The Applications and Combination of Bioinformatics, Medical informatics, and Neuroinformatics
Mental disorders and other brain disorders such as anxiety, depression, schizophrenia, and visual impairments may account for at least one third of the worldwide burden of diseases (Wittchen et al., 2011). Neuroinformatics provides the supports for neuroscience studies via the applications of databases, neuroimaging analysis tools, modeling tools, and tools to support clinical trials and data analysis. Resources for neuroinformatics organizations and communities include International Neuroinformatics Coordinating Facility (http://www.incf.org/) and The Organization for Human Brain Mapping (OHBM) (http://www.humanbrainmapping.org).
Neuroinformatics needs to be integrated with other methods such as bioinformatics, medical informatics, and public health informatics to provide efficient support for the analysis, prevention, and treatment of brain-related diseases. Medical informatics is the usage of computational technologies in healthcare and the processing of clinical data to support clinical decision making. Its major applications include clinical decision support systems. Medical informatics can be used for neurophysiological modeling. Bioinformatics utilizes mathematical and computational methods to manage and analyze biological data including genetics data. Neuroinformatics is the integration of informatics and neuroscience to support the studies of the structure and function of the brain. Major neuroinformatics applications include the processing of neuroimages, neurophysiological modeling, and artificial neural networks.
The combination of neuroinformatics and medical informatics can lead to the development of novel therapies. For example, neuroinformatics and medical informatics can be used to analyze neuroimages and cortical maps. By applying neuroinformatics concepts such as “self-organization”, computational simulations and predictions can be made for analyzing the relationships between systematic spatio-temporal tactile stimuli and the somatosensory homunculus (Wiemer et al., 2003). Such analysis may be helpful for the development of novel therapies.
Another example is the application of neuroinformatics and medical informatics methods in analyzing the functional topology and complex dynamics of the cell nucleus using three dimensional (3D) datasets (Tvarusko et al., 1999). These methods are useful for analyzing both biological and medical imaging data, such as the analyses in the field of medical computer vision (Wiemer et al., 2003).
Neuroinformatics is especially useful for data classification to provide medical decision support. In the example of cancer and clinical oncological research, the self-organizing map (SOM) method that is commonly used in neuroinformatics to analyze gene expression data and data from comparative genomic hybridization (CGH) to classify cancer subtypes (Dougherty et al., 2002; Wiemer et al., 2003).
For data mining, model prediction, and decision support, neuroinformatics and bioinformatics methods can be combined for data collection, data preprocessing, subset selection, design of classifier, model selection, neural network establishment, model training, and receiver-operating characteristic (ROC) analysis (Wiemer et al., 2003).
Bioinformatics, medical informatics, and neuroinformatics share some common technologies. They also have specific methods and features in each field. The combination and integration of these methods and technologies would be helpful for applications in both laboratory and clinical decision support, in the analysis of gene expression profiles, and in the development of personalized medicine.
Dougherty ER, Barrera J, Brun M, Kim S, Cesar RM, Chen Y, et al. Inference from clustering with application to gene-expression microarrays. J Comput Biol 2002; 9 (1): 105-26.
International Neuroinformatics Coordinating Facility [Internet]. Stockholm (SE): International Neuroinformatics Coordinating Facility; 2011 [cited 2011 Jan 3]. Available from: http://www.incf.org/
Tvarusko W, Bentele M, Misteli T, Rudolf R, Kaether C, Spector DL, et al. Time-resolved analysis and visualization of dynamic processes in living cells. Proc Natl Acad Sci USA 1999; 96 (14): 7950-5.
Wiemer J, Schubert F, Granzow M, Ragg T, Fieres J, Mattes J, Eils R. Informatics united: exemplary studies combining medical informatics, neuroinformatics and bioinformatics. Methods Inf Med. 2003;42(2):126-33.
Wittchen HU, Jacobi F, Rehm J, Gustavsson A, Svensson M, Jonsson B, et al. The size and burden of mental disorders and other disorders of the brain in Europe 2010. Eur Neuropsychopharmacol. 2011;21(9):655–679.