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Combining Neuroinformatics Databases for Multi-Level Analysis of Brain Disorders Interdisciplinary Bio Central Open Access IBC 2012;4:7, 1-8 • DOI: 10.4051/ibc.2012.4.3.0007 REVIEW Combining Neuroinformatics Databases for Multi-Level Analysis of Brain Disorders Ha Sun Yu1, Joon Bang2, Yousang Jo1 and Doheon Lee1,* 1Department of Bio and Brain Engineering, KAIST, Daejeon, Korea 2Winchester College, College Street, Winchester, UK Subject areas; Biological computation/ SYNOPSIS Database Author contribution; H.S.Y. writing and design With the development of many methods of studying the brain, the field of neuroscience of the manuscript; J.B. writing part of ‘brain has generated large amounts of information obtained from various techniques: imaging imaging databases’, ‘electrophysiological techniques, electrophysiological techniques, techniques for analyzing brain connectivity, databases’, and ‘databases of genetic information of brain’; Y.J. writing part of ‘brain techniques for getting molecular information of the brain, etc. A plenty of neuroinfor- connectivity database’ and ‘multi-level analysis matics databases have been made for storing and sharing this useful information and combining different types of databases’; D.L. those databases can be publicly accessed by researchers as needed. However, since there study design, management, and advice of the are too many neuroinformatics databases, it is difficult to find the appropriate database study and manuscript writing. depending on the needs of researcher. Moreover, many researchers in neuroscience fields *Correspondence and requests for materials are unfamiliar with using neuroinformatics databases for their studies because data is should be addressed to D.L. ([email protected]). too diverse for neuroscientists to handle this and there is little precedent for using neu- Editor; Keun Woo Lee, Gyeongsang National roinformatics databases for their research. Therefore, in this article, we review databases University, Korea in the field of neuroscience according to both their methods for obtaining data and their Received August 02, 2012 objectives to help researchers to use databases properly. We also introduce major neuro- Accepted August 10, 2012 informatics databases for each type of information. In addition, to show examples of Published August 10, 2012 novel uses of neuroinformatics databases, we represent several studies that combine Citation; Yu, H.S., et al. Combining neuroinformatics databases of different information types and discover new findings. Neuroinformatics Databases for Multi-Level Analysis of Brain Disorders. IBC 2012, 4:7, 1-8. Finally, we conclude our paper with the discussion of potential applications of neuroin- doi: 10.4051/ibc.2012.4.3.0007 formatics databases. Funding; This work was supported by the National Research Foundation of Korea funded by the Korea Government, Ministry of Education, Science and Technology through the WCU (World Class University) program (R32-2008- 000-10218-0) and Basic Research Laboratory Genomic Structural imaging grant (2009-0086964). It was also supported by information (NGS, (MRI, CT, EM, etc.) the KISTI (Korea Institute of Science and etc.) Functional imaging Technology Information). Genomic (fMRI, PET, etc.) Data type information Competing interest; All authors declare no (Microarray, etc.) Electrophysiological information (EEG, MEG, etc.) financial or personal conflict that could inappropriately bias their experiments or Proteomic Microconnectome Macroconnectome information (EM, etc.) (fMRI, DTI, etc.) writing. (ELISA, etc.) Molecular level Brain regional level (small scale) (large scale) Data scale DNA, RNA, Neurons Brain regions Proteins © Yu, HS. et al. This is an Open Access article distrib- uted under the terms of the Creative Commons At- tribution Non-Commercial License (http://creative- commons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and Key Words: neuroscience; database; neuroinformatics databases; usages of neuroin- reproduction in any medium, provided the original work is properly cited. formatics databases; application of neuroinformatics databases www.ibc7.org 1 IBC 2012;4:7 • DOI: 10.4051/ibc.2012.4.3.0007 Interdisciplinary Bio Central Yu HS, et al. INTRODUCTION physiological databases; brain connectivity databases; genetic databases and represent the latest useful neuroinformatics da- Brain is one of the most complex organs in our body and it has tabases (Table 1). We also present databases related to brain been studied for a long time in the field of neuroscience. Re- disorders such as Alzheimer’s diseases, Parkinson’s disease, searchers have studied the brain using various technologies schizophrenia, depression, and bipolar disorder (Table 2). In (Figure 1): magnetic resonance imaging (MRI), functional