{"id":6088,"date":"2025-03-26T14:02:25","date_gmt":"2025-03-26T05:02:25","guid":{"rendered":"https:\/\/www.infront.kyoto-u.ac.jp\/?page_id=6088"},"modified":"2026-05-12T16:05:07","modified_gmt":"2026-05-12T07:05:07","slug":"labo32","status":"publish","type":"page","link":"https:\/\/www.infront.kyoto-u.ac.jp\/en\/laboratory\/labo32\/","title":{"rendered":"LAB. OF Tissue Homeostasis"},"content":{"rendered":"<div id=\"pagehead\">\n<h2>LABORATORY<span>About our laboratory<\/span><\/h2>\n<\/div>\n<div id=\"pankuzu\"><a href=\"..\/..\/\">HOME<\/a> &gt; <a href=\"..\/\">Faculty<\/a> &gt; Lab. of Biological Data Science<\/div>\n<p><main id=\"main\" class=\"laboratory\"><\/p>\n<div class=\"contents no-photo\">\n<div class=\"department\">\n<p class=\"field\"><span>DEPARTMENT OF Biosystems Science<\/span>LAB. OF Biological Data Science<\/p>\n<\/p><\/div>\n<ul class=\"web-list\" style=\"padding-bottom:50px;\">\n<li><a href=\"https:\/\/genomics.virus.kyoto-u.ac.jp\/\" target=\"_blank\" rel=\"noopener\"><img decoding=\"async\" src=\"\/assets\/img\/laboratory\/i_web.svg\" alt=\"Website\"><\/a><\/li>\n<li><a href=\"https:\/\/x.com\/alexisvdb\" target=\"_blank\" rel=\"noopener\"><img decoding=\"async\" src=\"\/assets\/img\/laboratory\/i_x.svg\" alt=\"Website\"><\/a><\/li>\n<\/ul>\n<div class=\"message\">\n<h3 class=\"tit\">MESSAGE FROM THE LAB<\/h3>\n<p>An interdisciplinary team with expertise in bioinformatics, data science, and biology develops computational approaches to analyze and integrate single-cell and spatial transcriptomics data, aiming to uncover the principles governing cellular organization, interactions, and tissue function, and to elucidate previously uncharacterized biological processes.<\/p>\n<\/p><\/div>\n<\/p><\/div>\n<div class=\"member\">\n<div class=\"contents\">\n<div class=\"professer\" style=\"border-bottom:none;\">\n<div class=\"photo-p\"><img decoding=\"async\" src=\"\/assets\/img\/laboratory\/labo32\/prof.jpg\" alt=\"Alexis Vandenbon\"><\/div>\n<div class=\"identity\">\n<p><span class=\"position\">Associate Professor<\/span><span class=\"name\">Alexis Vandenbon<\/span><\/p>\n<\/div>\n<ul class=\"msg-list\">\n<li><a href=\"https:\/\/genomics.virus.kyoto-u.ac.jp\/\" target=\"_blank\" rel=\"noopener\"><img decoding=\"async\" src=\"\/assets\/img\/laboratory\/i_web.svg\" alt=\"Website\"><\/a><\/li>\n<li><a href=\"https:\/\/x.com\/alexisvdb\" target=\"_blank\" rel=\"noopener\"><img decoding=\"async\" src=\"\/assets\/img\/laboratory\/i_x.svg\" alt=\"Website\"><\/a><\/li>\n<li><a href=\"m&#97;&#105;&#108;&#116;&#111;&#58;&#97;&#108;&#101;&#120;&#105;&#115;&#118;&#100;&#98;&#64;&#105;&#110;&#102;&#114;&#111;&#110;&#116;&#46;&#107;&#121;&#111;&#116;&#111;&#45;&#117;&#46;&#97;&#99;&#46;jp\"><img decoding=\"async\" src=\"\/assets\/img\/laboratory\/i_ms.svg\" alt=\"Mail\"><\/a><\/li>\n<\/ul><\/div>\n<\/p><\/div>\n<\/p><\/div>\n<div class=\"research\">\n<h3 class=\"tit\">RESEARCH<\/h3>\n<div class=\"contents\">\n<div class=\"field\">\n<h4><span>Integrative analysis of large-scale omics data<\/span><\/h4>\n<p>Modern molecular biology generates vast, high-dimensional datasets, yet data alone does not yield biological insight. Our laboratory develops computational and bioinformatics approaches to extract meaningful patterns from large-scale datasets, with a particular focus on single-cell and spatial transcriptomics. By integrating diverse omics modalities across tissues and conditions, we aim to uncover the principles governing cellular organization, interactions, and systemic responses in health and disease.