{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,27]],"date-time":"2026-02-27T04:29:23Z","timestamp":1772166563375,"version":"3.50.1"},"reference-count":49,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2023,9,9]],"date-time":"2023-09-09T00:00:00Z","timestamp":1694217600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2023,9,9]],"date-time":"2023-09-09T00:00:00Z","timestamp":1694217600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"name":"NKFI","award":["K-128136"],"award-info":[{"award-number":["K-128136"]}]},{"DOI":"10.13039\/501100009934","name":"E\u00f6tv\u00f6s Lor\u00e1nd University","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100009934","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Cheminform"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>We developed a new seriation merit function for enhancing the visual information of data matrices. A local similarity matrix is calculated, where the average similarity of neighbouring objects is calculated in a limited variable space and a global function is constructed to maximize the local similarities and cluster them into patches by simple row and column ordering. The method identifies data clusters in a powerful way, if the similarity of objects is caused by some variables and these variables differ for the distinct clusters. The method can be used in the presence of missing data and also on more than two-dimensional data arrays. We show the feasibility of the method on different data sets: on QSAR, chemical, material science, food science, cheminformatics and environmental data in two- and three-dimensional cases. The method can be used during the development and the interpretation of artificial neural network models by seriating different features of the models. It helps to identify interpretable models by elucidating clusters of objects, variables and hidden layer neurons.<\/jats:p>\n                  <jats:p>\n                    <jats:bold>Graphical Abstract<\/jats:bold>\n                  <\/jats:p>","DOI":"10.1186\/s13321-023-00757-1","type":"journal-article","created":{"date-parts":[[2023,9,9]],"date-time":"2023-09-09T06:02:24Z","timestamp":1694239344000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Patch seriation to visualize data and model parameters"],"prefix":"10.1186","volume":"15","author":[{"given":"Rita","family":"Lasfar","sequence":"first","affiliation":[]},{"given":"Gergely","family":"T\u00f3th","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,9,9]]},"reference":[{"key":"757_CR1","first-page":"295","volume":"29","author":"WM Petrie","year":"1899","unstructured":"Petrie WM (1899) Flinders sequences in prehistoric remains. J Anthropol Inst Great Br Irel 29:295\u2013301","journal-title":"J Anthropol Inst Great Br Irel"},{"key":"757_CR2","doi-asserted-by":"publisher","DOI":"10.1515\/9783110854688","volume-title":"Graphics and graphic information processing","author":"J Bertin","year":"1981","unstructured":"Bertin J (1981) Graphics and graphic information processing. Walter de Gruyter, Berlin, Boston. https:\/\/doi.org\/10.1515\/9783110854688"},{"key":"757_CR3","doi-asserted-by":"publisher","first-page":"79","DOI":"10.1111\/j.1502-3931.1988.tb01756.x","volume":"21","author":"JC Brower","year":"1988","unstructured":"Brower JC, Kile KM (1988) Seriation of an original data matrix as applied to palaeoecology. Lethaia 21:79\u201393. https:\/\/doi.org\/10.1111\/j.1502-3931.1988.tb01756.x","journal-title":"Lethaia"},{"key":"757_CR4","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1142\/9789812832153_0002","volume-title":"Clustering and classification","author":"P Arabie","year":"1996","unstructured":"Arabie P, Hubert LJ (1996) An overview of combinatorial data analysis. In: Arabie P, Hubert LJ, De Soete G (eds) Clustering and classification. World Scientific, River Edge, pp 5\u201363"},{"key":"757_CR5","doi-asserted-by":"publisher","first-page":"70","DOI":"10.1002\/sam.10071","volume":"3","author":"I Liiv","year":"2010","unstructured":"Liiv I (2010) Seriation and Matrix Reordering Methods: an historical