{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,15]],"date-time":"2026-04-15T21:26:33Z","timestamp":1776288393469,"version":"3.50.1"},"reference-count":24,"publisher":"Oxford University Press (OUP)","issue":"14","license":[{"start":{"date-parts":[[2019,7,8]],"date-time":"2019-07-08T00:00:00Z","timestamp":1562544000000},"content-version":"vor","delay-in-days":7,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"name":"NSF-BIO\/DBI","award":["1759736"],"award-info":[{"award-number":["1759736"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019,7,15]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Motivation<\/jats:title>\n                  <jats:p>Mass spectrometry imaging (MSI) characterizes the spatial distribution of ions in complex biological samples such as tissues. Since many tissues have complex morphology, treatments and conditions often affect the spatial distribution of the ions in morphology-specific ways. Evaluating the selectivity and the specificity of ion localization and regulation across morphology types is biologically important. However, MSI lacks algorithms for segmenting images at both single-ion and spatial resolution.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>This article contributes spatial-Dirichlet Gaussian mixture model (DGMM), an algorithm and a workflow for the analyses of MSI experiments, that detects components of single-ion images with homogeneous spatial composition. The approach extends DGMMs to account for the spatial structure of MSI. Evaluations on simulated and experimental datasets with diverse MSI workflows demonstrated that spatial-DGMM accurately segments ion images, and can distinguish ions with homogeneous and heterogeneous spatial distribution. We also demonstrated that the extracted spatial information is useful for downstream analyses, such as detecting morphology-specific ions, finding groups of ions with similar spatial patterns, and detecting changes in chemical composition of tissues between conditions.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Availability and implementation<\/jats:title>\n                  <jats:p>The data and code are available at https:\/\/github.com\/Vitek-Lab\/IonSpattern.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Supplementary information<\/jats:title>\n                  <jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btz345","type":"journal-article","created":{"date-parts":[[2019,5,9]],"date-time":"2019-05-09T19:21:53Z","timestamp":1557429713000},"page":"i208-i217","source":"Crossref","is-referenced-by-count":14,"title":["Unsupervised segmentation of mass spectrometric ion images characterizes morphology of tissues"],"prefix":"10.1093","volume":"35","author":[{"given":"Dan","family":"Guo","sequence":"first","affiliation":[{"name":"Khoury College of Computer Sciences, Northeastern University, Boston, MA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kylie","family":"Bemis","sequence":"additional","affiliation":[{"name":"Khoury College of Computer Sciences, Northeastern University, Boston, MA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Catherine","family":"Rawlins","sequence":"additional","affiliation":[{"name":"Department of Chemistry and Chemical Biology, Northeastern University, Boston, MA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jeffrey","family":"Agar","sequence":"additional","affiliation":[{"name":"Department of Chemistry and Chemical Biology, Northeastern University, Boston, MA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Olga","family":"Vitek","sequence":"additional","affiliation":[{"name":"Khoury College of Computer Sciences, Northeastern University, Boston, MA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2019,7,5]]},"reference":[{"key":"2023062712364458800_btz345-B1","doi-asserted-by":"crossref","first-page":"422.","DOI":"10.1038\/labinvest.2014.156","article-title":"MALDI imaging mass spectrometry: current frontiers and perspectives in pathology research and practice","volume":"95","author":"Aichler","year":"2015","journal-title":"Lab. Invest"},{"key":"2023062712364458800_btz345-B2","doi-asserted-by":"crossref","first-page":"6535.","DOI":"10.1021\/pr100734z","article-title":"Spatial segmentation of imaging mass spectrometry data with edge-preserving image denoising and clustering","volume":"9","author":"Alexandrov","year":"2010","journal-title":"J.