Abstract Systemic analysis of available large-scale biological and biomedical data is critical for developing novel and effective treatment approaches against both complex and infectious diseases. Owing to the fact that different sections of the biomedical data is produced by different organizations/institutions using various types of technologies, the data are scattered across individual computational resources, without any explicit relations/connections to each other, which greatly hinders the comprehensive multi-omics-based analysis of data. We aimed to address this issue by constructing a new biological and biomedical data resource, CROssBAR, a comprehensive system that integrates large-scale biomedical data from various resources and store them in a new NoSQL database, enrich these data with deep-learning-based prediction of relations between numerous biomedical entities, rigorously analyse the enriched data to obtain biologically meaningful modules and display them to users via easy-to-interpret, interactive and heterogenous knowledge graph (KG) representations within an open access, user-friendly and online web-service at https://crossbar.kansil.org . As a use-case study, we constructed CROssBAR COVID-19 KGs (available at: https://crossbar.kansil.org/covid_main.php ) that incorporate relevant virus and host genes/proteins, interactions, pathways, phenotypes and other diseases, as well as known and completely new predicted drugs/compounds. Our COVID-19 graphs can be utilized for a systems-level evaluation of relevant virus-host protein interactions, mechanisms, phenotypic implications and potential interventions.

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virus and host genesproteins interactions pathways phenotypes covid19 graphs system predicted easytointerpret interactive and heterogenous knowledge graph kg representations modules deeplearningbased prediction of relations treatment systemic analysis of available largescale biological and biomedical data systemslevel evaluation of virushost protein interactions mechanisms phenotypic implications interventions crossbar covid19 kgs available at httpscrossbarkansilorgcovidmainphp

Nalbat, Esra, Atakan, Ahmet, Joshi, Vishal, Atalay, Volkan, Rifaioglu, Ahmet Sureyya, Martin, Maria, Zellner, Hermann,Doğan, Tunca, Saidi, Rabie, Volynkin, Vladimir, Cetin-Atalay, Rengul, Atas, Heval, Nightingale, Andrew,.CROssBAR: Comprehensive Resource of Biomedical Relations with Deep Learning Applications and Knowledge Graph Representations. (),.

Nalbat, Esra, et al."CROssBAR: Comprehensive Resource of Biomedical Relations with Deep Learning Applications and Knowledge Graph Representations"

Nalbat, Esra, Atakan, Ahmet, Joshi, Vishal, Atalay, Volkan, Rifaioglu, Ahmet Sureyya, Martin, Maria, Zellner, Hermann,Doğan, Tunca, Saidi, Rabie, Volynkin, Vladimir, Cetin-Atalay, Rengul, Atas, Heval, Nightingale, Andrew,"CROssBAR: Comprehensive Resource of Biomedical Relations with Deep Learning Applications and Knowledge Graph Representations"