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INetModels 2.0: An interactive visualization and database of multi-omics data

Research output: Contribution to journalArticlepeer-review

Muhammad Arif, Cheng Zhang, Xiangyu Li, Cem Güngör, Buǧra Çakmak, Metin Arslantürk, Abdellah Tebani, Berkay Özcan, Oǧuzhan Subaş, Wenyu Zhou, Brian Piening, Hasan Turkez, Linn Fagerberg, Nathan Price, Leroy Hood, Michael Snyder, Jens Nielsen, Mathias Uhlen, Adil Mardinoglu

Original languageEnglish
Pages (from-to)W271-W276
JournalNucleic Acids Research
Issue numberW1
Published2 Jul 2021

Bibliographical note

Publisher Copyright: © 2021 The Author(s) 2021. Published by Oxford University Press on behalf of Nucleic Acids Research. Copyright: Copyright 2021 Elsevier B.V., All rights reserved.

King's Authors


It is essential to reveal the associations between various omics data for a comprehensive understanding of the altered biological process in human wellness and disease. To date, very few studies have focused on collecting and exhibiting multi-omics associations in a single database. Here, we present iNetModels, an interactive database and visualization platform of Multi-Omics Biological Networks (MOBNs). This platform describes the associations between the clinical chemistry, anthropometric parameters, plasma proteomics, plasma metabolomics, as well as metagenomics for oral and gut microbiome obtained from the same individuals. Moreover, iNetModels includes tissue- and cancer-specific Gene Co-expression Networks (GCNs) for exploring the connections between the specific genes. This platform allows the user to interactively explore a single feature's association with other omics data and customize its particular context (e.g. male/female specific). The users can also register their data for sharing and visualization of the MOBNs and GCNs. Moreover, iNetModels allows users who do not have a bioinformatics background to facilitate human wellness and disease research. iNetModels can be accessed freely at without any limitation.

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