\u00a0Proteome Res"},{"key":"2023062712364458800_btz345-B3","doi-asserted-by":"crossref","first-page":"i230.","DOI":"10.1093\/bioinformatics\/btr246","article-title":"Efficient spatial segmentation of large imaging mass spectrometry datasets with spatially aware clustering","volume":"27","author":"Alexandrov","year":"2011","journal-title":"Bioinformatics"},{"key":"2023062712364458800_btz345-B4","doi-asserted-by":"crossref","first-page":"2418.","DOI":"10.1093\/bioinformatics\/btv146","article-title":"Cardinal: an R package for statistical analysis of mass spectrometry-based imaging experiments","volume":"31","author":"Bemis","year":"2015","journal-title":"Bioinformatics"},{"key":"2023062712364458800_btz345-B5","doi-asserted-by":"crossref","first-page":"1761","DOI":"10.1074\/mcp.O115.053918","article-title":"Probabilistic segmentation of mass spectrometry images helps select important ions and characterize confidence in the resulting segments","volume":"15","author":"Bemis","year":"2016","journal-title":"Mol. Cell. Proteomics"},{"key":"2023062712364458800_btz345-B6","doi-asserted-by":"crossref","first-page":"49.","DOI":"10.1016\/j.ijms.2018.07.006","article-title":"Statistical detection of differentially abundant ions in mass spectrometry-based imaging experiments with complex designs","volume":"437","author":"Bemis","year":"2019","journal-title":"Int. J. Mass Spectrom"},{"key":"2023062712364458800_btz345-B7","doi-asserted-by":"crossref","first-page":"494.","DOI":"10.1109\/TNN.2004.841773","article-title":"A spatially constrained mixture model for image segmentation","volume":"16","author":"Blekas","year":"2005","journal-title":"IEEE Trans. Neural Netw"},{"key":"2023062712364458800_btz345-B8","doi-asserted-by":"crossref","first-page":"149.","DOI":"10.1007\/s00216-011-5020-5","article-title":"Multivariate analyses for biomarkers hunting and validation through on-tissue bottom-up or in-source decay in MALDI-MSI: application to prostate cancer","volume":"401","author":"Bonnel","year":"2011","journal-title":"Anal. Bioanal. Chem"},{"key":"2023062712364458800_btz345-B9","doi-asserted-by":"crossref","first-page":"5871","DOI":"10.1021\/acs.analchem.6b00672","article-title":"Spatial autocorrelation in mass spectrometry imaging","volume":"88","author":"Cassese","year":"2016","journal-title":"Anal. Chem"},{"key":"2023062712364458800_btz345-B10","doi-asserted-by":"crossref","first-page":"806","DOI":"10.1038\/35097565","article-title":"From Charcot to Lou Gehrig: deciphering selective motor neuron death in ALS","volume":"2","author":"Cleveland","year":"2001","journal-title":"Nat. Rev. Neurosci"},{"key":"2023062712364458800_btz345-B11","doi-asserted-by":"crossref","first-page":"2635.","DOI":"10.1007\/s13361-017-1784-y","article-title":"Automated morphological and morphometric analysis of mass spectrometry imaging data: application to biomarker discovery","volume":"28","author":"de Muller","year":"2017","journal-title":"J.\u00a0Am. Soc. Mass Spectrom"},{"key":"2023062712364458800_btz345-B12","doi-asserted-by":"crossref","first-page":"357.","DOI":"10.1074\/mcp.M116.065755","article-title":"Spatially-resolved top-down proteomics bridged to MALDI MS imaging reveals the molecular physiome of brain regions","volume":"17","author":"Delcourt","year":"2018","journal-title":"Mol. Cell. Proteomics"},{"key":"2023062712364458800_btz345-B13","doi-asserted-by":"crossref","first-page":"e24913.","DOI":"10.1371\/journal.pone.0024913","article-title":"Multiple statistical analysis techniques corroborate intratumor heterogeneity in imaging mass spectrometry datasets of myxofibrosarcoma","volume":"6","author":"Jones","year":"2011","journal-title":"PLoS One"},{"key":"2023062712364458800_btz345-B14","doi-asserted-by":"crossref","first-page":"4962.","DOI":"10.1016\/j.jprot.2012.06.014","article-title":"Imaging mass spectrometry statistical analysis","volume":"75","author":"Jones","year":"2012","journal-title":"J.