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Methods Inf Med 2003; 42(02): 126-133
DOI: 10.1055/s-0038-1634323
Original article
Schattauer GmbH

Informatics United

Exemplary Studies Combining Medical Informatics, Neuroinformatics and Bioinformatics
J. Wiemer
1   Intelligent Bioinformatics Systems, German Cancer Research Center, Heidelberg, Germany
2   Phase-it Intelligent Solutions AG, Heidelberg, Germany
,
F. Schubert
1   Intelligent Bioinformatics Systems, German Cancer Research Center, Heidelberg, Germany
,
M. Granzow
1   Intelligent Bioinformatics Systems, German Cancer Research Center, Heidelberg, Germany
2   Phase-it Intelligent Solutions AG, Heidelberg, Germany
,
T. Ragg   *
2   Phase-it Intelligent Solutions AG, Heidelberg, Germany
,
J. Fieres
2   Phase-it Intelligent Solutions AG, Heidelberg, Germany
,
J. Mattes
1   Intelligent Bioinformatics Systems, German Cancer Research Center, Heidelberg, Germany
,
R. Eils
1   Intelligent Bioinformatics Systems, German Cancer Research Center, Heidelberg, Germany
2   Phase-it Intelligent Solutions AG, Heidelberg, Germany
› Author Affiliations
Further Information

Publication History

Publication Date:
08 February 2018 (online)

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Summary

Objectives: Medical informatics, neuroinformatics and bioinformatics provide a wide spectrum of research. Here, we show the great potential of synergies between these research areas on the basis of four exemplary studies where techniques are transferred from one of the disciplines to the other.

Methods: Reviewing and analyzing exemplary and specific projects at the intersection of medical informatics, neuroinformatics, and bioinformatics from our experience in an interdisciplinary research group. Results: Synergy emerges when techniques and solutions from medical informatics, bioinformatics, or neuroinformatics are successfully applied in one of the other disciplines. Synergy was found in 1. the modeling of neurophysiological systems for medical therapy development, 2. the use of image processing techniques from medical computer vision for the analysis of the dynamics of cell nuclei, and 3. the application of neuroinformatics tools for data mining in bioinformatics and as classifiers in clinical oncology. Conclusions: Each of the three different disciplines have delivered technologies that are readily applicable in the other disciplines. The mutual transfer of knowledge and techniques proved to increase efficiency and accuracy in a manifold of applications. In particular, we expect that clinical decision support systems based on techniques derived from neuro- and bioinformatics have the potential to improve medical diagnostics and will finally lead to a personalized delivery of healthcare.

Keywords

Medical informatics - bioinformatics - neuroinformatics - data mining - decision support systems

* current address: Dr. T. Ragg, Quantiom bioinformatics, 76356 Weingarten, Germany


 

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