asserted-by":"publisher","DOI":"10.1109\/72.846747"},{"issue":"28","key":"e_1_3_1_14_1","first-page":"1522","article-title":"Nonlinear signal analysis methods in the elucidation of protein sequence\u2014 structure relationships","volume":"33","author":"Giuliani A","year":"2002","unstructured":"GiulianiABenigniRZbilutJPWebberCLJrSirabellaPColosimoA2002Nonlinear signal analysis methods in the elucidation of protein sequence\u2014 structure relationshipsChem Inform332815222667ISSN 1522-2667","journal-title":"Chem Inform"},{"key":"e_1_3_1_15_1","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2002.1028355"},{"issue":"1","key":"e_1_3_1_16_1","first-page":"1041","article-title":"Multidimensional sequence classification based on fuzzy distances and discriminant analysis","volume":"99","author":"Iosifidis A","year":"2012","unstructured":"IosifidisATefasAPitasI2012Multidimensional sequence classification based on fuzzy distances and discriminant analysisIEEE Transactions on Knowledge and Data Engineering99(PrePrints)110414347","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"key":"e_1_3_1_17_1","doi-asserted-by":"publisher","DOI":"10.1109\/34.862197"},{"key":"e_1_3_1_18_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2008.110"},{"key":"e_1_3_1_19_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10044-012-0284-8"},{"key":"e_1_3_1_20_1","first-page":"186","article-title":"Graph recognition by seriation and frequent substructures mining","volume":"1","author":"Livi L","year":"2012","unstructured":"LiviLDel VescovoGRizziA2012Graph recognition by seriation and frequent substructures miningIn Proceedings of the First International Conference on Pattern Recognition Applications and Methods1186191ISBN 978-989-8425-98-0","journal-title":"In Proceedings of the First International Conference on Pattern Recognition Applications and Methods"},{"key":"e_1_3_1_21_1","first-page":"1646","article-title":"Dissimilarity space embedding of labeled graphs by a clustering-based compression procedure","author":"Livi L","year":"2013","unstructured":"LiviLBianchiFMRizziASadeghianA2013Dissimilarity space embedding of labeled graphs by a clustering-based compression procedureIn Proceedings of the 2013 International Joint Conference on Neural Networks16461653ISBN 978-1-4673-6129-3","journal-title":"In Proceedings of the 2013 International Joint Conference on Neural Networks"},{"key":"e_1_3_1_22_1","first-page":"79","article-title":"Combining graph seriation and substructures mining for graph recognition","author":"Livi L","year":"2013","unstructured":"LiviLDel VescovoGRizziA2013Combining graph seriation and substructures mining for graph recognitionPattern Recognition - Applications and Methods, volume 204 of Advances in Intelligent and Soft ComputingLatorre CarmonaPS\u00e1nchezJSFredALN7991Springer Berlin HeidelbergISBN 978-3-642-36529-4","journal-title":"Pattern Recognition - Applications and Methods, volume 204 of Advances in Intelligent and Soft Computing"},{"key":"e_1_3_1_23_1","doi-asserted-by":"crossref","unstructured":"LiviLTahayoriHSadeghianARizziA2013Aggregating -planes for type-2 fuzzy set matching. In Joint IFSA World Congress and NAFIPS Annual Meeting (IFSA\/NAFIPS)860865","DOI":"10.1109\/IFSA-NAFIPS.2013.6608513"},{"key":"e_1_3_1_24_1","article-title":"Building pattern recognition applications with the SPARE library","author":"Livi L","year":"2014","unstructured":"LiviLDel VescovoGRizziAFrattale MascioliFM2014Building pattern recognition applications with the SPARE libraryArXiv preprint arXiv:1410.5263","journal-title":"ArXiv preprint arXiv:1410.5263"},{"key":"e_1_3_1_25_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2014.01.005"},{"key":"e_1_3_1_26_1","article-title":"Designing labeled graph classifiers by exploiting the R\u00e9nyi entropy of the dissimilarity representation","author":"Livi L","year":"2014","unstructured":"LiviLRizziASadeghianA2014Designing labeled graph classifiers by exploiting the R\u00e9nyi entropy of the dissimilarity representationArXiv preprint arXiv:1408.5286","journal-title":"ArXiv preprint arXiv:1408.5286"},{"key":"e_1_3_1_27_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2013.12.020"},{"key":"e_1_3_1_28_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2013.03.020"},{"key":"e_1_3_1_29_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2014.04.017"},{"key":"e_1_3_1_30_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2014.04.003"},{"key":"e_1_3_1_31_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00500-014-1246-4"},{"key":"e_1_3_1_32_1","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.0811922106"},{"key":"e_1_3_1_33_1","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1201380109"},{"key":"e_1_3_1_34_1","first-page":"1","article-title":"Human-centric