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http://braininfo.rprc.washington.edu

Portal to neuroanatomical information on the Web that helps you identify structures in the brain and provides a variety of information about each structure by porting you to the best of 1500 web pages at 100 other neuroscience sites. BrainInfo consists of three basic components: NeuroNames, a developing database of definitions of neuroanatomic structures in four species, their most common acronyms and their names in eight languages; NeuroMaps, a digital atlas system based on 3-D canonical stereotaxic atlases of rhesus macaque and mouse brains and programs that enable one to map data to standard surface and cross-sectional views of the brains for presentation and publication; and the NeuroMaps precursor: Template Atlas of the Primate Brain, a 2-D stereotaxic atlas of the longtailed (fascicularis) macaque brain that shows the locations of some 250 architectonic areas of macaque cortex. The NeuroMaps atlases will soon include a number of overlays showing the locations of cortical areas and other neuroscientific data in the standard frameworks of the macaque and mouse atlases. Viewers are encouraged to use NeuroNames as a stable source of unique standard terms and acronyms for brain structures in publications, illustrations and indexing systems; to use templates extracted from the NeuroMaps macaque and mouse brain atlases for presenting neuroscientific information in image format; and to use the Template Atlas for warping to MRIs or PET scans of the macaque brain to estimate the stereotaxic locations of structures.

Proper citation: BrainInfo (RRID:SCR_003142) Copy   

•   Source: SciCrunch Registry
  

http://www.brainarchitecture.org/mouse-home

An atlas project whose goal is to enerate brainwide maps of inter-regional neural connectivity that specify the inputs and outputs of every brain region, at a "mesoscopic" level of analysis. A 3D injection viewer is used to view the mouse brain. To determine the outputs of a brain region, anterograde tracers are used which are taken up by neurons locally ("the input"), then transported actively down the axons to the "output regions." The whole brain is then sliced thinly, and each slice is digitally imaged. These 2-D images are reconstructed in 3D. The majority of the resulting 3-D brain image is unlabeled. Only the injected region and its output regions have tracer in them, allowing for identification of this small fraction of the connectivity map. This procedure is repeated identically, to account for individual variability. To determine the inputs to the same brain region as above, a retrograde tracer is injected in the same stereotaxic location ("the input"), and the process is repeated. In order to accumulate data from different mice (each of whom has a slightly different brain shape and size), 3-D spatial normalization is performed using registration algorithms. These gigapixel images of whole-brain sections can be zoomed to show individual neurons and their processes, providing a "virtual microscope." Each sampled brain is represented in about 500 images, each image showing an optical section through a 20 micron-thick slice of brain tissue. A multi-resolution viewer permits users to journey through each brain, following the pathways taken through three-dimensional brain space by tracer-labeled neuronal pathways. A key point is that at the mid-range "mesoscopic" scale, the team expects to assemble a picture of connections that are stereotypical and probably genetically determined in a species-specific manner. By dividing the volume of a hemisphere of the mouse brain into 250 equidistant, predefined grid-points, and administering four different kinds of tracer injections at each grid point -- in different animals of the same sex and age a complete wiring diagram that will be stitched together in "shotgun" fashion from the full dataset.

Proper citation: Mouse Brain Architecture Project (RRID:SCR_004683) Copy   

•   Source: SciCrunch Registry
  

http://learn.genetics.utah.edu/

Educational resources that provide accurate and unbiased information about topics in genetics, bioscience and health for global and local audiences. They are jargon-free, target multiple learning styles, and often convey concepts through animation and interactivity. The Genetic Science Learning Center is a science and health education program located in the midst of the bioscience research being carried out at the University of Utah. Our mission is making science easy for everyone to understand. * Two websites, available free of charge to Internet users worldwide: ** Learn.Genetics delivers educational materials on genetics, bioscience and health topics. They are designed to be used by students, teachers and members of the public. The materials meet selected US education standards for science and health. ** Teach.Genetics provides resources for K-12 teachers, higher education faculty, and public educators. These include PDF-based Print-and-Go™ activities, unit plans and other supporting resources. The materials are designed to support and extend the materials on Learn.Genetics. *Professional development programs that update K-16 teachers' expertise in bioscience and health topics as well as prepare them to implement the materials on our websites. * Community programs that engage with diverse communities in discussions about genetics and health, and in developing culturally and linguistically-appropriate educational materials. Some topics in genetics and bioscience research are controversial. The Center does not take sides in political or ethical controversies. Rather, our goal is to provide comprehensive information that promotes a lively discussion of these topics, so that individuals can arrive at their own informed decisions.

Proper citation: University of Utah Genetic Science Learning Center - Learn Genetics (RRID:SCR_001910) Copy   

•   Source: SciCrunch Registry
  

http://mousemutant.jax.org/index.html

Producer and supplier of a collection of mice bearing spontaneous mutations. These mice contribute to a better understanding of the genetic bases of neurological, neuromuscular, sensory, metabolic, skeletal/craniofacial and developmental disorders and conditions such as diabetes, obesity and heart disease.

Proper citation: Mouse Mutant Resource (RRID:SCR_008367) Copy   

•   Source: SciCrunch Registry
  

http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000674.v1.p1

Human genetics data from an immense (78,000) and ethnically diverse population available for secondary analysis to qualified researchers through the database of Genotypes and Phenotypes (dbGaP). It offers the opportunity to identify potential genetic risks and influences on a broad range of health conditions, particularly those related to aging. The GERA cohort is part of the Research Program on Genes, Environment, and Health (RPGEH), which includes more than 430,000 adult members of the Kaiser Permanente Northern California system. Data from this larger cohort include electronic medical records, behavioral and demographic information from surveys, and saliva samples from 200,000 participants obtained with informed consent for genomic and other analyses. The RPGEH database was made possible largely through early support from the Robert Wood Johnson Foundation to accelerate such health research. The genetic information in the GERA cohort translates into more than 55 billion bits of genetic data. Using newly developed techniques, the researchers conducted genome-wide scans to rapidly identify single nucleotide polymorphisms (SNPs) in the genomes of the people in the GERA cohort. These data will form the basis of genome-wide association studies (GWAS) that can look at hundreds of thousands to millions of SNPs at the same time. The RPGEH then combined the genetic data with information derived from Kaiser Permanente''s comprehensive longitudinal electronic medical records, as well as extensive survey data on participants'' health habits and backgrounds, providing researchers with an unparalleled research resource. As information is added to the Kaiser-UCSF database, the dbGaP database will also be updated.

Proper citation: Resource for Genetic Epidemiology Research on Adult Health and Aging (RRID:SCR_010472) Copy   

•   Source: SciCrunch Registry