{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,26]],"date-time":"2026-02-26T20:34:48Z","timestamp":1772138088678,"version":"3.50.1"},"reference-count":35,"publisher":"Oxford University Press (OUP)","issue":"21","license":[{"start":{"date-parts":[[2018,6,5]],"date-time":"2018-06-05T00:00:00Z","timestamp":1528156800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"funder":[{"name":"Sealy Center for Structural Biology and Molecular Biophysics"},{"name":"Institute for Human Infections and Immunity"},{"DOI":"10.13039\/100007865","name":"University of Texas Medical Branch","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100007865","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018,11,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Motivation<\/jats:title>\n                    <jats:p>Identification of complex relationships among members of microbial communities is key to understand and control the microbiota. Co-exclusion is arguably one of the most important patterns reflecting micro-organisms\u2019 intolerance to each other\u2019s presence. Knowing these relations opens an opportunity to manipulate microbiotas, personalize anti-microbial and probiotic treatments as well as guide microbiota transplantation. The co-exclusion pattern however, cannot be appropriately described by a linear function nor its strength be estimated using covariance or (negative) Pearson and Spearman correlation coefficients. This manuscript proposes a way to quantify the strength and evaluate the statistical significance of co-exclusion patterns between two, three or more variables describing a microbiota and allows one to extend analysis beyond micro-organism abundance by including other microbiome associated measurements such as, pH, temperature etc., as well as estimate the expected numbers of false positive co-exclusion patterns in a co-exclusion network.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The implemented computational pipeline (CoEx) tested against 2380 microbial profiles (samples) from The Human Microbiome Project resulted in body-site specific pairwise co-exclusion patterns.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Availability and implementation<\/jats:title>\n                    <jats:p>C++\u2009source code for calculation of the score and P-value for two, three and four dimensional co-exclusion patterns as well as source code and executable files for the CoEx pipeline are available at https:\/\/scsb.utmb.edu\/labgroups\/fofanov\/co-exclusion_in_microbial_communities.asp.<\/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\/bty414","type":"journal-article","created":{"date-parts":[[2018,6,1]],"date-time":"2018-06-01T23:52:41Z","timestamp":1527897161000},"page":"3695-3701","source":"Crossref","is-referenced-by-count":5,"title":["Detection of multi-dimensional co-exclusion patterns in microbial communities"],"prefix":"10.1093","volume":"34","author":[{"given":"Levent","family":"Albayrak","sequence":"first","affiliation":[{"name":"Department of Pharmacology and Toxicology, University of Texas Medical Branch\u2013Galveston, Galveston, USA"},{"name":"Sealy Center for Structural Biology and Molecular Biophysics, University of Texas Medical Branch\u2013Galveston, Galveston, USA"}]},{"given":"Kamil","family":"Khanipov","sequence":"additional","affiliation":[{"name":"Department of Pharmacology and Toxicology, University of Texas Medical Branch\u2013Galveston, Galveston, USA"},{"name":"Sealy Center for Structural Biology and Molecular Biophysics, University of Texas Medical Branch\u2013Galveston, Galveston, USA"},{"name":"Department of Computer Science, University of Houston, Houston, USA"}]},{"given":"George","family":"Golovko","sequence":"additional","affiliation":[{"name":"Department of Pharmacology and Toxicology, University of Texas Medical Branch\u2013Galveston, Galveston, USA"},{"name":"Sealy Center for Structural Biology and Molecular Biophysics, University of Texas Medical Branch\u2013Galveston, Galveston, USA"}]},{"given":"Yuriy","family":"Fofanov","sequence":"additional","affiliation":[{"name":"Department of Pharmacology and Toxicology, University of Texas Medical Branch\u2013Galveston, Galveston, USA"},{"name":"Sealy Center for Structural Biology and Molecular Biophysics, University of Texas Medical Branch\u2013Galveston, Galveston, USA"}]}],"member":"286","published-online":{"date-parts":[[2018,6,5]]},"reference":[{"key":"2023012712343959000_bty414-B1","doi-asserted-by":"crossref","first-page":"1907","DOI":"10.1093\/jnci\/djt300","article-title":"Human gut microbiome and risk for colorectal cancer","volume":"105","author":"Ahn","year":"2013","journal-title":"J. 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