overview. Stat Anal Data Min 3:70\u201391. https:\/\/doi.org\/10.1002\/sam.10071","journal-title":"Stat Anal Data Min"},{"issue":"1","key":"757_CR6","doi-asserted-by":"publisher","first-page":"141","DOI":"10.1016\/j.jpba.2005.11.007","volume":"41","author":"E Van Gyseghem","year":"2006","unstructured":"Van Gyseghem E, Dejaegher B, Put R, Forlay-Frick P, Elkihel A, Daszykowski M, H\u00e9berger K, Massart DL, Heyden YV (2006) Evaluation of chemometric techniques to select orthogonal chromatographic systems. J Pharm Biomed Anal 41(1):141\u2013151. https:\/\/doi.org\/10.1016\/j.jpba.2005.11.007","journal-title":"J Pharm Biomed Anal"},{"key":"757_CR7","doi-asserted-by":"publisher","first-page":"14","DOI":"10.1002\/cem.1267","volume":"24","author":"G T\u00f3th","year":"2010","unstructured":"T\u00f3th G, Szepesv\u00e1ry P (2010) A diagonal measure and a local distance matrix to display relations between objects and variables P. J Chemometr 24:14\u201321. https:\/\/doi.org\/10.1002\/cem.1267","journal-title":"J Chemometr"},{"key":"757_CR8","doi-asserted-by":"publisher","first-page":"188","DOI":"10.1002\/cem.2786","volume":"30","author":"TD Sekuli\u0107a","year":"2016","unstructured":"Sekuli\u0107a TD, Bo\u017einb B, Smoli\u0144skic A (2016) Chemometric study of biological activities of 10 aromatic Lamiaceae species\u2019 essential oils. J Chemometr 30:188\u2013196. https:\/\/doi.org\/10.1002\/cem.2786","journal-title":"J Chemometr"},{"key":"757_CR9","doi-asserted-by":"publisher","first-page":"209","DOI":"10.12700\/APH.13.2.2016.2.12","volume":"13","author":"C Pigler","year":"2016","unstructured":"Pigler C, Fogarassy-Vathy \u00c1, Abonyi J (2016) Scalable co-clustering using a crossing minimization \u2013 application to production flow analysis. Act Polytech Hung 13:209\u2013228. https:\/\/doi.org\/10.12700\/APH.13.2.2016.2.12","journal-title":"Act Polytech Hung"},{"key":"757_CR10","first-page":"1","volume":"4","author":"\u00d8 Hammer","year":"2001","unstructured":"Hammer \u00d8, Harper D, Ryan P (2001) PAST: Paleontological Statistics Software Package for Education and Data Analysis. Palaeontologia Electronica 4:1\u20139","journal-title":"Palaeontologia Electronica"},{"issue":"3","key":"757_CR11","doi-asserted-by":"publisher","first-page":"1","DOI":"10.18637\/jss.v025.i03","volume":"25","author":"M Hahsler","year":"2008","unstructured":"Hahsler M, Hornik K, Buchta C (2008) Getting things in Order: an introduction to the R Package seriation. J Stat Soft 25(3):1\u201334. https:\/\/doi.org\/10.18637\/jss.v025.i03","journal-title":"J Stat Soft"},{"key":"757_CR12","unstructured":"R Core Team (2013) R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. http:\/\/www.R-project.org\/\u00a0. Accessed 21 Mar 2023"},{"key":"757_CR13","first-page":"2825","volume":"12","author":"F Pedregosa","year":"2011","unstructured":"Pedregosa F (2011) Scikit-learn: machine learning in Python. J Mach Learn Res 12:2825\u20132830","journal-title":"J Mach Learn Res"},{"key":"757_CR14","doi-asserted-by":"publisher","first-page":"123","DOI":"10.1080\/01621459.1972.10481214","volume":"67","author":"JA Hartigan","year":"1972","unstructured":"Hartigan JA (1972) Direct clustering of a data matrix. J Am Stat Assoc 67:123\u2013129","journal-title":"J Am Stat Assoc"},{"key":"757_CR15","unstructured":"Cheng Y, Church GM (2000) Biclustering of expression data, Proceedings. International Conference on Intelligent Systems for Molecular Biology 8:93\u2013103"},{"key":"757_CR16","doi-asserted-by":"publisher","first-page":"260","DOI":"10.1002\/wcms.23","volume":"1","author":"D Stumpfe","year":"2011","unstructured":"Stumpfe D, Bajorath J (2011) Similarity searching. WIREs Comput Mol Sci 1:260\u2013282. https:\/\/doi.org\/10.1002\/wcms.23","journal-title":"WIREs Comput Mol Sci"},{"key":"757_CR17","doi-asserted-by":"publisher","DOI":"10.1525\/9780520943742","volume-title":"Sequence alignment: methods, models, concepts, and strategies","author":"MS Rosenberg","year":"2009","unstructured":"Rosenberg MS (2009) Sequence alignment: methods, models, concepts, and