Neuroinformatics: An Introduction

Neuroinformatics: An Introduction

The challenges in neuroinformatics


  • Challenges in making neuroinformatics databases and tools (Morse, 2008)
    • The variety in spatial scales
    • Various data types
    • Traditional bioinformatics concentrates on
      • Genomic and proteomic data
      • Sequences (DNA, RNA, and protein molecules)
      • Development of the databases of
        • Interactions between proteins
        • The evolution of genes
        • Systems biology
  •  Other challenges (Bloom et al., 2006)
    • To improve the mapping gene expression patterns in the mouse brain
    • To analyze the phenotypic alterations in the genetic models of human brain diseases

The goals of neuroinformatics studies

  • Neuroinformatics goals (Morse, 2008)
    • To support the study of the nervous system
      • Normal functions
      • Neurological disorders
  • To develop web-accessible databases
  • To develop software tools
  • The requirements for neuroinformatics (Eckersley et al., 2003)
    • Technical requirements
      • The hardware
      • The software
      • The protocols
  • The legal and policy frameworks
  • To solve the cultural and legal problems
  • Legal strategies by the Free Software community
  • “Open science” uses for data
  • Flexible licensing for secondary commercial studies

The contents in neuroinformatics

  • Neuroinformatics studies include (Morse, 2008)
    • Traditional bioinformatics analyses of the brain gene and protein sequences
    • The localization of genes and proteins in the brain
    • The brain anatomy
    • Imaging of the brain cells
    • Brain imaging analyses via
      • Positron emission tomography (PET)
      • Functional magnetic resonance imaging (fMRI)
      • Electroencephalography (EEG)
      • Magnetoencephalography (MEG)
  • The analyses via electrophysiological recording approaches
  • The mining of clinical neurological data
  • The tools for studying the brain-related diseases (Bloom et al., 2006)
    • Central nervous system diseases
      • A main category of drug targets
  • Mouse models of Amyotrophic Lateral Sclerosis and Alzheimer’s disease
    • May be helpful for drug development
    • Can help with the study of
      • Abnormal behaviors
      • Cognition
      • Emotions
  • The analyses of the genes expressed in the nervous system
    • At least half of the mammalian genome
  • Applications of neuroinformatics (Grisham et al., 2010)
    • From the phenotypic level to the molecular level
    • Neuroanatomy and histology
    • Quantitative trait locus analysis
    • In situ hybridization and microarray analysis
    • Data mining of
      • The region(s) of chromosome(s) involving the phenotypic traits
      • Candidate genes
      • The in situ patterns
      • The nucleotide sequences

Neuroinformatics: the integration and associations with medical informatics and bioinformatics (Wiemer et al., 2003)

  • Intersections among
    • Neuroinformatics
    • Medical informatics
    • Bioinformatics
    • Common grounds in the techniques and solutions
      • The modeling of neurophysiological systems for the development of medical treatment
      • Medical computer vision for the image processing applications
      • For the studies of the dynamics of cell nuclei
      • Using neuroinformatics tools for bioinformatics data mining
      • For the studies in clinical oncology
      • The bidirectional transfers of knowledge and techniques
        • To improve efficiency and accuracy
        • Clinical decision support systems from neuroinformatics and bioinformatics may lead to
          • Better diagnostics
          • Personalized medicine

Relevant bioinformatics resources (Grisham et al., 2010)




Bloom, F. E., Morrison, J. H., & Young, W. G. (2006). Neuroinformatics: a new tool for studying the brain. Journal of affective disorders, 92(1), 133–138. doi:10.1016/j.jad.2005.12.043


Eckersley, P., Egan, G. F., Amari, S., Beltrame, F., Bennett, R., Bjaalie, J. G., Dalkara, T., et al. (2003). Neuroscience data and tool sharing: a legal and policy framework for neuroinformatics. Neuroinformatics, 1(2), 149–165. Retrieved from


Grisham, W., Schottler, N. A., Valli-Marill, J., Beck, L., & Beatty, J. (2010). Teaching bioinformatics and neuroinformatics by using free web-based tools. CBE life sciences education, 9(2), 98–107. doi:10.1187/cbe.09-11-0079


Morse, T. M. (2008). Neuroinformatics: from bioinformatics to databasing the brain. Bioinformatics and biology insights, 2, 253–264. Retrieved from


Wiemer, J., Schubert, F., Granzow, M., Ragg, T., Fieres, J., Mattes, J., & Eils, R. (2003). Informatics united: exemplary studies combining medical informatics, neuroinformatics and bioinformatics. Methods of information in medicine, 42(2), 126–133. doi:10.1267/METH03020126



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