{"id":1653,"date":"2025-08-03T10:21:33","date_gmt":"2025-08-03T01:21:33","guid":{"rendered":"https:\/\/www.jsbi.org\/iibmp2025\/?page_id=1653"},"modified":"2025-08-22T15:24:10","modified_gmt":"2025-08-22T06:24:10","slug":"%e5%8f%a3%e9%a0%ad%e7%99%ba%e8%a1%a8%e3%83%8f%e3%82%a4%e3%83%a9%e3%82%a4%e3%83%88%e3%83%88%e3%83%a9%e3%83%83%e3%82%af","status":"publish","type":"page","link":"https:\/\/www.jsbi.org\/iibmp2025\/%e5%8f%a3%e9%a0%ad%e7%99%ba%e8%a1%a8%e3%83%8f%e3%82%a4%e3%83%a9%e3%82%a4%e3%83%88%e3%83%88%e3%83%a9%e3%83%83%e3%82%af\/","title":{"rendered":"\u53e3\u982d\u767a\u8868\u30fb\u30cf\u30a4\u30e9\u30a4\u30c8\u30c8\u30e9\u30c3\u30af"},"content":{"rendered":"\n<h2 class=\"wp-block-heading\">\u8b1b\u6f14\u8005\u3078\u306e\u3054\u6848\u5185<\/h2>\n\n\n\n<ul class=\"wp-block-list is-style-vk-check-mark\">\n<li>\u884c\u52d5\u898f\u7bc4\u3092\u9075\u5b88\u3057\u3066\u304f\u3060\u3055\u3044\u3002<\/li>\n\n\n\n<li>\u4f7f\u7528\u8a00\u8a9e\u306f\u65e5\u672c\u8a9e\u53ca\u3073\u82f1\u8a9e\u3067\u3059\u3002\u30b9\u30e9\u30a4\u30c9\u306f\u82f1\u8a9e\u3092\u63a8\u5968\u3044\u305f\u3057\u307e\u3059\u3002<\/li>\n\n\n\n<li>\u3054\u4f7f\u7528\u306b\u306a\u308b\u30b9\u30e9\u30a4\u30c9\u306f16\uff1a9\u3067\u3054\u4f5c\u6210\u4e0b\u3055\u3044\uff08\uff14\uff1a\uff13\u3067\u3082\u6620\u50cf\u306f\u51fa\u307e\u3059\u304c\u5c11\u3057\u5c0f\u3055\u304f\u306a\u308a\u307e\u3059\uff09\u3002<\/li>\n\n\n\n<li>\u767a\u8868\u306f\u5404\u81ea\u306ePC\u306b\u3066\u884c\u3063\u3066\u3044\u305f\u3060\u304d\u307e\u3059\u3002\u63a5\u7d9a\u7aef\u5b50\u306fHDMI\u3067\u3059\u3002\u4f1a\u5834\u3067\u3082\u5909\u63db\u30a2\u30c0\u30d7\u30bf\u3092\u3054\u7528\u610f\u3057\u307e\u3059\u304c\u3001\u3054\u81ea\u8eab\u306ePC\u3067\u4f7f\u7528\u5b9f\u7e3e\u306e\u3042\u308bHDMI\uff08\u30e1\u30b9\uff09\u3078\u306e\u5909\u63db\u30a2\u30c0\u30d7\u30bf\u3092\u3054\u6301\u53c2\u3044\u305f\u3060\u304f\u3053\u3068\u3092\u63a8\u5968\u3057\u307e\u3059\u3002<\/li>\n\n\n\n<li>\u4e8b\u524d\u306b\u63a5\u7d9a\u78ba\u8a8d\u3092\u884c\u3044\u307e\u3059\u3002\u30bb\u30c3\u30b7\u30e7\u30f310\u5206\u524d\u307e\u3067\u306b\u3054\u81ea\u8eab\u306e\u30d1\u30bd\u30b3\u30f3\u3092\u6301\u3063\u3066\u4f1a\u5834\u524d\u65b9\u306e\u6f14\u8005\u5e2d\u306b\u304a\u8d8a\u3057\u9802\u304d\u3001\u6f14\u53f0\u8fd1\u304f\u306b\u3044\u308b\u30b9\u30bf\u30c3\u30d5(SATFF\u306e\u540d\u672d\u3092\u3064\u3051\u3066\u3044\u307e\u3059)\u306b\u304a\u58f0\u304c\u3051\u304f\u3060\u3055\u3044\u3002<\/li>\n\n\n\n<li>\u5ea7\u9577\u306e\u6307\u793a\u306b\u3057\u305f\u304c\u3044\u3001\u4e88\u5b9a\u3055\u308c\u305f\u767a\u8868\u6642\u523b\u3092\u53b3\u5b88\u3057\u3066\u3044\u305f\u3060\u3051\u307e\u3059\u3088\u3046\u304a\u9858\u3044\u81f4\u3057\u307e\u3059\u3002<br>\u53e3\u982d\u767a\u8868\u3000\u3000\u3000\u3000\u3000\u300022\u5206 \uff08\u767a\u886817\u5206 + \u8cea\u7591\u5fdc\u7b545\u5206\uff09<br>\u30cf\u30a4\u30e9\u30a4\u30c8\u30c8\u30e9\u30c3\u30af\u300022\u5206 \uff08\u767a\u886817\u5206 + \u8cea\u7591\u5fdc\u7b545\u5206\uff09<\/li>\n\n\n\n<li>\u30cf\u30a4\u30e9\u30a4\u30c8\u30c8\u30e9\u30c3\u30af\u767a\u8868\u8005\u306e\u4e2d\u304b\u3089\u300c\u5f8c\u85e4\u4fee\u8cde\uff08\u30cf\u30a4\u30e9\u30a4\u30c8\u30c8\u30e9\u30c3\u30af\u90e8\u9580\uff09\u300d\uff081\u540d\uff09\u3092\u9078\u51fa\u3044\u305f\u3057\u307e\u3059\u3002<\/li>\n\n\n\n<li>\u4e00\u822c\u53e3\u982d\u767a\u8868\u8005\u306e\u4e2d\u304b\u3089\u3001\u300c\u5f8c\u85e4\u4fee\u8cde\uff08\u53e3\u982d\u767a\u8868\u90e8\u9580\uff09\u300d\uff081\u540d\uff09\u304a\u3088\u3073\u300c\u512a\u79c0\u53e3\u982d\u767a\u8868\u8cde\u300d\uff08\u6570\u540d\uff09\u3092\u9078\u51fa\u3044\u305f\u3057\u307e\u3059\u3002<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">\u53e3\u982d\u767a\u8868\u30fb\u30cf\u30a4\u30e9\u30a4\u30c8\u30c8\u30e9\u30c3\u30af\u3000OS-1<\/h3>\n\n\n<figure