analysis and interpretation of time series: A perspective of granular computing","author":"Pedrycz W","year":"2014","unstructured":"PedryczWLuWLiuXWangWWangL2014Human-centric analysis and interpretation of time series: A perspective of granular computingSoft Computing15ISSN 1432-7643","journal-title":"Soft Computing"},{"key":"e_1_3_1_35_1","doi-asserted-by":"crossref","unstructured":"Pr\u00edncipeJC2010Information Science and StatisticsInformation Theoretic Learning: Renyi\u2019s Entropy and Kernel PerspectivesSpringerISBN 9781441915696","DOI":"10.1007\/978-1-4419-1570-2"},{"key":"e_1_3_1_36_1","doi-asserted-by":"crossref","unstructured":"RiesenKBunkeH2010Series in Machine Perception and Artificial IntelligenceGraph Classification and Clustering Based on Vector Space EmbeddingWorld Scientific Pub Co IncISBN 9789814304719","DOI":"10.1142\/7731"},{"key":"e_1_3_1_37_1","doi-asserted-by":"publisher","DOI":"10.1109\/72.991426"},{"key":"e_1_3_1_38_1","first-page":"2268","article-title":"A new granular computing approach for sequences representation and classification","author":"Rizzi A","year":"2012","unstructured":"RizziADel VescovoGLiviLFrattale MascioliFM2012A new granular computing approach for sequences representation and classificationIn Proceedings of the 2012 International Joint Conference on Neural Networks22682275ISBN 978-1-4673-1489-3","journal-title":"In Proceedings of the 2012 International Joint Conference on Neural Networks"},{"key":"e_1_3_1_39_1","doi-asserted-by":"publisher","DOI":"10.1109\/IFSA-NAFIPS.2013.6608514"},{"key":"e_1_3_1_40_1","first-page":"2397","article-title":"A dissimilarity-based classifier for generalized sequences by a Granular Computing approach","author":"Rizzi A","year":"2013","unstructured":"RizziAPossematoFLiviLSebastianiAGiulianiAFrattale MascioliFM2013A dissimilarity-based classifier for generalized sequences by a Granular Computing approachIn Proceedings of the 2013 International Joint Conference on Neural Networks23972404ISBN 978-1-4673-6129-3","journal-title":"In Proceedings of the 2013 International Joint Conference on Neural Networks"},{"key":"e_1_3_1_41_1","first-page":"1022","article-title":"Nonlinear neuro-fuzzy prediction: methodology, design and applications","author":"Sadeghian A","year":"2001","unstructured":"SadeghianA2001Nonlinear neuro-fuzzy prediction: methodology, design and applicationsIn The 10th IEEE International Conference on Fuzzy Systems10221026","journal-title":"In The 10th IEEE International Conference on Fuzzy Systems"},{"key":"e_1_3_1_42_1","first-page":"1","article-title":"Prediction of protein solubility in E. coli","author":"Samak T","year":"2012","unstructured":"SamakTGunterDWangZ2012Prediction of protein solubility in E. coliIn 2012 IEEE 8th International Conference on E-Science (e-Science)18","journal-title":"In 2012 IEEE 8th International Conference on E-Science (e-Science)"},{"key":"e_1_3_1_43_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2013.09.014"},{"key":"e_1_3_1_44_1","doi-asserted-by":"publisher","DOI":"10.1126\/science.284.5415.822"},{"key":"e_1_3_1_45_1","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btl623"},{"key":"e_1_3_1_46_1","doi-asserted-by":"publisher","DOI":"10.1109\/34.57669"},{"key":"e_1_3_1_47_1","doi-asserted-by":"publisher","DOI":"10.1126\/science.271.5255.1493"},{"key":"e_1_3_1_48_1","doi-asserted-by":"publisher","DOI":"10.1049\/el.2012.3431"},{"key":"e_1_3_1_49_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2013.08.064"},{"key":"e_1_3_1_50_1","doi-asserted-by":"publisher","DOI":"10.1145\/1882471.1882478"}],"container-title":["Journal of Intelligent &amp; Fuzzy Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.3233\/IFS-151550","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/full-xml\/10.3233\/IFS-151550","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.3233\/IFS-151550","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,10]],"date-time":"2026-02-10T08:28:43Z","timestamp":1770712123000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/10.3233\/IFS-151550"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015,8,10]]},"references-count":49,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2015,8,10]]}},"alternative-id":["10.3233\/IFS-151550"],"URL":"https:\/\/doi.org\/10.3233\/ifs-151550","relation":{},"ISSN":["1064-1246","1875-8967"],"issn-type":[{"value":"1064-1246","type":"print"},{"value":"1875-8967","type":"electronic"}],"subject":[],"published":{"date-parts":[[2015,8,10]]}}}