title: Gene expression profiling in neurological disorders: toward a systems-level understanding of the brain.
abstract: Neurological disease arises when a sufficient number of neural cells stop performing their normal functions, lose their ability to respond to local environment, and die. In the last decade, a major technological leap led to the development of efficient and cost-effective high-throughput methods for determining gene expression. This, in turn, resulted in the rapid accumulation of data describing gene expression patterns in the brain of humans and experimental animals. This article reviews several of the most commonly used technologies to retrieve transcriptional information, such as large-scale expressed sequence tag (EST) sequencing, serial analyses of gene experiment, and different DNA microarray platforms. In addition, efforts focusing on data collection, sharing, and standardization are described. A section is devoted to the latest advances in large-scale gene expression in several neurological disorders, including Alzheimer's disease, Parkinson's disease, multiple sclerosis, and epilepsy. Finally, the need for integration of different sources of data is discussed in the context of systems biology and how such integration could result in improved diagnostics, therapies, and disease prevention.
authors.affiliation: Department of Neurology, School of Medicine, University of California, San Francisco, 513 Parnassus Avenue, Medical Sciences Building S-256, San Francisco, CA 94143, USA. sebaran@cgl.ucsf.edu
authors.forename: Sergio E
authors.initials: SE
authors.lastname: Baranzini
mesh_terms: D001921:Brain / Q000473:pathology / Q000503:physiopathology*; D019295:Computational Biology; D020224:Expressed Sequence Tags; D020869:Gene Expression Profiling; D015723:Gene Library; D006801:Humans; D009422:Nervous System Diseases / Q000235:genetics*; D020411:Oligonucleotide Array Sequence Analysis; D014158:Transcription, Genetic