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http://projects.tcag.ca/humandup/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 17, 2013. It contains information about segmental duplications in the human genome. The criteria used to identify regions of segmental duplication are: Sequence identity of at least 90, Sequence length of at least 5 kb, Not be entirely composed of repetitive elements. Background Previous studies have suggested that recent segmental duplications, which are often involved in chromosome rearrangements underlying genomic disease, account for some 5 of the human genome. We have developed rapid computational heuristics based on BLAST analysis to detect segmental duplications, as well as regions containing potential sequence misassignments in the human genome assemblies. Results Our analysis of the June 2002 public human genome assembly revealed that 107.4 of 3,043.1 megabases (Mb) (3.53) of sequence contained segmental duplications, each with size equal or more than 5 kb and 90 identity. We have also detected that 38.9 Mb (1.28) of sequence within this assembly is likely to be involved in sequence misassignment errors. Furthermore, we have identified a significant subset (199,965 of 2,327,473 or 8.6) of single-nucleotide polymorphisms (SNPs) in the public databases that are not true SNPs but are potential paralogous sequence variants. Conclusion Using two distinct computational approaches, we have identified most of the sequences in the human genome that have undergone recent segmental duplications. Near-identical segmental duplications present a major challenge to the completion of the human genome sequence. Potential sequence misassignments detected in this study would require additional efforts to resolve. The segmental duplication data and summary statistics are available for download. Data for Human Genome (based on the May 2004 Human Genome Assembly (hg17)) Visualize duplication relationships in GBrowse (GBrowse) Duplicon Pair relationships (GFF) Genes within duplication regions (HTML) Genome duplication content (MS Excel) The segmental duplication data can be visualized in a genome browser in the GBrowse section. Selected human genome annotation tracks (except the segmental duplication track) have also been obtained from UCSC and loaded into the genome browser. Detailed information (e.g. overlapping genes, overlapping clones, detailed alignment) can be obtained by clicking on a duplication cluster in GBrowse. Both keyword search and BLAT search are available. Analyses based on previous human genome assemblies can be found in the Previous Analyses section. Acknowledgments We thank The Centre for Applied Genomics at the Hospital for Sick Children (HSC) as well as collaborators worldwide. Supported by Genome Canada the Howard Hughes Medical Institute International Scholar Program (to S.W.S.) and the HSC Foundation.

Proper citation: Human Genome Segmental Duplication Database (RRID:SCR_007728) Copy   

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http://systers.molgen.mpg.de/

SYSTERS is a database of protein sequences grouped into homologous families and superfamilies. The SYSTERS project aims to provide a meaningful partitioning of the whole protein sequence space by a fully automatic procedure. A refined two-step algorithm assigns each protein to a family and a superfamily. The sequence data underlying SYSTERS release 4 now comprise several protein sequence databases derived from completely sequenced genomes (ENSEMBL, TAIR, SGD and GeneDB), in addition to the comprehensive Swiss-Prot/TrEMBL databases. To augment the automatically derived results, information from external databases like Pfam and Gene Ontology are added to the web server. Furthermore, users can retrieve pre-processed analyses of families like multiple alignments and phylogenetic trees. New query options comprise a batch retrieval tool for functional inference about families based on automatic keyword extraction from sequence annotations. A new access point, PhyloMatrix, allows the retrieval of phylogenetic profiles of SYSTERS families across organisms with completely sequenced genomes. Gene, Human, Vertebrate, Genome, Human ORFs

Proper citation: SYSTERS (RRID:SCR_007955) Copy   

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https://cnprc.ucdavis.edu/

Center for investigators studying human health and disease, offering the opportunity to assess the causes of disease, and new treatment methods in nonhuman primate models that closely recapitulate humans. Its mission is to provide interdisciplinary programs in biomedical research on significant human health-related problems in which nonhuman primates are the models of choice.