strategies. University of California Press, Berkeley, CA"},{"key":"757_CR18","first-page":"241","volume-title":"Computer applications and quantitative methods in Archaeology 1989","author":"MN Leese","year":"1989","unstructured":"Leese MN, Hughes MJ, Stopford J (1989) The chemical composition of tiles from Bordesley: a case study in data treatment. In: Rahtz S (ed) Computer applications and quantitative methods in Archaeology 1989. BAR International Series, Oxford, pp 241\u2013249"},{"key":"757_CR19","first-page":"557","volume":"7","author":"HG Bartel","year":"1990","unstructured":"Bartel HG (1990) Seriation to describe some aspects of generalized evolution and its application in chemical informatics. Syst Anal Modelling Simul 7:557\u2013565","journal-title":"Syst Anal Modelling Simul"},{"key":"757_CR20","doi-asserted-by":"publisher","first-page":"262","DOI":"10.1016\/j.chemolab.2007.03.004","volume":"87","author":"M Forina","year":"2007","unstructured":"Forina M, Lanteri S, Casale M, Cerrato Oliveros M (2007) A new algorithm for seriation and its use in similarity dendrograms. Chemometr Intell Lab Syst 87:262\u2013274. https:\/\/doi.org\/10.1016\/j.chemolab.2007.03.004","journal-title":"Chemometr Intell Lab Syst"},{"issue":"3\u20134","key":"757_CR21","doi-asserted-by":"publisher","first-page":"e2995","DOI":"10.1002\/cem.2995","volume":"32","author":"G T\u00f3th","year":"2018","unstructured":"T\u00f3th G, Amariamir S (2018) Seriation, the method out of a chemist\u2019s mind. J Chemom 32(3\u20134):e2995. https:\/\/doi.org\/10.1002\/cem.2995","journal-title":"J Chemom"},{"key":"757_CR22","first-page":"357","volume":"29","author":"E Makinen","year":"2005","unstructured":"Makinen E, Siirtola H (2005) The barycenter heuristic and the reorderable matrix. Informatica 29:357\u2013363","journal-title":"Informatica"},{"key":"757_CR23","doi-asserted-by":"publisher","first-page":"7","DOI":"10.1002\/jgt.3190010105","volume":"1","author":"P Turan","year":"1977","unstructured":"Turan P (1977) A note of welcome J. Graph Theory 1:7\u20139","journal-title":"Graph Theory"},{"key":"757_CR24","unstructured":"Molnar C (2022) Interpretable machine learning. A guide for making black box models explainable, 2nd ed. Munich, Germany.\u00a0https:\/\/christophm.github.io\/interpretable-ml-book\/https:\/\/christophm.github.io\/interpretable-ml-book\/. Accessed 7 June 2022"},{"key":"757_CR25","doi-asserted-by":"publisher","first-page":"41","DOI":"10.1198\/000313005X22770","volume":"59","author":"S Nierman","year":"2005","unstructured":"Nierman S (2005) Optimizing the ordering of tables with evolutionary computation. Am Stat 59:41\u201346","journal-title":"Am Stat"},{"key":"757_CR26","doi-asserted-by":"publisher","first-page":"293","DOI":"10.2307\/276978","volume":"16","author":"WS Robinson","year":"1951","unstructured":"Robinson WS (1951) A method for chronologically ordering archeological deposits. Am Antiq 16:293\u2013301","journal-title":"Am Antiq"},{"key":"757_CR27","unstructured":"RGL package https (2023) :\/\/CRAN.R-project.org\/package=rgl last accessed 26th"},{"key":"757_CR28","doi-asserted-by":"publisher","first-page":"2200072","DOI":"10.1002\/minf.202200072","volume":"41","author":"P Kir\u00e1ly","year":"2022","unstructured":"Kir\u00e1ly P, Kiss R, Kov\u00e1cs D, Ballaj A, T\u00f3th G (2022) The relevance of goodness-of-fit, robustness and prediction validation categories of OECD-QSAR principles with respect to sample size and model type. Mol Inf 41:2200072. https:\/\/doi.org\/10.1002\/minf.202200072","journal-title":"Mol Inf"},{"key":"757_CR29","doi-asserted-by":"publisher","first-page":"32","DOI":"10.1186\/s13321-015-0082-6","volume":"7","author":"V Ruusmann","year":"2015","unstructured":"Ruusmann V, Sild S, Maran U (2015) QSAR DataBank repository: open and linked qualitative and quantitative structure\u2013activity relationship models. J Cheminf 7:32. https:\/\/doi.org\/10.1186\/s13321-015-0082-6. http:\/\/www.qsardb.org","journal-title":"J Cheminf"},{"key":"757_CR30","unstructured":"Kaggle Inc. http:\/\/kaggle.com Accessed 2018 Nov\u20132023 