INetModels 2.0: An interactive visualization and database of multi-omics data
Journal article, 2021

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.


Muhammad Arif

Royal Institute of Technology (KTH)

C. Zhang

Royal Institute of Technology (KTH)

Zhengzhou University

Xiangyu Li

Royal Institute of Technology (KTH)

Cem Güngör

Bash Biotech Inc.

Buǧra Çakmak

Bash Biotech Inc.

Metin Arslantürk

Bash Biotech Inc.

Abdellah Tebani

University of Rouen

CHU Rouen Normandie

Berkay Özcan

Bash Biotech Inc.

Oǧuzhan Subaş

Bash Biotech Inc.

Wenyu Zhou

Stanford University

B. D. Piening

Providence Cancer Center

Hasan Turkez

Atatürk University

L. Fagerberg

Royal Institute of Technology (KTH)

Nathan D. Price

Institute of Molecular Systems Biology

Leroy Hood

Institute of Molecular Systems Biology

Michael P. Snyder

Stanford University

Jens B Nielsen

Chalmers, Biology and Biological Engineering, Systems and Synthetic Biology

Mathias Uhlen

Royal Institute of Technology (KTH)

Adil Mardinoglu

Royal Institute of Technology (KTH)

King's College London

Nucleic Acids Research

0305-1048 (ISSN) 1362-4962 (eISSN)

Vol. 49 W1 W271-W276

Areas of Advance

Health Engineering

Subject Categories

Bioinformatics (Computational Biology)

Human Computer Interaction

Bioinformatics and Systems Biology





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