<\/p>\n<\/p><\/div>\n<\/p><\/div>\n<div class=\"bg-field\">\n<div class=\"field\">\n<h4>Revealing structured gene expression patterns in large-scale omics data<\/h4>\n<div class=\"with-photo\">\n<p class=\"txt\">Modern omics technologies generate large-scale gene expression datasets across thousands of genes and samples. While these data contain rich biological signals, it remains challenging to systematically identify meaningful patterns without prior assumptions. To address this, we developed singleCellHaystack, a bioinformatics method for detecting structured gene expression patterns in high-dimensional data, including single-cell and spatial omics (Vandenbon and Diez, Nature Communications, 2020). The identified patterns can be mapped back onto tissues or samples, enabling the discovery of biologically relevant gene activities across conditions. The figure shows representative examples from mouse liver (left), human intestine (top right), and mouse brain (bottom right).<\/p>\n<p class=\"img\"><img decoding=\"async\" src=\"\/assets\/img\/laboratory\/labo32\/figure_1.png\" alt=\"Revealing structured gene expression patterns in large-scale omics data\"><\/p>\n<\/p><\/div>\n<\/p><\/div>\n<div class=\"field\">\n<h4>DeepSpaceDB: a platform for accessible analysis of spatial transcriptomics data<\/h4>\n<div class=\"with-photo\">\n<p class=\"txt\">Spatial transcriptomics technologies enable high-resolution mapping of gene expression within tissues, but experiments remain costly and data processing requires substantial computational expertise. As a result, effective reuse and exploration of existing datasets is often limited. To address this, we developed DeepSpaceDB, a database and analysis platform that collects, standardizes, and integrates publicly available spatial transcriptomics data (Honcharuk et al., Nucleic Acids Res. 2026). DeepSpaceDB enables users to explore gene expression patterns, compare samples, and perform interactive analyses through an intuitive interface, without requiring advanced bioinformatics skills. The figure illustrates the data processing pipeline (left), the integration of more than 3,000 spatial datasets (center), and representative interactive analysis functions (right).<\/p>\n<p class=\"img\"><img decoding=\"async\" src=\"\/assets\/img\/laboratory\/labo32\/figure_2.png\" alt=\"DeepSpaceDB: a platform for accessible analysis of spatial transcriptomics data\"><\/p>\n<\/p><\/div>\n<\/p><\/div>\n<\/p><\/div>\n<\/p><\/div>\n<p>  \n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n<br \/>\n<\/main><\/p>\n","protected":false},"excerpt":{"rendered":"<p>LABORATORYAbout our laboratory HOME &gt; Faculty &gt; Lab. of Biological Data Science DEPARTMENT OF Biosystems ScienceLAB. OF Biological Data Science MESSAGE FROM THE LAB An interdisciplinary team with expertise in bioinformatics, data science, and biology develops computational approaches to analyze and integrate single-cell and spatial transcriptomics data, aiming to uncover the principles governing cellular organization, [&hellip;]<\/p>\n","protected":false},"author":2,"featured_media":0,"parent":131,"menu_order":32,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"_locale":"en_US","_original_post":"https:\/\/www.infront.kyoto-u.ac.jp\/?page_id=6086","footnotes":""},"class_list":["post-6088","page","type-page","status-publish","hentry","en-US"],"acf":[],"_links":{"self":[{"href":"https:\/\/www.infront.kyoto-u.ac.jp\/wp-json\/wp\/v2\/pages\/6088","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.infront.kyoto-u.ac.jp\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.infront.kyoto-u.ac.jp\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.infront.kyoto-u.ac.jp\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.infront.kyoto-u.ac.jp\/wp-json\/wp\/v2\/comments?post=6088"}],"version-history":[{"count":8,"href":"https:\/\/www.infront.kyoto-u.ac.jp\/wp-json\/wp\/v2\/pages\/6088\/revisions"}],"predecessor-version":[{"id":7608,"href":"https:\/\/www.infront.kyoto-u.ac.jp\/wp-json\/wp\/v2\/pages\/6088\/revisions\/7608"}],"up":[{"embeddable":true,"href":"https:\/\/www.infront.kyoto-u.ac.jp\/wp-json\/wp\/v2\/pages\/131"}],"wp:attachment":[{"href":"https:\/\/www.infront.kyoto-u.ac.jp\/wp-json\/wp\/v2\/media?parent=6088"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}