Integrating Genomics and Clinical Data for Statistical Analysis by Using GEnome MINIng (GEMINI) and Fast Healthcare Interoperability Resources (FHIR): System Design and Implementation

Gründner J, Wolf N, Tögel L, Haller F, Prokosch HU, Christoph J (2020)

Publication Type: Journal article

Publication year: 2020

Journal

Journal of Medical Internet Research Journal of Medical Internet Research / Gunther Eysenbach

Book Volume: 22

Journal Issue: 10

DOI: 10.2196/19879

Abstract

Background: The introduction of next-generation sequencing (NGS) into molecular cancer diagnostics has led to an increase in the data available for the identification and evaluation of driver mutations and for defining personalized cancer treatment regimens. The meaningful combination of omics data, ie, pathogenic gene variants and alterations with other patient data, to understand the full picture of malignancy has been challenging.

Authors with CRIS profile

Julian Gründner Lehrstuhl für Medizinische Informatik Lars Tögel Institute of Pathology Florian Haller Professur für Diagnostische Molekularpathologie Hans-Ulrich Prokosch Lehrstuhl für Medizinische Informatik Jan Christoph Lehrstuhl für Medizinische Informatik

How to cite

APA:

Gründner, J., Wolf, N., Tögel, L., Haller, F., Prokosch, H.-U., & Christoph, J. (2020). Integrating Genomics and Clinical Data for Statistical Analysis by Using GEnome MINIng (GEMINI) and Fast Healthcare Interoperability Resources (FHIR): System Design and Implementation. Journal of Medical Internet Research, 22(10). https://doi.org/10.2196/19879

MLA:

Gründner, Julian, et al. "Integrating Genomics and Clinical Data for Statistical Analysis by Using GEnome MINIng (GEMINI) and Fast Healthcare Interoperability Resources (FHIR): System Design and Implementation." Journal of Medical Internet Research 22.10 (2020).

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