Apr"},{"key":"757_CR31","unstructured":"Dua D, Graff C, Machine Learning UCI, Repository (2019)\u00a0http:\/\/archive.ics.uci.edu\/ml. Irvine, CA: University of California, School of Information and Computer Science"},{"key":"757_CR32","doi-asserted-by":"publisher","unstructured":"Toth G (2023) Benchmark datasets for seriation and patch seriation code. Mendeley Data V1. https:\/\/doi.org\/10.17632\/b96s5bcfc2.1","DOI":"10.17632\/b96s5bcfc2.1"},{"key":"757_CR33","unstructured":"Hungarian Air Quality Network, later it has been transported to http:\/\/legszennyezettseg.met.hu\/. Accessed at June 2017"},{"key":"757_CR34","first-page":"491","volume":"39","author":"J Tetteh","year":"1999","unstructured":"Tetteh J, Suzuki T, Metcalfe E, Howells S (1999) Quantitative structure-property relationships for the estimation of boiling point and flash point using a radial basis function neural network. J Chem Inf Model 39:491\u2013507","journal-title":"J Chem Inf Model"},{"key":"757_CR35","doi-asserted-by":"publisher","first-page":"501","DOI":"10.1080\/1062936X.2016.1196388","volume":"27","author":"V Drgan","year":"2016","unstructured":"Drgan V, Zuperl S, Vracko M, Como F, Novic M (2016) Robust modelling of acute toxicity towards fathead minnow (Pimephales promelas) using counter-propagation artificial neural networks and genetic algorithm. SAR QSAR Environ Res 27:501\u2013519. https:\/\/doi.org\/10.1080\/1062936X.2016.1196388","journal-title":"SAR QSAR Environ Res"},{"key":"757_CR36","doi-asserted-by":"publisher","first-page":"3900","DOI":"10.15152\/QDB.123","volume":"25","author":"DA Saldana","year":"2011","unstructured":"Saldana DA, Starck L, Mougin P, Rousseau B, Pidol L, Jeuland N, Creton B (2011) Flash point and cetane number predictions for fuel compounds using quantitative structure property relationship (QSPR) Methods. Energy Fuels 25:3900\u20133908. https:\/\/doi.org\/10.15152\/QDB.123","journal-title":"Energy Fuels"},{"key":"757_CR37","doi-asserted-by":"publisher","unstructured":"Salma I (2023) Daily air pollution and meteorological data Budapest, 2007. Mendeley Data, V1, https:\/\/doi.org\/10.17632\/2mmwv3j4ms.1","DOI":"10.17632\/2mmwv3j4ms.1"},{"key":"757_CR38","doi-asserted-by":"publisher","first-page":"5123","DOI":"10.1016\/j.ceramint.2015.12.030","volume":"42","author":"Z He","year":"2016","unstructured":"He Z, Zhang M, Zhang H (2016) Data-driven research on chemical features of Jingdezhen and Longquan celadon by energy dispersive X-ray fluorescence. Ceram Int 42:5123\u20135129. https:\/\/doi.org\/10.1016\/j.ceramint.2015.12.030","journal-title":"Ceram Int"},{"key":"757_CR39","volume-title":"Glass identification dataset, central research establishment","author":"B German","year":"1987","unstructured":"German B (1987) Glass identification dataset, central research establishment. Home Office Forensic Science Service, Aldermaston"},{"key":"757_CR40","unstructured":"Wine recognition dataset, Kaggle Inc (2017) https:\/\/www.kaggle.com\/brynja\/wineuci March-2023 Apr"},{"key":"757_CR41","doi-asserted-by":"publisher","DOI":"10.1016\/j.cdc.2016.12.002","author":"DE Arthur","year":"2017","unstructured":"Arthur DE, Uzairu A, Mamza P, Stephen AE, Gideon Shallangwa GA (2017) Quantitative structure-activity and toxicity relationship study of CCRF\u2010CEM and RPMI 8402 cell line apoptosis with some anticancer compounds. Chem Data Coll. https:\/\/doi.org\/10.1016\/j.cdc.2016.12.002. 7\u20108:8\u201050","journal-title":"Chem Data Coll"},{"key":"757_CR42","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.cdc.2016.03.001","volume":"2","author":"R Hariprasath","year":"2016","unstructured":"Hariprasath R, Jose MT, Vijayalakshmi I, Rajesh A (2016) Determination of natural radioactivity and radiological hazards of sediment sands in Tiruchirappalli district, Tamil Nadu, India. Chem Data Coll 2:1\u20139. https:\/\/doi.org\/10.1016\/j.cdc.2016.03.001","journal-title":"Chem Data Coll"},{"key":"757_CR43","doi-asserted-by":"publisher","unstructured":"Lang A (2012) Data for: Abraham descriptor A. QsarDB