{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,6]],"date-time":"2025-05-06T08:27:08Z","timestamp":1746520028554,"version":"3.37.3"},"reference-count":11,"publisher":"Oxford University Press (OUP)","issue":"11","license":[{"start":{"date-parts":[[2020,10,14]],"date-time":"2020-10-14T00:00:00Z","timestamp":1602633600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"name":"JSPS Grant-in-Aid for Scientific Research","award":["18H04798","19H05210","20H04841","20H04281"],"award-info":[{"award-number":["18H04798","19H05210","20H04841","20H04281"]}]},{"DOI":"10.13039\/100009619","name":"Japan Agency for Medical Research and Development","doi-asserted-by":"publisher","award":["JP19dm0107087h0004","JP19km0405207h9904","JP19ek0109281h0003"],"award-info":[{"award-number":["JP19dm0107087h0004","JP19km0405207h9904","JP19ek0109281h0003"]}],"id":[{"id":"10.13039\/100009619","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,7,12]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Summary<\/jats:title>\n                  <jats:p>Recent advancements in high-dimensional single-cell technologies, such as mass cytometry, enable longitudinal experiments to track dynamics of cell populations and identify change points where the proportions vary significantly. However, current research is limited by the lack of tools specialized for analyzing longitudinal mass cytometry data. In order to infer cell population dynamics from such data, we developed a statistical framework named CYBERTRACK2.0. The framework\u2019s analytic performance was validated against synthetic and real data, showing that its results are consistent with previous research.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Availability and implementation<\/jats:title>\n                  <jats:p>CYBERTRACK2.0 is available at https:\/\/github.com\/kodaim1115\/CYBERTRACK2.<\/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\/btaa873","type":"journal-article","created":{"date-parts":[[2020,9,28]],"date-time":"2020-09-28T19:17:03Z","timestamp":1601320623000},"page":"1632-1634","source":"Crossref","is-referenced-by-count":5,"title":["CYBERTRACK2.0: zero-inflated model-based cell clustering and population tracking method for longitudinal mass cytometry data"],"prefix":"10.1093","volume":"37","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3221-329X","authenticated-orcid":false,"given":"Kodai","family":"Minoura","sequence":"first","affiliation":[{"name":"Division of Systems Biology"},{"name":"Division of Immunology, Graduate School of Medicine, Nagoya University , Nagoya 4668550, Japan"}]},{"given":"Ko","family":"Abe","sequence":"additional","affiliation":[{"name":"Division of Systems Biology"}]},{"given":"Yuka","family":"Maeda","sequence":"additional","affiliation":[{"name":"Division of Cancer Immunology, Research Institute\/EPOC, National Cancer Center , Tokyo, Chiba 1040045\/2778577, Japan"}]},{"given":"Hiroyoshi","family":"Nishikawa","sequence":"additional","affiliation":[{"name":"Division of Immunology, Graduate School of Medicine, Nagoya University , Nagoya 4668550, Japan"},{"name":"Division of Cancer Immunology, Research Institute\/EPOC, National Cancer Center , Tokyo, Chiba 1040045\/2778577, Japan"}]},{"given":"Teppei","family":"Shimamura","sequence":"additional","affiliation":[{"name":"Division of Systems Biology"}]}],"member":"286","published-online":{"date-parts":[[2020,10,14]]},"reference":[{"key":"2023051709351625200_btaa873-B1","doi-asserted-by":"crossref","first-page":"827","DOI":"10.1158\/2159-8290.CD-15-1545","article-title":"Analysis of immune signatures in longitudinal tumor samples yields insight into biomarkers of response and mechanisms of resistance to immune checkpoint blockade","volume":"6","author":"Chen","year":"2016","journal-title":"Cancer Discov"},{"key":"2023051709351625200_btaa873-B2","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1016\/j.ejca.2016.03.085","article-title":"Systems immune monitoring in cancer therapy","volume":"61","author":"Greenplate","year":"2016","journal-title":"Eur. 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