class=\"wp-block-table is-style-regular\">\n<table>\n<tbody>\n<tr>\n<td style=\"background: #eeeeee; width: 100pt;\"><strong>\u65e5\u6642\u30fb\u4f1a\u5834<\/strong><\/td>\n<td>9\u67083\u65e5\uff08\u6c34\uff0913\u664240\u5206\u301c15\u664210\u5206\u3000\u7b2c3\u4f1a\u5834<\/td>\n<\/tr>\n<tr>\n<td style=\"background: #eeeeee; width: 100pt;\"><strong>\u5ea7\u9577<\/strong><\/td>\n<td>\u7b20\u539f \u6d69\u592a (\u65e5\u672c\u305f\u3070\u3053\u7523\u696d\u682a\u5f0f\u4f1a\u793e \u533b\u85ac\u7dcf\u5408\u7814\u7a76\u6240)<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/figure>\n\n\n<h4 class=\"wp-block-heading\">\u30cf\u30a4\u30e9\u30a4\u30c8\u30c8\u30e9\u30c3\u30af<\/h4>\n\n\n\n<p><strong>HT-101<\/strong> \/ PO-148<br>Novel artificial intelligence-based identification of drug-gene-disease interaction using protein-protein interaction<br>\u30bf\u30f3\u30d1\u30af\u8cea\u9593\u76f8\u4e92\u4f5c\u7528\u3092\u5229\u7528\u3057\u305f\u4eba\u5de5\u77e5\u80fd\u306b\u3088\u308b\u65b0\u3057\u3044\u85ac\u5264\u907a\u4f1d\u5b50-\u75be\u60a3\u76f8\u4e92\u4f5c\u7528\u306e\u540c\u5b9a<br>\u7530\u53e3 \u5584\u5f18<sup>1<\/sup>&nbsp; (<sup>1<\/sup>\u4e2d\u592e\u5927\u5b66)<\/p>\n\n\n\n<p><strong>HT-102<\/strong><br>Evolutionary scenarios for the specific recognition of nonhomologous endogenous peptides by G protein\u2013coupled receptor paralogs<br>G\u30bf\u30f3\u30d1\u30af\u8cea\u5171\u5f79\u578b\u53d7\u5bb9\u4f53\u306e\u30da\u30d7\u30c1\u30c9\u30ea\u30ac\u30f3\u30c9\u8a8d\u8b58\u6a5f\u69cb\u3068\u305d\u306e\u9032\u5316\u904e\u7a0b\u306e\u63a8\u5b9a<br>\u767d\u77f3 \u6167<sup>1<\/sup>, \u548c\u7530 \u660e\u6f84<sup>1<\/sup>, \u4f50\u7af9 \u708e<sup>1<\/sup> (<sup>1<\/sup>\u516c\u76ca\u8ca1\u56e3\u6cd5\u4eba\u30b5\u30f3\u30c8\u30ea\u30fc\u751f\u547d\u79d1\u5b66\u8ca1\u56e3 \u751f\u7269\u6709\u6a5f\u79d1\u5b66\u7814\u7a76\u6240)<\/p>\n\n\n\n<h4 class=\"wp-block-heading\">\u53e3\u982d\u767a\u8868<\/h4>\n\n\n\n<p><strong>OS-103<\/strong> \/ PO-151<br>PLANT: Protein language model for predicting the antigenicity of Influenza viruses<br>PLANT: \u30a4\u30f3\u30d5\u30eb\u30a8\u30f3\u30b6\u30a6\u30a4\u30eb\u30b9\u306e\u6297\u539f\u6027\u3092\u4e88\u6e2c\u3059\u308b\u30bf\u30f3\u30d1\u30af\u8cea\u8a00\u8a9e\u30e2\u30c7\u30eb<br>\u4f0a\u6771 \u6f64\u5e73<sup>1<\/sup>, \u5ddd\u4e45\u4fdd \u4fee\u4f51<sup>1<\/sup>, \u6d77\u91ce \u535a\u4eae<sup>1<\/sup>, Strange Adam<sup>1<\/sup>, Lytras Spyros<sup>1<\/sup>, Lilley Alice<sup>2<\/sup>, Harvey Ruth<sup>2<\/sup>, Lewis Nicola<sup>2<\/sup>, \u4f50\u85e4 \u4f73<sup>1 <\/sup>&nbsp;(<sup>1<\/sup>\u6771\u4eac\u5927\u5b66\u533b\u79d1\u5b66\u7814\u7a76\u6240, <sup>2<\/sup>The Francis Crick Institute)<\/p>\n\n\n\n<p><strong>OS-104<\/strong> \/ PO-162<br>Estimating the impact of haplotype-phased SNVs on protein structure and transcriptional expression<br>\u30cf\u30d7\u30ed\u30bf\u30a4\u30d7\u306b\u95a2\u9023\u3059\u308bSNV\u306b\u3088\u308b\u30bf\u30f3\u30d1\u30af\u8cea\u7acb\u4f53\u69cb\u9020\u304a\u3088\u3073\u8ee2\u5199\u767a\u73fe\u3078\u306e\u5f71\u97ff\u63a8\u5b9a<br>\u5927\u5e73 \u6b63\u8cb4<sup>1,2<\/sup>, \u9577\ufa11 \u6b63\u6717<sup>3,4<\/sup>, \u571f\u539f \u4e00\u54c9<sup>1,2<\/sup>, \u5c71\u4e0b \u7406\u5b87<sup>1,5<\/sup>&nbsp; (<sup>1<\/sup>\u56fd\u7acb\u304c\u3093\u7814\u7a76\u30bb\u30f3\u30bf\u30fc \u5148\u7aef\u533b\u7642\u958b\u767a\u30bb\u30f3\u30bf\u30fc \u30c8\u30e9\u30f3\u30b9\u30ec\u30fc\u30b7\u30e7\u30ca\u30eb\u30a4\u30f3\u30d5\u30a9\u30de\u30c6\u30a3\u30af\u30b9\u5206\u91ce, <sup>2<\/sup>\u6771\u4eac\u5927\u5b66\u5927\u5b66\u9662 \u65b0\u9818\u57df\u5275\u6210\u79d1\u5b66\u7814\u7a76\u79d1 \u5148\u7aef\u751f\u547d\u79d1\u5b66\u5c02\u653b, <sup>3<\/sup>\u4e5d\u5dde\u5927\u5b66 \u751f\u4f53\u9632\u5fa1\u533b\u5b66\u7814\u7a76\u6240 \u9ad8\u6df1\u5ea6\u30aa\u30df\u30af\u30b9\u30b5\u30a4\u30a8\u30f3\u30b9\u30bb\u30f3\u30bf\u30fc \u30d0\u30a4\u30aa\u30e1\u30c7\u30a3\u30ab\u30eb\u60c5\u5831\u89e3\u6790\u5206\u91ce, <sup>4<\/sup>\u4eac\u90fd\u5927\u5b66\u5927\u5b66\u9662\u533b\u5b66\u7814\u7a76\u79d1\u9644\u5c5e\u30b2\u30ce\u30e0\u533b\u5b66\u30bb\u30f3\u30bf\u30fc, <sup>5<\/sup>\u6771\u4eac\u5927\u5b66\u5927\u5b66\u9662 \u65b0\u9818\u57df\u5275\u6210\u79d1\u5b66\u7814\u7a76\u79d1 \u30e1\u30c7\u30a3\u30ab\u30eb\u60c5\u5831\u751f\u547d\u5c02\u653b)<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">\u53e3\u982d\u767a\u8868\u30fb\u30cf\u30a4\u30e9\u30a4\u30c8\u30c8\u30e9\u30c3\u30af\u3000OS-2<\/h3>\n\n\n<figure class=\"wp-block-table is-style-regular\">\n<table>\n<tbody>\n<tr>\n<td style=\"background: #eeeeee; width: 100pt;\"><strong>\u65e5\u6642\u30fb\u4f1a\u5834<\/strong><\/td>\n<td>9\u67084\u65e5\uff08\u6728\uff0910\u664210\u5206\u301c11\u664240\u5206\u3000\u7b2c2\u4f1a\u5834<\/td>\n<\/tr>\n<tr>\n<td style=\"background: #eeeeee; width: 100pt;\"><strong>\u5ea7\u9577<\/strong><\/td>\n<td>\u5927\u4e0a \u96c5\u53f2 (\u6771\u4eac\u79d1\u5b66\u5927\u5b66)<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/figure>\n\n\n<h4 class=\"wp-block-heading\">\u30cf\u30a4\u30e9\u30a4\u30c8\u30c8\u30e9\u30c3\u30af<\/h4>\n\n\n\n<p><strong>HT-201<\/strong> \/ PO-057<br>Drug-induced cis-regulatory elements in human hepatocytes affect molecular phenotypes associated with adverse reactions<br>\u85ac\u7269\u526f\u4f5c\u7528\u306b\u95a2\u9023\u3059\u308b\u5206\u5b50\u8868\u73fe\u578b\u3092\u5236\u5fa1\u3059\u308b\u85ac\u5264\u5fdc\u7b54\u6027\u30b7\u30b9\u5236\u5fa1\u30a8\u30ec\u30e1\u30f3\u30c8<br>\u5ddd\u8def \u82f1\u54c9<sup>1<\/sup>, \u9f4a\u85e4 \u7d17\u5e0c<sup>1<\/sup>, \u548c\u7530 \u6dbc\u5b50<sup>1<\/sup>, \u897f\u6751 \u53cb\u679d<sup>1 <\/sup>&nbsp;(<sup>1<\/sup>Tokyo Metropolitan Institute of Medical Science)<\/p>\n\n\n\n<p><strong>HT-202<\/strong> \/ PO-019<br>Data-efficient protein mutational effect prediction with weak supervision by molecular simulation and protein language models<br>\u5206\u5b50\u30b7\u30df\u30e5\u30ec\u30fc\u30b7\u30e7\u30f3\u3068\u30bf\u30f3\u30d1\u30af\u8cea\u8a00\u8a9e\u30e2\u30c7\u30eb\u306b\u3088\u308b\u5f31\u6559\u5e2b\u3042\u308a\u5b66\u7fd2\u3092\u7528\u3044\u305f\u30c7\u30fc\u30bf\u52b9\u7387\u7684\u306a\u30bf\u30f3\u30d1\u30af\u8cea\u5909\u7570\u52b9\u679c\u4e88\u6e2c<br>\u51fa\u53e3 \u9244\u5e73<sup>1,2<\/sup>, \u6765\u898b\u7530 \u9065\u4e00<sup>3<\/sup>, \u98ef\u7530 \u614e\u4ec1<sup>3<\/sup>, \u5c0f\u6797 \u6d77\u6e21<sup>2<\/sup>, \u9f4b\u85e4 \u88d5<sup>1,2,3<\/sup>&nbsp; (<sup>1<\/sup>\u6771\u4eac\u5927\u5b66, <sup>2<\/sup>\u7523\u696d\u6280\u8853\u7dcf\u5408\u7814\u7a76\u6240, <sup>3<\/sup>\u5317\u91cc\u5927\u5b66)<\/p>\n\n\n\n<h4 class=\"wp-block-heading\">\u53e3\u982d\u767a\u8868<\/h4>\n\n\n\n<p><strong>OS-203<\/strong> \/ PO-153<br>RNA Inverse Folding Using a Grammar-Guided Generative Model with Tree-Based Representations<br>\u6587\u6cd5\u8a98\u5c0e\u3068\u6728\u69cb\u9020\u8868\u73fe\u3092\u7528\u3044\u305f\u751f\u6210\u30e2\u30c7\u30eb\u306b\u3088\u308bRNA\u9006\u6298\u308a\u7573\u307f<br>\u6e21\u9089 \u5065\u592a\u90ce<sup>1<\/sup>, \u79cb\u5c71 \u771f\u90a3\u6597<sup>2<\/sup>, \u698a\u539f \u5eb7\u6587<sup>2 <\/sup>&nbsp;(<sup>1<\/sup>\u6176\u61c9\u7fa9\u587e\u5927\u5b66\u5927\u5b66\u9662 \u7406\u5de5\u5b66\u7814\u7a76\u79d1, <sup>2<\/sup>\u5317\u91cc\u5927\u5b66 \u672a\u6765\u5de5\u5b66\u90e8)<\/p>\n\n\n\n<p><strong>OS-204<\/strong> \/ PO-172<br>A