repository, QDB.100. https:\/\/doi.org\/10.15152\/QDB.100","DOI":"10.15152\/QDB.100"},{"issue":"1","key":"757_CR44","doi-asserted-by":"publisher","first-page":"2","DOI":"10.1186\/2050-7445-1-2","volume":"1","author":"A R\u00e1cz","year":"2013","unstructured":"R\u00e1cz A, H\u00e9berger K, Rajk\u00f3 R, Elek J (2013) Classification of hungarian medieval silver coins using X-ray fluorescent spectroscopy and multivariate data analysis. Herit Sci 1(1):2. https:\/\/doi.org\/10.1186\/2050-7445-1-2","journal-title":"Herit Sci"},{"key":"757_CR45","doi-asserted-by":"publisher","first-page":"287","DOI":"10.1002\/cem.2601","volume":"28","author":"HJ Christie Olav","year":"2014","unstructured":"Christie Olav HJ, R\u00e1cz A, Elek J, H\u00e9berger K (2014) Classification and unscrambling a class-inside\u2010class situation by object target rotation: hungarian silver coins of the \u00c1rp\u00e1d Dynasty, 997\u20101301 AD. J Chemometr 28:287\u2013292. https:\/\/doi.org\/10.1002\/cem.2601","journal-title":"J Chemometr"},{"key":"757_CR46","doi-asserted-by":"publisher","unstructured":"R\u00e1cz A, H\u00e9berger K, Rajko R, Elek J (2023) Composition data of 257 hungarian medieval silver coins. Mendeley Data V1. https:\/\/doi.org\/10.17632\/kbjrfkvcs3.1","DOI":"10.17632\/kbjrfkvcs3.1"},{"key":"757_CR47","unstructured":"Juh\u00e1sz G (2015) Reduction of a biodiesel combustion reaction mechanism. BSc thesis Budapest: Institute of Chemistry, Department of Physical Chemistry, E\u00f6tv\u00f6s Lor\u00e1nd University, Budapest"},{"key":"757_CR48","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-28954-6_18","volume-title":"Explainable AI: interpreting, explaining and visualizing deep learning. Lecture notes in Computer Science","author":"K Preuer","year":"2019","unstructured":"Preuer K, Klambauer G, Rippmann F, Hochreiter S, Unterthiner T (2019) Interpretable deep learning in drug discovery. In: Samek W, Montavon G, Vedaldi A, Hansen L, M\u00fcller KR (eds) Explainable AI: interpreting, explaining and visualizing deep learning. Lecture notes in Computer Science. Springer, Cham. https:\/\/doi.org\/10.1007\/978-3-030-28954-6_18"},{"key":"757_CR49","doi-asserted-by":"publisher","first-page":"573","DOI":"10.1038\/s42256-020-00236-4","volume":"2","author":"J Jim\u00e9nez-Luna","year":"2020","unstructured":"Jim\u00e9nez-Luna J, Grisoni F, Schneider G (2020) Drug discovery with explainable artificial intelligence. Nat Mach Intell 2:573\u2013584. https:\/\/doi.org\/10.1038\/s42256-020-00236-4","journal-title":"Nat Mach Intell"}],"container-title":["Journal of Cheminformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s13321-023-00757-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s13321-023-00757-1\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s13321-023-00757-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,11,19]],"date-time":"2023-11-19T07:39:52Z","timestamp":1700379592000},"score":1,"resource":{"primary":{"URL":"https:\/\/jcheminf.biomedcentral.com\/articles\/10.1186\/s13321-023-00757-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,9,9]]},"references-count":49,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2023,12]]}},"alternative-id":["757"],"URL":"https:\/\/doi.org\/10.1186\/s13321-023-00757-1","relation":{"has-preprint":[{"id-type":"doi","id":"10.21203\/rs.3.rs-2780120\/v1","asserted-by":"object"}]},"ISSN":["1758-2946"],"issn-type":[{"value":"1758-2946","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,9,9]]},"assertion":[{"value":"5 April 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"31 August 2023","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"9 September 2023","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Not applicable.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"We give our consent for the publication of identifiable details, which can include details within the text and figures to be published in the above Journal and Article.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The authors declare that they have no competing interests.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"78"}}