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Databasing the Brain: From Data to Knowledge (Neuroinformatics)

ISBN: 978-0-471-30921-5
480 pages
March 2005
Databasing the Brain: From Data to Knowledge (Neuroinformatics) (0471309214) cover image
Expertly edited by two pioneers in this burgeoning field, this book covers both basic principles and specific applications across a range of problems in brain research. It truly integrates neuroscience with informatics, providing a means for understanding the new analytical tools and models of neuronal functions now being developed. Each chapter offers practical guidance for applying this knowledge to current research, enhancing electronic collaborations, and formulating hypotheses.

Prize or Award

  • AAP Awards for Excellence in Professional and Scholarly Publishing, 2006
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Chapter 1. Database Needs of Neuroscience: Schema and Design (Floyd E. Bloom and Warren G. Young).

Chapter 2. Neuroanatomical Nomenclature and Ontology (Douglas M. Bowden and Mark Dubach).

Chapter 3. Neuroinformatics for Neurophysiology: The Role, Design, and Use of Databases (Daniel Gardner, Michael Abato, Kevin H. Knuth, and Adrian Robert).

Chapter 4. Persistent Collections (Reagan W. Moore).

Chapter 5. Entity-Attribute-Value Database Approaches for Heterogeneous, Evolving Neuroscience Data (Perry L. Miller, Luis Marenco, Gordon M. Shepherd, and Prakash M. Nadkarni).

Chapter 6. Data Grids (Ian Foster).

Chapter 7. Building Grid-Based Resources for Neurosciences (Maryann E. Martone, Steven T. Peltier, and Mark H. Ellisman).

Chapter 8. Visualization in Life Sciences (Donna J. Cox).

Chapter 9. Biology Workbenches(Andreia Maer, Brian Saunders, Roger Unwin, and Shankar Subramaniam).


Chapter 10. Genome to Disease (Iiris Hovatta and Carrolee Barlow).

Chapter 11. Stimulus-Dependent Regulation of Gene Expression in the Nervous System  (Colleen A. McClung and Eric J. Nestler).

Chapter 12. Cell Signaling Networks in Long-Term Potentiation (Elizabeth A. Grace, Emmanuel M. Landau, Ravi Iyengar, and Robert D. Blitzer).

Chapter 13. Genetic Analyses of Functional Connectivity in the Nervous System (Amit Etkin, Gleb Shumyatsky, Christopher J. Pittenger, and Eric R. Kandel).

Chapter 14. GeneWays: A System for Extracting, Analyzing, Visualizing, and Integrating Molecular Pathway Data (Andrey Rzhetsky, Ivan Iossifov, Tomohiro Koike, Michael Krauthammer, Pauline Kra, Mitzi Morris, Hong Yu, Pablo Ariel Duboue, Wubin Weng, John W. Wilbur, Vasileios Hatzivassiloglou, and Carol Friedman).

Chapter 15. Cellular Morphology at the Cellular Level (Christopher J. Beaver, Robert C. Cannon, and Dennis A. Turner).

Chapter 16. cellular Models (Raimond L. Winslow).

Chapter 17. Electrophysiological Models (Mark E. Nelson).

Chapter 18. Models of Neuronal Outgrowth (Duncan E. Donohue and Giorgio A. Ascoli).


Chapter 19. The Neocortical Microcircuit Database (NMDB) (Henry Markram, Xiaozhong Luo, Gilad Silberberg, Maria Toledo-Rodriguez, and Anirudh Gupta).

Chapter 20. SenseLab: A Decade of Experience with Multilevel, Multidisciplinary Neuroscience Databases (Luis Marenco, Chiquito J. Crasto, Nian Liu, Michele Migliore, Jian Liu, Thomas M. Morse, Michael L. Hines, Prakash M. Nadkarni, Perry L. Miller, and Gordon M. Shepherd).

Chapter 21. Three-Dimensional Visualization and Analysis of Wiring Patterns in the Brain: Experiments, Tools, Models,and Databases (Jan G. Bjaalie and Trygve B. Leergaard).

Chapter 22. Surface-Based Atlases and a Database of Cortical Structure and Function (David C. Van Essen, John Harwell, Donna Hanlon, and James Dickson).

Chapter 23. Brain Atlases of Normal Human Subjects (John Mazziotta).

Chapter 24. Overcoming Challenges to Sharing Neuroimagery (Kenneth Smith).

Chapter 25. Probabilistic Brain Atlases of Normal and Diseased Populations (Arthur W. Toga, Paul M. Thompson, Katherine L. Narr, and Elizabeth R. Sowell).

Chapter 26. Maximizing Information Content in Shared and Archived Neuroimaging Studies of Human Cognition (John Darrell Van Horn and Michael S. Gazzaniga).


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Stephen H. Koslow is the Director Office on Neuroinformatics, Associate Director, National Institute of Mental Health, National Institutes of Health. He also coordinates the Human Brain Project, a multi-government agency informatics initiative. He earned his PhD from the Division of Biological Sciences, Department of Pharmacology, University of Chicago. He is a fellow of the American Association for the Advancement of Science, the American College of Medical Informatics, and the American College of Neuropsychopharmacology. He has been awarded several distinctions, including the Public Health Service Special Recognition Award, two NIH Director's Awards, the Presidents Award from the International Neural Network Society, and the President Award from the International Neural Network Society. He has 72 publications in referred journals, 20 invited chapters in books and edited 13 books.

Shankar Subramaniam is a Professor of Bioengineering, Chemistry and Biochemistry and Biology and Director of the Bioinformatics Graduate Program at the University of California at San Diego. He also has adjunct Professorships at the Salk Institute for Biological Studies and the San Diego Supercomputer Center. He has previously served as Director of the Bioinformatics and Computational Biology Program at the National Center for Supercomputing Applications and the Co-Director of the W.M. Keck Center for Comparative and Functional Genomics at UIUC. He is a fellow of the American Institute for Medical and Biological Engineering and is a recipient of Smithsonian Foundation and Association of Laboratory Automation Awards.

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"...a welcome overview and update of the rapid developments of the last few years...the publishers are to be commended on the excellent way the book has been executed, on glossy paper and with liberal use of color in the figures." (Genes, Brain and Behavior, April 2006)

"...well illustrated, referenced, and written...a very unique book and should find a place in the libraries of neuroscience, informatics, and general biological sciences." (Doody's Health Services)

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