Maximum Expected Accuracy\u2013Based RNA Secondary Structure Prediction Method Considering Loop Structures<br>\u30eb\u30fc\u30d7\u69cb\u9020\u3092\u8003\u616e\u3057\u305f\u6700\u5927\u671f\u5f85\u7cbe\u5ea6\u578bRNA\u4e8c\u6b21\u69cb\u9020\u4e88\u6e2c\u624b\u6cd5<br>\u592a\u7530\u57a3 \u5320<sup>1<\/sup>, \u6d45\u4e95 \u6f54<sup>1<\/sup>&nbsp; (<sup>1<\/sup>\u6771\u4eac\u5927\u5b66)<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">\u53e3\u982d\u767a\u8868\u30fb\u30cf\u30a4\u30e9\u30a4\u30c8\u30c8\u30e9\u30c3\u30af\u3000OS-3<\/h3>\n\n\n<figure class=\"wp-block-table is-style-regular\">\n<table>\n<tbody>\n<tr>\n<td style=\"background: #eeeeee; width: 100pt;\"><strong>\u65e5\u6642\u30fb\u4f1a\u5834<\/strong><\/td>\n<td>9\u67084\u65e5\uff08\u6728\uff0910\u664210\u5206\u301c11\u664240\u5206\u3000\u7b2c3\u4f1a\u5834<\/td>\n<\/tr>\n<tr>\n<td style=\"background: #eeeeee; width: 100pt;\"><strong>\u5ea7\u9577<\/strong><\/td>\n<td>\u9060\u91cc \u7531\u4f73\u5b50 (\u7acb\u547d\u9928\u5927\u5b66)<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/figure>\n\n\n<h4 class=\"wp-block-heading\">\u30cf\u30a4\u30e9\u30a4\u30c8\u30c8\u30e9\u30c3\u30af<\/h4>\n\n\n\n<p><strong>HT-301<\/strong> \/ PO-085<br>TRESOR: comprehensive discovery of therapeutic targets for orphan diseases via integration of GWAS and TWAS<br>TRESOR: GWAS\u3068TWAS\u306e\u878d\u5408\u306b\u3088\u308b\u5e0c\u5c11\u75be\u60a3\u306b\u5bfe\u3059\u308b\u5275\u85ac\u6a19\u7684\u5206\u5b50\u306e\u7db2\u7f85\u7684\u63a2\u7d22<br>\u96e3\u6ce2 \u91cc\u5b50<sup>1<\/sup>, \u5ca9\u7530 \u901a\u592b<sup>2<\/sup>, \u6fe1\u6728 \u771f\u4e00<sup>3<\/sup>, \u5927\u8c37 \u5247\u5b50<sup>1<\/sup>, \u5c71\u897f \u82b3\u88d5<sup>1<\/sup>&nbsp; (<sup>1<\/sup>\u540d\u53e4\u5c4b\u5927\u5b66,<sup> 2<\/sup>\u4e5d\u5dde\u5de5\u696d\u5927\u5b66,<sup> 3<\/sup>\u5927\u5206\u5927\u5b66)<\/p>\n\n\n\n<p><strong>HT-302<\/strong> \/ PO-107<br>MetDeeCINE: Deciphering Metabolic Regulation through Deep Learning and Multi-Omics<br>MetDeeCINE: \u5b9a\u91cf\u7684\u4ee3\u8b1d\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u69cb\u7bc9\u306e\u305f\u3081\u306e\u30de\u30eb\u30c1\u30aa\u30df\u30af\u30b9\u7d71\u5408AI<br>\u4f0a\u6771 \u5de7<sup>1<\/sup>, \u5927\u91ce \u8061<sup>1<\/sup>, \u738b \u4e00\u7136<sup>2<\/sup>, \u9ed2\u7530 \u771f\u4e5f<sup>2<\/sup>, \u6e05\u6c34 \u79c0\u5e78<sup>1 <\/sup>&nbsp;(<sup>1<\/sup>\u6771\u4eac\u79d1\u5b66\u5927\u5b66, <sup>2<\/sup>\u6771\u4eac\u5927\u5b66)<\/p>\n\n\n\n<p><strong>HT-303<br><\/strong>DBgDel: Database-Enhanced Gene Deletion Framework for Growth-Coupled Production in Genome-Scale Metabolic Models<br>DBgDel: \u30b2\u30ce\u30e0\u30b9\u30b1\u30fc\u30eb\u4ee3\u8b1d\u30e2\u30c7\u30eb\u306b\u304a\u3051\u308b\u5897\u6b96\u9023\u52d5\u751f\u7523\u306e\u305f\u3081\u306e\u30c7\u30fc\u30bf\u30d9\u30fc\u30b9\u5f37\u5316\u578b\u907a\u4f1d\u5b50\u524a\u9664\u30d5\u30ec\u30fc\u30e0\u30ef\u30fc\u30af<br>Yang Ziwei<sup>1<\/sup>, Tamura Takeyuki<sup>1<\/sup>,&nbsp; (<sup>1<\/sup>\u4eac\u90fd\u5927\u5b66)<\/p>\n\n\n\n<h4 class=\"wp-block-heading\">\u53e3\u982d\u767a\u8868<\/h4>\n\n\n\n<p><strong>OS-304<\/strong> \/ PO-152<br>DeepRES: Deep learning enables reaction-based comprehensive enzyme screening<br>DeepRES: \u53cd\u5fdc\u60c5\u5831\u306b\u57fa\u3065\u304f\u7db2\u7f85\u7684\u306a\u9175\u7d20\u30b9\u30af\u30ea\u30fc\u30cb\u30f3\u30b0\u306e\u305f\u3081\u306e\u6df1\u5c64\u5b66\u7fd2\u30e2\u30c7\u30eb<br>\u5ee3\u7530 \u4f73\u4eae<sup>1<\/sup>, \u5c71\u7530 \u62d3\u53f8<sup>1,2,3,4<\/sup>&nbsp; (<sup>1<\/sup>\u6771\u4eac\u79d1\u5b66\u5927\u5b66, <sup>2<\/sup>\u682a\u5f0f\u4f1a\u793e\u30e1\u30bf\u30b8\u30a7\u30f3, <sup>3<\/sup>\u30e1\u30bf\u30b8\u30a7\u30f3\u30bb\u30e9\u30d4\u30e5\u30fc\u30c6\u30a3\u30af\u30b9\u682a\u5f0f\u4f1a\u793e, <sup>4<\/sup>\u682a\u5f0f\u4f1a\u793edigzyme)<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">\u53e3\u982d\u767a\u8868\u30fb\u30cf\u30a4\u30e9\u30a4\u30c8\u30c8\u30e9\u30c3\u30af\u3000OS-4<\/h3>\n\n\n<figure class=\"wp-block-table is-style-regular\">\n<table>\n<tbody>\n<tr>\n<td style=\"background: #eeeeee; width: 100pt;\"><strong>\u65e5\u6642\u30fb\u4f1a\u5834<\/strong><\/td>\n<td>9\u67084\u65e5\uff08\u6728\uff0914\u664200\u5206\u301c15\u664230\u5206\u3000\u7b2c3\u4f1a\u5834<\/td>\n<\/tr>\n<tr>\n<td style=\"background: #eeeeee; width: 100pt;\"><strong>\u5ea7\u9577<\/strong><\/td>\n<td>\u702c\u5c3e \u8302\u4eba (\u5927\u962a\u5927\u5b66)<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/figure>\n\n\n<h4 class=\"wp-block-heading\">\u30cf\u30a4\u30e9\u30a4\u30c8\u30c8\u30e9\u30c3\u30af<\/h4>\n\n\n\n<p><strong>HT-401<\/strong><br>RVINN: A Flexible Modeling for Inferring Dynamic Transcriptional and Post-Transcriptional Regulation Using Physics-Informed Neural Networks<br>RVINN: Physics-Informed Neural Networks\u3092\u7528\u3044\u305f\u52d5\u7684\u306a\u8ee2\u5199\u30fb\u8ee2\u5199\u5f8c\u5236\u5fa1\u63a8\u8ad6\u306e\u305f\u3081\u306e\u67d4\u8edf\u306a\u30e2\u30c7\u30ea\u30f3\u30b0<br>\u6b66\u85e4 \u7406<sup>1,2<\/sup>, \u90ed \u4e2d\u6a11<sup>1,2<\/sup>, \u5c71\u53e3 \u985e<sup>1,2<\/sup> (<sup>1<\/sup>\u611b\u77e5\u770c\u304c\u3093\u30bb\u30f3\u30bf\u30fc\u7814\u7a76\u6240\u30b7\u30b9\u30c6\u30e0\u89e3\u6790\u5b66\u5206\u91ce, <sup>2<\/sup>\u540d\u53e4\u5c4b\u5927\u5b66\u5927\u5b66\u9662\u533b\u5b66\u7cfb\u7814\u7a76\u79d1\u304c\u3093\u30b7\u30b9\u30c6\u30e0\u60c5\u5831\u5b66)<\/p>\n\n\n\n<h4 class=\"wp-block-heading\">\u53e3\u982d\u767a\u8868<\/h4>\n\n\n\n<p><strong>OS-402<\/strong> \/ PO-164<br>Analysis and Prediction of the Impact of Anticancer Drugs on Gut Microbiota<br>\u304c\u3093\u6cbb\u7642\u85ac\u306b\u3088\u308b\u8178\u5185\u7d30\u83cc\u53e2\u306e\u5909\u5316\u89e3\u6790\u3068\u4e88\u6e2c\u30e2\u30c7\u30eb\u306e\u69cb\u7bc9<br>\u6817\u539f \u606d\u5b50<sup>1,2<\/sup>, \u9152\u4e95 \u4fca\u8f14<sup>1,2<\/sup>, \u98ef\u7530 \u76f4\u5b50<sup>3<\/sup>, \u6fa4\u7530 \u61b2\u592a\u90ce<sup>4<\/sup>, \u6d1e\u6fa4 \u667a\u81f3<sup>3<\/sup>, \u85e4\u6fa4 \u5b5d\u592b<sup>3,5<\/sup>, \u4e2d\u6751 \u80fd\u7ae0<sup>3,6<\/sup>, \u5f71\u5c71 \u4fca\u4e00\u90ce<sup>2<\/sup>, \u571f\u539f \u4e00\u54c9<sup>1,2<\/sup>, \u5c71\u4e0b \u7406\u5b87<sup>2,7<\/sup>&nbsp; (<sup>1<\/sup>\u6771\u4eac\u5927\u5b66\u65b0\u9818\u57df\u5275\u6210\u79d1\u5b66\u7814\u7a76\u79d1\u5148\u7aef\u751f\u547d\u79d1\u5b66\u5c02\u653b, <sup>2<\/sup>\u56fd\u7acb\u304c\u3093\u7814\u7a76\u30bb\u30f3\u30bf\u30fc\u5148\u7aef\u533b\u7642\u958b\u767a\u30bb\u30f3\u30bf\u30fc\u30c8\u30e9\u30f3\u30b9\u30ec\u30fc\u30b7\u30e7\u30ca\u30eb\u30a4\u30f3\u30d5\u30a9\u30de\u30c6\u30a3\u30af\u30b9\u5206\u91ce, <sup>3<\/sup>\u56fd\u7acb\u304c\u3093\u7814\u7a76\u30bb\u30f3\u30bf\u30fc\u6771\u75c5\u9662\u533b\u85ac\u54c1\u958b\u767a\u63a8\u9032\u90e8\u30c8\u30e9\u30f3\u30b9\u30ec\u30fc\u30b7\u30e7\u30ca\u30eb\u30ea\u30b5\u30fc\u30c1\u652f\u63f4\u5ba4, <sup>4<\/sup>\u91e7\u8def\u52b4\u707d\u75c5\u9662\u816b\u760d\u5185\u79d1, <sup>5<\/sup>\u56fd\u7acb\u304c\u3093\u7814\u7a76\u30bb\u30f3\u30bf\u30fc\u6771\u75c5\u9662\u982d\u9838\u90e8\u5185\u79d1, <sup>6<\/sup>\u56fd\u7acb\u304c\u3093\u7814\u7a76\u30bb\u30f3\u30bf\u30fc\u6771\u75c5\u9662\u6d88\u5316\u7ba1\u5185\u79d1, <sup>7<\/sup>\u6771\u4eac\u5927\u5b66\u65b0\u9818\u57df\u5275\u6210\u79d1\u5b66\u7814\u7a76\u79d1\u30e1\u30c7\u30a3\u30ab\u30eb\u60c5\u5831\u751f\u547d\u5c02\u653b)<\/p>\n\n\n\n<h4 