{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,3]],"date-time":"2026-03-03T07:45:50Z","timestamp":1772523950533,"version":"3.50.1"},"reference-count":53,"publisher":"Oxford University Press (OUP)","issue":"15","license":[{"start":{"date-parts":[[2022,6,24]],"date-time":"2022-06-24T00:00:00Z","timestamp":1656028800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Grohne-Stepp Endowment from the University of Colorado Cancer Center, NCI","award":["R01 CA129102"],"award-info":[{"award-number":["R01 CA129102"]}]},{"name":"Grohne-Stepp Endowment from the University of Colorado Cancer Center, NCI","award":["NSF DMS 1914937"],"award-info":[{"award-number":["NSF DMS 1914937"]}]},{"name":"Grohne-Stepp Endowment from the University of Colorado Cancer Center, NCI","award":["NCI R01 CA129102"],"award-info":[{"award-number":["NCI R01 CA129102"]}]},{"name":"Grohne-Stepp Endowment from the University of Colorado Cancer Center, NCI","award":["NSF DMS 1914937"],"award-info":[{"award-number":["NSF DMS 1914937"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,8,2]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Motivation<\/jats:title>\n                    <jats:p>Studying the interaction or co-expression of the proteins or markers in the tumor microenvironment of cancer subjects can be crucial in the assessment of risks, such as death or recurrence. In the conventional approach, the cells need to be declared positive or negative for a marker based on its intensity. For multiple markers, manual thresholds are required for all the markers, which can become cumbersome. The performance of the subsequent analysis relies heavily on this step and thus suffers from subjectivity and lacks robustness.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>We present a new method where different marker intensities are viewed as dependent random variables, and the mutual information (MI) between them is considered to be a metric of co-expression. Estimation of the joint density, as required in the traditional form of MI, becomes increasingly challenging as the number of markers increases. We consider an alternative formulation of MI which is conceptually similar but has an efficient estimation technique for which we develop a new generalization. With the proposed method, we analyzed a lung cancer dataset finding the co-expression of the markers, HLA-DR and CK to be associated with survival. We also analyzed a triple negative breast cancer dataset finding the co-expression of the immuno-regulatory proteins, PD1, PD-L1, Lag3 and IDO, to be associated with disease recurrence. We demonstrated the robustness of our method through different simulation studies.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Availability and implementation<\/jats:title>\n                    <jats:p>The associated R package can be found here, https:\/\/github.com\/sealx017\/MIAMI.<\/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\/btac414","type":"journal-article","created":{"date-parts":[[2022,6,24]],"date-time":"2022-06-24T09:31:16Z","timestamp":1656063076000},"page":"3818-3826","source":"Crossref","is-referenced-by-count":7,"title":["MIAMI: mutual information-based analysis of multiplex imaging data"],"prefix":"10.1093","volume":"38","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3268-610X","authenticated-orcid":false,"given":"Souvik","family":"Seal","sequence":"first","affiliation":[{"name":"Department of Biostatistics and Informatics, University of Colorado CU Anschutz Medical Campus , Aurora, CO 80045, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6618-1316","authenticated-orcid":false,"given":"Debashis","family":"Ghosh","sequence":"additional","affiliation":[{"name":"Department of Biostatistics and Informatics, University of Colorado CU Anschutz Medical Campus , Aurora, CO 80045, USA"}]}],"member":"286","published-online":{"date-parts":[[2022,6,24]]},"reference":[{"key":"2023041405360185000_","doi-asserted-by":"crossref","first-page":"163","DOI":"10.1038\/s43018-020-0026-6","article-title":"Imaging mass cytometry and multiplatform genomics define the phenogenomic landscape of breast cancer","volume":"1","author":"Ali","year":"2020","journal-title":"Nat. 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