{"id":3650,"date":"2020-11-10T14:04:21","date_gmt":"2020-11-10T19:04:21","guid":{"rendered":"https:\/\/www.med.unc.edu\/compmed\/?post_type=tribe_events&#038;p=3650"},"modified":"2021-04-22T10:36:46","modified_gmt":"2021-04-22T14:36:46","slug":"computational-medicine-seminar-11","status":"publish","type":"tribe_events","link":"https:\/\/www.med.unc.edu\/compmed\/event\/computational-medicine-seminar-11\/","title":{"rendered":"Computational Medicine Seminar"},"content":{"rendered":"<table width=\"100%\">\n<tbody>\n<tr>\n<td width=\"100%\"><strong>David Van Valen, PhD<\/strong><\/p>\n<p>Assistant Professor, Division of Biology and Biological Engineering<\/p>\n<p>California Institute of Technology<\/p>\n<p>Talk Title: <em><strong>\u00a0&#8220;Single-cell biology in a software 2.0 world&#8221;<\/strong><\/em><\/p>\n<p>&nbsp;<\/p>\n<p>Abstract:<\/p>\n<p>Multiplexed imaging methods can measure the expression of dozens of proteins while preserving spatial information. While these methods open an exciting new window into the biology of human tissues, interpreting the images they generate with single cell resolution remains a significant challenge. Current approaches to this problem in tissues rely on identifying cell nuclei, which results in inaccurate estimates of cellular phenotype and morphology. In this work, we overcome this limitation by combining multiplexed imaging\u2019s ability to image nuclear and membrane markers with large-scale data annotation and deep learning. We describe the construction of TissueNet, an image dataset containing more than one million paired whole-cell and nuclear annotations across eight tissue types and five imaging platforms. We also present Mesmer, a single model trained on this dataset that can perform nuclear and whole cell segmentation with human-level accuracy \u2013 as judged by expert human annotators and a panel of pathologists \u2013 across tissue types and imaging platforms. We show that Mesmer accurately measures cell morphology in tissues, opening up a new observable for quantifying cellular phenotypes in vivo. We make this model available to users of all backgrounds with both cloud-native software and on-premise software. Last, we also describe ongoing work to develop a similar resource and models for dynamic live-cell imaging data.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n","protected":false},"excerpt":{"rendered":"<p>David Van Valen, PhD Assistant Professor, Division of Biology and Biological Engineering California Institute of Technology Talk Title: \u00a0&#8220;Single-cell biology in a software 2.0 world&#8221; &nbsp; Abstract: Multiplexed imaging methods can measure the expression of dozens of proteins while preserving spatial information. While these methods open an exciting new window into the biology of human &hellip; <a href=\"https:\/\/www.med.unc.edu\/compmed\/event\/computational-medicine-seminar-11\/\" aria-label=\"Read more about Computational Medicine Seminar\">Read more<\/a><\/p>\n","protected":false},"author":89430,"featured_media":3786,"template":"","meta":{"_acf_changed":false,"_tribe_events_status":"","_tribe_events_status_reason":"","_tribe_events_is_hybrid":"","_tribe_events_is_virtual":"","_tribe_events_virtual_video_source":"","_tribe_events_virtual_embed_video":"","_tribe_events_virtual_linked_button_text":"","_tribe_events_virtual_linked_button":"","_tribe_events_virtual_show_embed_at":"","_tribe_events_virtual_show_embed_to":[],"_tribe_events_virtual_show_on_event":"","_tribe_events_virtual_show_on_views":"","_tribe_events_virtual_url":"","footnotes":"","_links_to":"","_links_to_target":""},"tags":[],"tribe_events_cat":[9],"class_list":["post-3650","tribe_events","type-tribe_events","status-publish","has-post-thumbnail","hentry","tribe_events_cat-seminar","cat_seminar","odd"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.8 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Computational Medicine Seminar | Computational Medicine<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.med.unc.edu\/compmed\/event\/computational-medicine-seminar-11\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Computational Medicine Seminar | Computational Medicine\" \/>\n<meta property=\"og:description\" content=\"David Van Valen, PhD Assistant Professor, Division of Biology and Biological Engineering California Institute of Technology Talk Title: \u00a0&#8220;Single-cell biology in a software 2.0 world&#8221; &nbsp; Abstract: Multiplexed imaging methods can measure the expression of dozens of proteins while preserving spatial information. While these methods open an exciting new window into the biology of human &hellip; Read more\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.med.unc.edu\/compmed\/event\/computational-medicine-seminar-11\/\" \/>\n<meta property=\"og:site_name\" content=\"Computational Medicine\" \/>\n<meta property=\"article:modified_time\" content=\"2021-04-22T14:36:46+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/www.med.unc.edu\/compmed\/wp-content\/uploads\/sites\/852\/2020\/11\/David-Van-Valen.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"180\" \/>\n\t<meta property=\"og:image:height\" content=\"180\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data1\" content=\"1 minute\" \/>\n<script type=\"application\/ld+json\" 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