class=\"wp-block-heading\">\u30cf\u30a4\u30e9\u30a4\u30c8\u30c8\u30e9\u30c3\u30af<\/h4>\n\n\n\n<p><strong>HT-403<\/strong><br>SSBD: a public bioimaging data platform for advanced image analysis<br>SSBD: \u751f\u7269\u753b\u50cf\u89e3\u6790\u3068\u5171\u6709\u3092\u4fc3\u9032\u3059\u308b\u30c7\u30fc\u30bf\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0<br>\u4eac\u7530 \u8015\u53f8<sup>1<\/sup>, \u7cf8\u8cc0 \u88d5\u5f25<sup>1<\/sup>, \u5c71\u7e23 \u53cb\u7d00<sup>2,3<\/sup>, \u85e4\u6fa4 \u7d75\u7f8e<sup>1<\/sup>, \u5c71\u672c \u6625\u83dc<sup>1<\/sup>, \u83c5\u539f \u7693<sup>1<\/sup>, \u30a6\u30a7\u30f3 \u30c1\u30a7\u30f3\u30bf\u30aa<sup>1<\/sup>, \u5927\u6d6a \u4fee\u4e00<sup>1,2<\/sup>&nbsp; (<sup>1<\/sup>\u7406\u5316\u5b66\u7814\u7a76\u6240\u751f\u547d\u6a5f\u80fd\u79d1\u5b66\u7814\u7a76\u30bb\u30f3\u30bf\u30fc, <sup>2<\/sup>\u7406\u5316\u5b66\u7814\u7a76\u6240\u60c5\u5831\u7d71\u5408\u672c\u90e8, <sup>3<\/sup>\u7406\u5316\u5b66\u7814\u7a76\u6240\u30d0\u30a4\u30aa\u30ea\u30bd\u30fc\u30b9\u7814\u7a76\u30bb\u30f3\u30bf\u30fc)<\/p>\n\n\n\n<h4 class=\"wp-block-heading\">\u53e3\u982d\u767a\u8868<\/h4>\n\n\n\n<p><strong>OS-404<\/strong> \/ PO-166<br>Unsupervised annotation of spatial transcriptomes based on vectorial information<br>\u30d9\u30af\u30c8\u30eb\u60c5\u5831\u306b\u57fa\u3065\u304f\u7a7a\u9593\u30c8\u30e9\u30f3\u30b9\u30af\u30ea\u30d7\u30c8\u30fc\u30e0\u306e\u6559\u5e2b\u306a\u3057\u30a2\u30ce\u30c6\u30fc\u30b7\u30e7\u30f3<br>\u91ce\u6751 \u4eae\u8f14<sup>1,2<\/sup>, \u9152\u4e95 \u4fca\u8f14<sup>1,3<\/sup>, \u5f71\u5c71 \u4fca\u4e00\u90ce<sup>1<\/sup>, \u5c71\u4e0b \u7406\u5b87<sup>1,2<\/sup>&nbsp; (<sup>1<\/sup>\u56fd\u7acb\u304c\u3093\u7814\u7a76\u30bb\u30f3\u30bf\u30fc\u3000\u5148\u7aef\u533b\u7642\u958b\u767a\u30bb\u30f3\u30bf\u30fc\u3000\u30c8\u30e9\u30f3\u30b9\u30ec\u30fc\u30b7\u30e7\u30ca\u30eb\u30a4\u30f3\u30d5\u30a9\u30de\u30c6\u30a3\u30af\u30b9\u5206\u91ce, <sup>2<\/sup>\u6771\u4eac\u5927\u5b66\u5927\u5b66\u9662\u3000\u65b0\u9818\u57df\u5275\u6210\u79d1\u5b66\u7814\u7a76\u79d1\u3000\u30e1\u30c7\u30a3\u30ab\u30eb\u60c5\u5831\u751f\u547d\u5c02\u653b, <sup>3<\/sup>\u6771\u4eac\u5927\u5b66\u5927\u5b66\u9662\u3000\u65b0\u9818\u57df\u5275\u6210\u79d1\u5b66\u7814\u7a76\u79d1\u3000\u5148\u7aef\u751f\u547d\u79d1\u5b66\u5c02\u653b)<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">\u53e3\u982d\u767a\u8868\u30fb\u30cf\u30a4\u30e9\u30a4\u30c8\u30c8\u30e9\u30c3\u30af\u3000OS-5<\/h3>\n\n\n<figure class=\"wp-block-table is-style-regular\">\n<table>\n<tbody>\n<tr>\n<td style=\"background: #eeeeee; width: 100pt;\"><strong>\u65e5\u6642\u30fb\u4f1a\u5834<\/strong><\/td>\n<td>9\u67084\u65e5\uff08\u6728\uff0914\u664200\u5206\u301c15\u664230\u5206\u3000\u7b2c4\u4f1a\u5834<\/td>\n<\/tr>\n<tr>\n<td style=\"background: #eeeeee; width: 100pt;\"><strong>\u5ea7\u9577<\/strong><\/td>\n<td>\u6c38\u91ce \u60c7 (\u9f8d\u8c37\u5927\u5b66)<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/figure>\n\n\n<h4 class=\"wp-block-heading\">\u30cf\u30a4\u30e9\u30a4\u30c8\u30c8\u30e9\u30c3\u30af<\/h4>\n\n\n\n<p><strong>HT-501<br><\/strong>Vertebral count patterns across tetrapods<br>\u56db\u80a2\u52d5\u7269\u306e\u7a2e\u3092\u307e\u305f\u3050\u80cc\u9aa8\u6570\u30eb\u30fc\u30eb<br>Cerbus Rory<sup>1<\/sup> (<sup>1<\/sup>\u7406\u5316\u5b66\u7814\u7a76\u6240\u30fb\u751f\u547d\u6a5f\u80fd\u79d1\u5b66\u7814\u7a76\u30bb\u30f3\u30bf\u30fc)<\/p>\n\n\n\n<h4 class=\"wp-block-heading\">\u53e3\u982d\u767a\u8868<\/h4>\n\n\n\n<p><strong>OS-502<\/strong> \/ PO-165<br>Generative model for deciphering the relationship between mtDNA genotype and phenotypic heterogeneity<br>cloneVI:mtDNA\u591a\u69d8\u6027\u3068\u8868\u73fe\u578b\u4e0d\u5747\u4e00\u6027\u306e\u9023\u95a2\u3092\u8aad\u307f\u89e3\u304f\u305f\u3081\u306e\u6df1\u5c64\u751f\u6210\u30e2\u30c7\u30eb<br>\u65e5\u6bd4 \u592a\u667a<sup>1,2,3<\/sup>, \u5c0f\u5d8b \u6cf0\u5f18<sup>2<\/sup>, \u5cf6\u6751 \u5fb9\u5e73<sup>3<\/sup>&nbsp; (<sup>1<\/sup>\u540d\u53e4\u5c4b\u5927\u5b66\u5927\u5b66\u9662\u533b\u5b66\u7cfb\u7814\u7a76\u79d1\u7dcf\u5408\u533b\u5b66\u5c02\u653b\u30c7\u30fc\u30bf\u99c6\u52d5\u751f\u7269\u5b66\u5206\u91ce, <sup>2<\/sup>\u56fd\u7acb\u304c\u3093\u7814\u7a76\u30bb\u30f3\u30bf\u30fc\u7814\u7a76\u6240\u8a08\u7b97\u751f\u547d\u79d1\u5b66\u30e6\u30cb\u30c3\u30c8, <sup>3<\/sup>\u6771\u4eac\u79d1\u5b66\u5927\u5b66\u96e3\u6cbb\u75be\u60a3\u7814\u7a76\u6240\u8a08\u7b97\u30b7\u30b9\u30c6\u30e0\u751f\u7269\u5b66\u5206\u91ce)<\/p>\n\n\n\n<p><strong>OS-503<\/strong> \/ PO-168<br>Rewinding Time to Trace the Cooperative Evolution of Genes and Transcriptional Regulation<br>\u6642\u9593\u306e&#8221;\u5dfb\u304d\u623b\u3057&#8221;\u306b\u3088\u308b\u907a\u4f1d\u5b50\u3068\u8ee2\u5199\u5236\u5fa1\u306e\u5354\u8abf\u7684\u9032\u5316\u306e\u89e3\u660e<br>\u539f \u96c4\u4e00\u90ce<sup>1,2<\/sup>, \u5409\u6ca2 \u76f4\u5b50<sup>2<\/sup>, \u590f\u76ee \u8c4a\u5f70<sup>2<\/sup>, \u548c\u7530 \u6dbc\u5b50<sup>2<\/sup>, \u8c4a\u7530 \u6566<sup>3<\/sup>, \u5ddd\u8def \u82f1\u54c9<sup>2<\/sup>&nbsp; (<sup>1<\/sup>\u5317\u91cc\u5927\u5b66 \u672a\u6765\u5de5\u5b66\u90e8, <sup>2<\/sup>\u6771\u4eac\u90fd\u533b\u5b66\u7dcf\u5408\u7814\u7a76\u6240 \u30b2\u30ce\u30e0\u533b\u5b66\u7814\u7a76\u30bb\u30f3\u30bf\u30fc, <sup>3<\/sup>\u56fd\u7acb\u907a\u4f1d\u5b66\u7814\u7a76\u6240)<\/p>\n\n\n\n<p><strong>OS-504<\/strong> \/ PO-155<br>SlopeSearch: an improved slope-based alignment-free method for genome<br>SlopeSearch: \u30b2\u30ce\u30e0\u985e\u4f3c\u6027\u691c\u7d22\u306e\u305f\u3081\u306e\u659c\u7387\u30d9\u30fc\u30b9\u975e\u30a2\u30e9\u30a4\u30e1\u30f3\u30c8\u6cd5\u306e\u6539\u826f\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0<br>CHEN YE<sup>1<\/sup>, Frith Martin<sup>1<\/sup> (<sup>1<\/sup>The University of Tokyo)<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">\u53e3\u982d\u767a\u8868\u30fb\u30cf\u30a4\u30e9\u30a4\u30c8\u30c8\u30e9\u30c3\u30af\u3000OS-6<\/h3>\n\n\n<figure class=\"wp-block-table is-style-regular\">\n<table>\n<tbody>\n<tr>\n<td style=\"background: #eeeeee; width: 100pt;\"><strong>\u65e5\u6642\u30fb\u4f1a\u5834<\/strong><\/td>\n<td>9\u67084\u65e5\uff08\u6728\uff0915\u664240\u5206\u301c17\u664210\u5206\u3000\u7b2c3\u4f1a\u5834<\/td>\n<\/tr>\n<tr>\n<td style=\"background: #eeeeee; width: 100pt;\"><strong>\u5ea7\u9577<\/strong><\/td>\n<td>\u5c71\u4e0b \u7406\u5b87 (\u56fd\u7acb\u304c\u3093\u7814\u7a76\u30bb\u30f3\u30bf\u30fc)<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/figure>\n\n\n<h4 class=\"wp-block-heading\">\u30cf\u30a4\u30e9\u30a4\u30c8\u30c8\u30e9\u30c3\u30af<\/h4>\n\n\n\n<p><strong>HT-601<br><\/strong>Body mass index stratification optimizes polygenic prediction of type 2 diabetes in cross-biobank analyses<br>BMI\u5c64\u5225\u5316\u306b\u3088\u308a2\u578b\u7cd6\u5c3f\u75c5\u306e\u907a\u4f1d\u7684\u4e88\u6e2c\u7cbe\u5ea6\u304c\u6700\u9069\u5316\u3055\u308c\u308b\u3053\u3068\u3092\u793a\u3057\u305f\u30d0\u30a4\u30aa\u30d0\u30f3\u30af\u6a2a\u65ad\u7684\u7814\u7a76<br>\u5c0f\u5d8b \u5d07\u53f2<sup>1,2,3,4<\/sup>, \u96e3\u6ce2 \u771f\u4e00<sup>1,2,3<\/sup>, \u9234\u6728 \u9855<sup>1,2<\/sup>, \u5c71\u672c \u8ce2\u4e00<sup>2<\/sup>, \u66fd\u6839\u539f \u7a76\u4eba<sup>1,2,3<\/sup>, \u6210\u7530 \u6681<sup>3,4<\/sup>, \u6771\u5317\u30e1\u30c7\u30a3\u30ab\u30eb \u30e1\u30ac\u30d0\u30f3\u30af<sup>4<\/sup>, \u30d0\u30a4\u30aa\u30d0\u30f3\u30af \u30b8\u30e3\u30d1\u30f3<sup>1<\/sup>, \u938c\u8c37 \u6d0b\u4e00\u90ce<sup>1<\/sup>, \u7530\u5bae \u5143<sup>3,4<\/sup>, \u5c71\u672c \u96c5\u4e4b<sup>4<\/sup>, \u5c71\u5185 \u654f\u6b63<sup>1<\/sup>, \u9580\u8107 \u5b5d<sup>5<\/sup>, \u5ca1\u7530 \u96a8\u8c61<sup>1,2,3<\/sup> (<sup>1<\/sup>\u6771\u4eac\u5927\u5b66, <sup>2<\/sup>\u5927\u962a\u5927\u5b66, <sup>3<\/sup>\u7406\u5316\u5b66\u7814\u7a76\u6240, <sup>4<\/sup>\u6771\u5317\u5927\u5b66, <sup>5<\/sup>\u864e\u306e\u9580\u75c5\u9662)<\/p>\n\n\n\n<h4 class=\"wp-block-heading\">\u53e3\u982d\u767a\u8868<\/h4>\n\n\n\n<p><strong>OS-602<\/strong> \/ PO-154<br>Multimodal Gene\u2013Environment Modeling of Disease Onset Using a Context-Aware Genome Language Model<br>\u30b2\u30ce\u30e0\u8a00\u8a9e\u30e2\u30c7\u30eb\u3092\u7528\u3044\u305f\u75be\u60a3\u767a\u75c7\u306b\u304a\u3051\u308b\u500b\u5225\u907a\u4f1d\u30fb\u74b0\u5883\u76f8\u4e92\u4f5c\u7528\u306e\u30de\u30eb\u30c1\u30e2\u30fc\u30c0\u30eb\u89e3\u6790<br>\u6afb\u6728 \u5b9f<sup>1<\/sup>, \u6d45\u7530 \u68a8\u6e56<sup>1<\/sup>, \u938c\u7530 \u771f\u7531\u7f8e<sup>2<\/sup>, \u5965\u91ce \u606d\u53f2<sup>1<\/sup>&nbsp; (<sup>1<\/sup>\u4eac\u90fd\u5927\u5b66\u5927\u5b66\u9662\u533b\u5b66\u7814\u7a76\u79d1\u30d3\u30c3\u30b0\u30c7\u30fc\u30bf\u533b\u79d1\u5b66, <sup>2<\/sup>\u5317\u91cc\u5927\u5b66\u672a\u6765\u5de5\u5b66\u90e8)<\/p>\n\n\n\n<p><strong>HT-603<\/strong> \/ PO-048<br>ChIP-Atlas 3.0: a data-mining suite to explore chromosome architecture together with large-scale regulome data<br>ChIP-Atlas 3.0: \u67d3\u8272\u4f53\u69cb\u9020\u60c5\u5831\u3092\u7db2\u7f85\u3057\u305f\u30a8\u30d4\u30b2\u30ce\u30df\u30af\u30b9\u30c7\u30fc\u30bf\u30d9\u30fc\u30b9<br>\u6c96 \u771f\u5f25<sup>1<\/sup>&nbsp; (<sup>1<\/sup>\u718a\u672c\u5927\u5b66)<\/p>\n\n\n\n<p><strong>OS-604<\/strong> \/ PO-170<br>Decoding genomic and epigenomic diversity of transposable elements in brain<br>\u30d2\u30c8\u6b7b\u5f8c\u8133\u306b\u304a\u3051\u308b\u8ee2\u79fb\u56e0\u5b50\u306eGenetic\/Epigenetic\u306a\u591a\u69d8\u6027\u306e\u89e3\u6790<br>\u6e21\u908a \u7406\u7d17<sup>1 <\/sup>&nbsp;(<sup>1<\/sup>\u30de\u30a6\u30f3\u30c8\u30b5\u30a4\u30ca\u30a4\u533b\u79d1\u5927\u5b66, <sup>2<\/sup>\u30ab\u30ea\u30d5\u30a9\u30eb\u30cb\u30a2\u5927\u5b66\u30ed\u30b5\u30f3\u30bc\u30eb\u30b9\u6821)<\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u8b1b\u6f14\u8005\u3078\u306e\u3054\u6848\u5185 \u53e3\u982d\u767a\u8868\u30fb\u30cf\u30a4\u30e9\u30a4\u30c8\u30c8\u30e9\u30c3\u30af\u3000OS-1 \u65e5\u6642\u30fb\u4f1a\u5834 9\u67083\u65e5\uff08\u6c34\uff0913\u664240\u5206\u301c15\u664210\u5206\u3000\u7b2c3\u4f1a\u5834 \u5ea7\u9577 \u7b20\u539f \u6d69\u592a (\u65e5\u672c\u305f\u3070\u3053\u7523\u696d\u682a\u5f0f\u4f1a\u793e \u533b\u85ac\u7dcf\u5408\u7814\u7a76\u6240) \u30cf\u30a4\u30e9\u30a4\u30c8\u30c8\u30e9\u30c3\u30af HT-101 \/ [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"vkexunit_cta_each_option":"","footnotes":""},"class_list":["post-1653","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/www.jsbi.org\/iibmp2025\/wp-json\/wp\/v2\/pages\/1653","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.jsbi.org\/iibmp2025\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.jsbi.org\/iibmp2025\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.jsbi.org\/iibmp2025\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.jsbi.org\/iibmp2025\/wp-json\/wp\/v2\/comments?post=1653"}],"version-history":[{"count":8,"href":"https:\/\/www.jsbi.org\/iibmp2025\/wp-json\/wp\/v2\/pages\/1653\/revisions"}],"predecessor-version":[{"id":1780,"href":"https:\/\/www.jsbi.org\/iibmp2025\/wp-json\/wp\/v2\/pages\/1653\/revisions\/1780"}],"wp:attachment":[{"href":"https:\/\/www.jsbi.org\/iibmp2025\/wp-json\/wp\/v2\/media?parent=1653"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}