Neuroinformatics (Methods in Molecular Biology)
C. J. Crasto, ed. Humana Press; 2007, 404 pages, 86 illustrations, $99.50.
As neuroscience problems become more data-intensive and we rely heavily on computer systems for analysis, computational scientists have teamed up with neuroscientists and created the new field of neuroinformatics. Neuroinformatics provides software solutions to these complex data-analysis problems. The book Neuroinformatics compiles research topics from authors who received support from the Human Brain Project.
It is divided into 4 sections, which cover data base development, neuron modeling, neuroimaging with a focus on basic science applications, and applications of neuroinformatics to disease states. The “Neuroscience Knowledge Management” section describes methods of managing and structuring data bases. Interoperability is a particular focus as is the utility of extensible markup-language data. The “Computational Neuronal Modeling” section summarizes computational models of neuron physiology, biophysics, and neural networks. The imaging section attempts to describe methods of representing the brain in 2D, 3D, and even 4D. Two sections on functional MR imaging also deal with specific examples of mapping olfactory areas and receptors in brain images. Finally, “Neuroinformatics in Genetics and Neurodegenerative Diseases” returns to the origins of bioinformatics and describes genomic approaches to nervous system research and disease, including dementia, schizophrenia, and Alzheimer disease. Most chapters illustrate the techniques of neuroinfor-AQ: A matics through their own research examples. By understanding the authors’ methods, new investigators should be able to apply the techniques to their own work.
While not written for the clinical neuroradiology audience, basic neuroscientists and neuroimaging researchers navigating the complexities of applying neuroinformatics solutions to their research problems may find the book very useful. Many chapters include step-by-step coding or software instructions. The authors give clear experimental recommendations and guide the reader through new techniques of analyzing their data. The authors clearly demonstrate expertise in their field with in-depth knowledge of their techniques. Graduate students of biomedical informatics will find this book helpful as an introduction to various areas of neuroinformatics and as a guide to potential areas of research. In summary, this book will be valuable to the neuroscience and bioinformatics research community.
