BioUML—towards a universal research platform

Author:

Kolpakov Fedor123ORCID,Akberdin Ilya145ORCID,Kiselev Ilya123,Kolmykov Semyon14,Kondrakhin Yury24,Kulyashov Mikhail4,Kutumova Elena12,Pintus Sergey1,Ryabova Anna1,Sharipov Ruslan145ORCID,Yevshin Ivan14,Zhatchenko Sergey14,Kel Alexander46

Affiliation:

1. Sirius University of Science and Technology , Sochi 354340, Russian Federation

2. Federal Research Center for Information and Computational Technologies , Novosibirsk 630090, Russian Federation

3. Budker Institute of Nuclear Physics SB RAS , Novosibirsk 630090, Russian Federation

4. Biosoft.ru, LLC , Novosibirsk 630058, Russian Federation

5. Novosibirsk State University , Novosibirsk 630090, Russian Federation

6. geneXplain GmbH , Wolfenbüttel 38302, Germany

Abstract

AbstractBioUML (https://www.biouml.org)—is a web-based integrated platform for systems biology and data analysis. It supports visual modelling and construction of hierarchical biological models that allow us to construct the most complex modular models of blood pressure regulation, skeletal muscle metabolism, COVID-19 epidemiology. BioUML has been integrated with git repositories where users can store their models and other data. We have also expanded the capabilities of BioUML for data analysis and visualization of biomedical data: (i) any programs and Jupyter kernels can be plugged into the BioUML platform using Docker technology; (ii) BioUML is integrated with the Galaxy and Galaxy Tool Shed; (iii) BioUML provides two-way integration with R and Python (Jupyter notebooks): scripts can be executed on the BioUML web pages, and BioUML functions can be called from scripts; (iv) using plug-in architecture, specialized viewers and editors can be added. For example, powerful genome browsers as well as viewers for molecular 3D structure are integrated in this way; (v) BioUML supports data analyses using workflows (own format, Galaxy, CWL, BPMN, nextFlow). Using these capabilities, we have initiated a new branch of the BioUML development—u-science—a universal scientific platform that can be configured for specific research requirements.

Funder

Russian Science Foundation

Sirius University

Publisher

Oxford University Press (OUP)

Subject

Genetics

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