@article {47904,
	title = {Multi-scale correlation structure of gene expression in the brain.},
	journal = {Neural networks : the official journal of the International Neural Network Society},
	volume = {24},
	year = {2011},
	month = {2011 Nov},
	pages = {933-42},
	abstract = {<p>The mammalian brain is best understood as a multi-scale hierarchical neural system, in the sense that connection and function occur on multiple scales from micro to macro. Modern genomic-scale expression profiling can provide insight into methodologies that elucidate this architecture. We present a methodology for understanding the relationship of gene expression and neuroanatomy based on correlation between gene expression profiles across tissue samples. A resulting tool, NeuroBlast, can identify networks of genes co-expressed within or across neuroanatomic structures. The method applies to any data modality that can be mapped with sufficient spatial resolution, and provides a computation technique to elucidate neuroanatomy via patterns of gene expression on spatial and temporal scales. In addition, from the perspective of spatial location, we discuss a complementary technique that identifies gene classes that contribute to defining anatomic patterns.</p>
},
	keywords = {Algorithms, Animals, Atlases as Topic, Brain, Brain Chemistry, Data Mining, Databases, Genetic, Gene Expression, Mice, Mice, Inbred C57BL, Nerve Tissue Proteins, Tryptophan Hydroxylase},
	issn = {1879-2782},
	doi = {10.1016/j.neunet.2011.06.012},
	author = {Hawrylycz, Mike and Ng, Lydia and Page, Damon and Morris, John and Lau, Chris and Faber, Sky and Faber, Vance and Sunkin, Susan and Menon, Vilas and Lein, Ed and Jones, Allan}
}
