<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Zhao J</submitter><funding>Health Commission of Sichuan Province</funding><funding>Science and Technology Department of Sichuan Province</funding><funding>National Key Research and Development Program of China</funding><pagination>baaf029</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC12010968</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>2025</volume><pubmed_abstract>Due to tumor heterogeneity, a subset of patients fails to benefit from current treatment strategies. However, an integrated analysis of imaging features, genetic molecules, and clinical phenotypes can characterize tumor heterogeneity, enabling the development of more personalized treatment approaches. Despite its potential, cross-modal databases remain underexplored. To address this gap, we established a comprehensive database encompassing 9965 genes, 5449 proteins, 1121 metabolites, 283 pathways, 854 imaging features, and 73 clinical factors from colorectal cancer patients. This database identifies significantly distinct molecules and imaging features associated with clinical phenotypes and provides survival analysis based on these features. Additionally, it offers genetic molecule annota</pubmed_abstract><journal>Database : the journal of biological databases and curation</journal><pubmed_title>MIPD: Molecules, Imagings, and Clinical Phenotype Integrated Database.</pubmed_title><pmcid>PMC12010968</pmcid><funding_grant_id>2024JDHJ0039</funding_grant_id><funding_grant_id>24WSXT083</funding_grant_id><funding_grant_id>2024ZD0520500 2024ZD0520505</funding_grant_id><pubmed_authors>Wu M</pubmed_authors><pubmed_authors>Li J</pubmed_authors><pubmed_authors>Xiong M</pubmed_authors><pubmed_authors>Zhao C</pubmed_authors><pubmed_authors>Qin L</pubmed_authors><pubmed_authors>Zhang J</pubmed_authors><pubmed_authors>Wan M</pubmed_authors><pubmed_authors>Liu Q</pubmed_authors><pubmed_authors>Tu M</pubmed_authors><pubmed_authors>Yang X</pubmed_authors><pubmed_authors>Li X</pubmed_authors><pubmed_authors>Li S</pubmed_authors><pubmed_authors>Zhang Y</pubmed_authors><pubmed_authors>Fu J</pubmed_authors><pubmed_authors>Zeng F</pubmed_authors><pubmed_authors>Zhao J</pubmed_authors><pubmed_authors>Zhou J</pubmed_authors><pubmed_authors>Zhao H</pubmed_authors></additional><is_claimable>false</is_claimable><name>MIPD: Molecules, Imagings, and Clinical Phenotype Integrated Database.</name><description>Due to tumor heterogeneity, a subset of patients fails to benefit from current treatment strategies. However, an integrated analysis of imaging features, genetic molecules, and clinical phenotypes can characterize tumor heterogeneity, enabling the development of more personalized treatment approaches. Despite its potential, cross-modal databases remain underexplored. To address this gap, we established a comprehensive database encompassing 9965 genes, 5449 proteins, 1121 metabolites, 283 pathways, 854 imaging features, and 73 clinical factors from colorectal cancer patients. This database identifies significantly distinct molecules and imaging features associated with clinical phenotypes and provides survival analysis based on these features. Additionally, it offers genetic molecule annota</description><dates><release>2025-01-01T00:00:00Z</release><publication>2025 Apr</publication><modification>2026-05-30T03:16:15.186Z</modification><creation>2025-07-01T03:05:13.305Z</creation></dates><accession>S-EPMC12010968</accession><cross_references><pubmed>40257906</pubmed><doi>10.1093/database/baaf029</doi></cross_references></HashMap>