\u00a0Proteomics"},{"key":"2023062712364458800_btz345-B15","doi-asserted-by":"crossref","first-page":"818.","DOI":"10.1016\/j.imavis.2011.09.001","article-title":"Dirichlet Gaussian mixture model: application to image segmentation","volume":"29","author":"Nguyen","year":"2011","journal-title":"Image Vis. Comput"},{"key":"2023062712364458800_btz345-B16","doi-asserted-by":"crossref","first-page":"2278.","DOI":"10.1109\/TIP.2010.2047903","article-title":"A Bayesian framework for image segmentation with spatially varying mixtures","volume":"19","author":"Nikou","year":"2010","journal-title":"IEEE Trans. Image Process"},{"key":"2023062712364458800_btz345-B17","doi-asserted-by":"crossref","first-page":"2309.","DOI":"10.1021\/cr3004295","article-title":"Analysis of tissue specimens by matrix-assisted laser desorption\/ionization imaging mass spectrometry in biological and clinical research","volume":"113","author":"Norris","year":"2013","journal-title":"Chem. Rev"},{"key":"2023062712364458800_btz345-B18","doi-asserted-by":"crossref","first-page":"13257.","DOI":"10.1021\/acs.analchem.8b01870","article-title":"Drug-homogeneity index in mass spectrometry imaging","volume":"90","author":"Prasad","year":"2018","journal-title":"Anal. Chem"},{"key":"2023062712364458800_btz345-B19","doi-asserted-by":"crossref","first-page":"281.","DOI":"10.1002\/mas.21527","article-title":"Signal preprocessing, multivariate analysis and software tools for MALDI-TOF mass spectrometry imaging for biological applications","volume":"37","author":"R\u00e0fols","year":"2018","journal-title":"Mass Spectrom. Rev"},{"key":"2023062712364458800_btz345-B20","doi-asserted-by":"crossref","first-page":"64.","DOI":"10.1021\/ac504543v","article-title":"Mass spectrometry imaging of biomolecular information","volume":"87","author":"Spengler","year":"2015","journal-title":"Anal. Chem"},{"key":"2023062712364458800_btz345-B21","first-page":"50","author":"Trede","year":"2012"},{"key":"2023062712364458800_btz345-B22","doi-asserted-by":"crossref","first-page":"209.","DOI":"10.1002\/jms.1876","article-title":"The evolving field of imaging mass spectrometry and its impact on future biological research","volume":"46","author":"Watrous","year":"2011","journal-title":"J.\u00a0Mass Spectrom"},{"key":"2023062712364458800_btz345-B23","doi-asserted-by":"crossref","first-page":"218.","DOI":"10.1002\/mas.21360","article-title":"Mass spectrometry imaging under ambient conditions","volume":"32","author":"Wu","year":"2013","journal-title":"Mass Spectrom. Rev"},{"key":"2023062712364458800_btz345-B24","first-page":"28.","article-title":"Improved adaptive gaussian mixture model for background subtraction","volume":"2","author":"Zivkovic","year":"2004","journal-title":"Pattern Recognit"}],"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/35\/14\/i208\/50721511\/bioinformatics_35_14_i208.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/35\/14\/i208\/50721511\/bioinformatics_35_14_i208.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,6,27]],"date-time":"2023-06-27T12:37:20Z","timestamp":1687869440000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/35\/14\/i208\/5529219"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,7]]},"references-count":24,"journal-issue":{"issue":"14","published-print":{"date-parts":[[2019,7,15]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/btz345","relation":{},"ISSN":["1367-4803","1367-4811"],"issn-type":[{"value":"1367-4803","type":"print"},{"value":"1367-4811","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2019,7]]},"published":{"date-parts":[[2019,7]]}}}