{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,24]],"date-time":"2026-03-24T15:08:21Z","timestamp":1774364901119,"version":"3.50.1"},"reference-count":53,"publisher":"Oxford University Press (OUP)","issue":"19","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2015,10,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Motivation: There is a need for effective automated methods for profiling dynamic cell\u2013cell interactions with single-cell resolution from high-throughput time-lapse imaging data, especially, the interactions between immune effector cells and tumor cells in adoptive immunotherapy.<\/jats:p>\n               <jats:p>Results: Fluorescently labeled human T cells, natural killer cells (NK), and various target cells (NALM6, K562, EL4) were co-incubated on polydimethylsiloxane arrays of sub-nanoliter wells (nanowells), and imaged using multi-channel time-lapse microscopy. The proposed cell segmentation and tracking algorithms account for cell variability and exploit the nanowell confinement property to increase the yield of correctly analyzed nanowells from 45% (existing algorithms) to 98% for wells containing one effector and a single target, enabling automated quantification of cell locations, morphologies, movements, interactions, and deaths without the need for manual proofreading. Automated analysis of recordings from 12 different experiments demonstrated automated nanowell delineation accuracy &amp;gt;99%, automated cell segmentation accuracy &amp;gt;95%, and automated cell tracking accuracy of 90%, with default parameters, despite variations in illumination, staining, imaging noise, cell morphology, and cell clustering. An example analysis revealed that NK cells efficiently discriminate between live and dead targets by altering the duration of conjugation. The data also demonstrated that cytotoxic cells display higher motility than non-killers, both before and during contact.<\/jats:p>\n               <jats:p>Contact: broysam@central.uh.edu or nvaradar@central.uh.edu<\/jats:p>\n               <jats:p>Supplementary information: \u00a0Supplementary data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/btv355","type":"journal-article","created":{"date-parts":[[2015,6,11]],"date-time":"2015-06-11T04:09:00Z","timestamp":1433995740000},"page":"3189-3197","source":"Crossref","is-referenced-by-count":52,"title":["Automated profiling of individual cell\u2013cell interactions from high-throughput time-lapse imaging microscopy in nanowell grids (TIMING)"],"prefix":"10.1093","volume":"31","author":[{"given":"Amine","family":"Merouane","sequence":"first","affiliation":[{"name":"1 Department of Electrical and Computer Engineering and"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nicolas","family":"Rey-Villamizar","sequence":"additional","affiliation":[{"name":"1 Department of Electrical and Computer Engineering and"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yanbin","family":"Lu","sequence":"additional","affiliation":[{"name":"1 Department of Electrical and Computer Engineering and"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ivan","family":"Liadi","sequence":"additional","affiliation":[{"name":"2 Department of Chemical and Biomolecular Engineering, University of Houston, Houston, TX, USA and"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gabrielle","family":"Romain","sequence":"additional","affiliation":[{"name":"2 Department of Chemical and Biomolecular Engineering, University of Houston, Houston, TX, USA and"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jennifer","family":"Lu","sequence":"additional","affiliation":[{"name":"2 Department of Chemical and Biomolecular Engineering, University of Houston, Houston, TX, USA and"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Harjeet","family":"Singh","sequence":"additional","affiliation":[{"name":"3 Division of Pediatrics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Laurence J.N.","family":"Cooper","sequence":"additional","affiliation":[{"name":"3 Division of Pediatrics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Navin","family":"Varadarajan","sequence":"additional","affiliation":[{"name":"2 Department of Chemical and Biomolecular Engineering, University of Houston, Houston, TX, USA and"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Badrinath","family":"Roysam","sequence":"additional","affiliation":[{"name":"1 Department of Electrical and Computer Engineering and"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2015,6,9]]},"reference":[{"key":"2023020202301181500_btv355-B1","doi-asserted-by":"crossref","first-page":"327","DOI":"10.4161\/cc.5.3.2426","article-title":"Automated cell lineage construction: a rapid method to analyze clonal development established with murine neural progenitor cells","volume":"5","author":"Al-Kofahi","year":"2006","journal-title":"Cell Cycle"},{"key":"2023020202301181500_btv355-B2","doi-asserted-by":"crossref","first-page":"841","DOI":"10.1109\/TBME.2009.2035102","article-title":"Improved automatic detection and segmentation of cell nuclei in histopathology images","volume":"57","author":"Al-Kofahi","year":"2010","journal-title":"IEEE Trans. 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