Graph4Med: a web application and a graph database for visualizing and analyzing medical databases
- Background: Medical databases normally contain large amounts of data in a variety of forms. Although they grant significant insights into diagnosis and treatment, implementing data exploration into current medical databases is challenging since these are often based on a relational schema and cannot be used to easily extract information for cohort analysis and visualization. As a consequence, valuable information regarding cohort distribution or patient similarity may be missed. With the rapid advancement of biomedical technologies, new forms of data from methods such as Next Generation Sequencing (NGS) or chromosome microarray (array CGH) are constantly being generated; hence it can be expected that the amount and complexity of medical data will rise and bring relational database systems to a limit. Description: We present Graph4Med, a web application that relies on a graph database obtained by transforming a relational database. Graph4Med provides a straightforward visualization and analysis of a selected patient cohort. Our use case is a database of pediatric Acute Lymphoblastic Leukemia (ALL). Along routine patients’ health records it also contains results of latest technologies such as NGS data. We developed a suitable graph data schema to convert the relational data into a graph data structure and store it in Neo4j. We used NeoDash to build a dashboard for querying and displaying patients’ cohort analysis. This way our tool (1) quickly displays the overview of patients’ cohort information such as distributions of gender, age, mutations (fusions), diagnosis; (2) provides mutation (fusion) based similarity search and display in a maneuverable graph; (3) generates an interactive graph of any selected patient and facilitates the identification of interesting patterns among patients. Conclusion: We demonstrate the feasibility and advantages of a graph database for storing and querying medical databases. Our dashboard allows a fast and interactive analysis and visualization of complex medical data. It is especially useful for patients similarity search based on mutations (fusions), of which vast amounts of data have been generated by NGS in recent years. It can discover relationships and patterns in patients cohorts that are normally hard to grasp. Expanding Graph4Med to more medical databases will bring novel insights into diagnostic and research.
Author: | Jero SchäferORCiD, Ming Tang, Danny LuuGND, Anke Katharina BergmannGND, Lena WieseORCiDGND |
---|---|
URN: | urn:nbn:de:hebis:30:3-863630 |
DOI: | https://doi.org/10.1186/s12859-022-05092-0 |
ISSN: | 1471-2105 |
Parent Title (English): | BMC Bioinformatics |
Publisher: | BioMed Central , Springer |
Place of publication: | London ; Berlin ; Heidelberg |
Document Type: | Article |
Language: | English |
Date of Publication (online): | 2022/12/12 |
Date of first Publication: | 2022/12/12 |
Publishing Institution: | Universitätsbibliothek Johann Christian Senckenberg |
Release Date: | 2024/07/17 |
Tag: | Data exploration; Graph database; Medical database; Visualization; Web application |
Volume: | 23.2022 |
Issue: | art. 537 |
Article Number: | 537 |
Page Number: | 22 |
First Page: | 1 |
Last Page: | 22 |
Note: | Open Access funding enabled and organized by Projekt DEAL. |
Note: | Funding: Else Kröner-Fresenius-Stiftung ; DigiStrucMed 2020_EKPK.20 |
Note: | Funding: BMBF ; 01DD20003 |
Note: | Gefördert durch den Open-Access-Publikationsfonds der Goethe-Universität. |
Note: | The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
Note: | The clinical data used in our approach are not shared due to the preservation of the patients’ privacy. A public demonstrator with artificial data can be found on the Graph4Med website. Source code is located in the project repository. |
HeBIS-PPN: | 520903013 |
Institutes: | Informatik und Mathematik / Informatik |
Dewey Decimal Classification: | 0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik |
5 Naturwissenschaften und Mathematik / 57 Biowissenschaften; Biologie / 570 Biowissenschaften; Biologie | |
6 Technik, Medizin, angewandte Wissenschaften / 61 Medizin und Gesundheit / 610 Medizin und Gesundheit | |
Sammlungen: | Universitätspublikationen |
Open-Access-Publikationsfonds: | Informatik und Mathematik |
Licence (German): | Creative Commons - CC BY - Namensnennung 4.0 International |