mag- addition, we introduce several studies integrating databases of netic resonance imaging (fMRI), and computerized tomogra- multi-level information to show potential application of neuro- phy (CT) to study functions, connectivity, and structures of the informatics databases. Our review will aid researchers in using brain; microarray, in situ hybridization (ISH), and next genera- neuroinformatics databases in their research. tion sequencing (NGS) to study the molecular state of the brain; Brain imaging, electrophysiology, connectivity, and genetic databases electroencephalography (EEG) and magnetoencephalography Table 1. (MEG) to study the electrophysiology of the brain. Each tech- Database URL Data type nology has its own pros and cons to study the brain, and re- Brain-development. http://www.brain-development.org/ Structural images, org functional images searchers have used these technologies based on the objective Brainmusuem.org http://www.brainmuseum.org/ Structural images of their research. A large amount of studies and data for neuro- Harvard whole brain http://www.med.harvard.edu/AANLIB/ Structural images, science has been produced using these technologies and has atlas home.html functional images been opened to the public with the establishment of databases. BrainMap.org http://brainmap.org/ Structural images, functional images However, too many neuroinformatics databases have been BrainMaps.org http://brainmaps.org/ Structural images, generated. Furthermore, many neuroscientists are not familiar functional images with using those databases for their research. NeuroMorpho.org http://neuromorpho.org/neuroMorpho/ 3D model images index.jsp To give a guideline of databases related to neuroscience fields, CARMEN Project http://www.carmen.org.uk/ Neurophysiological called neuroinformatics databases, some researchers reviewed data 1-4 neuroinformatics databases . For example, Leon French et al. CRNCS http://crcns.org/ Neurophysiological recently reviewed the application of informatics to neurosci- data ence and several useful neuroinformatics databases3. However, Open Connectome http://openconnecto.me/ Microconnectome, Project macroconnectome since much time has passed after their reviews, there have been CoCoMac http://www.cocomac.org/ Macroconnectome a lot of new studies of neuroscience, and many databases have BAMS http://brancusi.usc.edu/bkms/ Macroconnectome been newly established and updated. Furthermore, they did UCLA-MCD http://umcd.humanconnectomeproject. Macroconnectome not review neuroinformatics databases related to diseases of org/ Gene Expression http://www.ncbi.nlm.nih.gov/geo/ Gene expression brains and they did not represent research using neuroinfor- Omnibus (GEO) matics databases. ArrayExpress http://www.ebi.ac.uk/arrayexpress/ Gene expression Therefore, in this review, we review neuroinformatics data- Allen Brain Atlas http://www.brain-map.org/ Gene expression, bases of various information types: imaging databases; electro- structural images Genomic Structural imaging information (NGS, (MRI, CT, EM, etc.) etc.) Functional imaging Genomic (fMRI, PET, etc.) Data type information (Microarray, etc.) Electrophysiological information (EEG, MEG, etc.) Proteomic Microconnectome Macroconnectome information (EM, etc.) (fMRI, DTI, etc.) (ELISA, etc.) Molecular level Brain regional level (small scale) (large scale) Data scale DNA, RNA, Neurons Brain regions Proteins Figure 1. Taxonomy of data in the field of neuroscience according to their types of information. www.ibc7.org 2 IBC 2012;4:7 • DOI: 10.4051/ibc.2012.4.3.0007 Interdisciplinary Bio Central Yu HS, et al. Table 2. Neuroinformatics databases related to brain disease dents, cow, and humans. This database is closely related to Database URL Data type Disease MSU brain diversity bank which is a repository containing both ADNI http://www.adni-info.org/ Structural images, Alzheimer’s disease cell stain images and Fiber Stain images for each Sagittal sec- functional images tion of the brain. MaND www.depressiondatabase. Study information Major depressive 7 Harvard whole brain atlas contains CT and MRI images for org/ (MRI, CT) disorder OASIS www.oasis-brains.org/ Structural images Dementia structural imaging and SPECT/PET images for functional imag- SMRI https://www.stanleygen- Gene expression, Schizophrenia, bi- ing. This database consists of normal brain images and brain omics.org/ DNA sequencing polar disorder, images with diseases and disorders such as cerebrovascular depression diseases, neoplastic diseases, degenerative diseases, and in- Parkinson's http://www2.cancer.ucl. Gene expression Parkinson’s disease disease ac.uk/Parkinson_Db2/ flammatory or infectious diseases. database BrainMap.org8 is a database collecting published functional PDGene http://www.pdgene.org/
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