Proper citation: California National Primate Research Center (RRID:SCR_006426) Copy   

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https://www.msu.edu/~brains/brains/human/index.html

A labeled three-dimensional atlas of the human brain created from MRI images. In conjunction are presented anatomically labeled stained sections that correspond to the three-dimensional MRI images. The stained sections are from a different brain than the one which was scanned for the MRI images. Also available the major anatomical features of the human hypothalamus, axial sections stained for cell bodies or for nerve fibers, at six rostro-caudal levels of the human brain stem; images and Quicktime movies. The MRI subject was a 22-year-old adult male. Differing techniques used to study the anatomy of the human brain all have their advantages and disadvantages. Magnetic resonance imaging (MRI) allows for the three-dimensional viewing of the brain and structures, precise spatial relationships and some differentiation between types of tissue, however, the image resolution is somewhat limited. Stained sections, on the other hand, offer excellent resolution and the ability to see individual nuclei (cell stain) or fiber tracts (myelin stain), however, there are often spatial distortions inherent in the staining process. The nomenclature used is from Paxinos G, and Watson C. 1998. The Rat Brain in Stereotaxic Coordinates, 4th ed. Academic Press. San Diego, CA. 256 pp

Proper citation: Human Brain Atlas (RRID:SCR_006131) Copy   

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http://www.catstests.com/Product05.htm

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 16, 2013. CATs Card Sort is a free, general purpose card sorting program which allows the user to design sorting tasks similar to those described by Vigotsky (1934), Weigel (1941), and Grant and Berg (1948). Card sorting tasks have been shown to be particularly sensitive to frontal lobe dysfunction, but have also shown sensitivity to motor disorders, schizophrenia, chronic alcoholism, aging, and attention deficit disorder. The CATs Card Sort package provides extensive flexibility in the development of stimulus cards, allowing the experimenter to define the relevant dimensions of cards in terms of figures, letters or words, figure/letter/word color, card color, figure/letter numerosity, and a user defined dimension. Considerable flexibility is also provided in designing lists of to be sorted cards, sort criteria, and the criteria for sort classification shift. The package also provides limited analysis capabilities as described by Grant and Berg (1948). However, as with all CATs packages raw data can be copied to the clipboard in a format acceptable for import into commonly available spreadsheets such as Excel allowing the user to design analysis routines appropriate to their needs.

Proper citation: Colorado Assessment Tests - Card Sort (RRID:SCR_007331) Copy   

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http://wiki.c2b2.columbia.edu/califanolab/index.php/BCellInteractome.htm

A network of protein-protein, protein-DNA and modulatory interactions in human B cells. The network contains known interactions (reported in public databases) and predicted interactions by a Bayesian evidence integration framework which integrates a variety of generic and context specific experimental clues about protein-protein and protein-DNA interactions with inferences from different reverse engineering algorithms, such as GeneWays and ARACNE. Modulatory interactions are predicted by the MINDY, an algorithm for the prediction of modulators of transcriptional interactions (please refer to the publication section for more information). The BCI can be downloaded as one tab delimited file containing the complete network (BCI.txt) with each type of interaction explicitly defined.

Proper citation: B Cell Interactome (RRID:SCR_008655) Copy   

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http://www.uv.es/vista/vistavalencia/

The general goal is to achieve a deeper understanding of natural image statistics because from this knowledge it should be possible to explain the behavior of the visual cortex and propose new alternatives in a number of applications in image processing and computer vision in which the basic problem is the choice of an appropriate signal representation. The range of basic and applied topics in which we are currently working include: * Mathematical models of human vision * Statistical image models * Image distortion metrics * Image coding * Motion estimation * Video coding * Image restoration * Color representation

Proper citation: Visual Statistics Group (RRID:SCR_008317) Copy   

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http://www.bic.mni.mcgill.ca/ServicesAtlases/ICBM152NLin2009

Unbiased standard magnetic resonance imaging template brain volume for normal population. These volumes were created using data from ICBM project. 6 different templates are available: * ICBM 2009a Nonlinear Symmetric - template which includes T1w,T2w,PDw modalities, also T2 relaxometry (T2 values calculated for each subject using single dual echo PD/T2 scan), and tissue probabilities maps. Also included lobe atlas used for ANIMAL+INSECT segmentation, brain mask, eye mask and face mask. Intensity inhomogeneity was performed using N3 version 1.10.1. * ICBM 2009a Nonlinear Asymmetric template - template which includes T1w,T2w,PDw modalities, and tissue probabilities maps. Intensity inhomogeneity was performed using N3 version 1.10.1. Also included brain mask, eye mask and face mask. * ICBM 2009b Nonlinear Symmetric - template which includes only T1w,T2w and PDw modalities. * ICBM 2009b Nonlinear Asymmetric - template which includes only T1w,T2w and PDw modalities. * ICBM 2009c Nonlinear Symmetric - template which includes T1w,T2w,PDw modalities, and tissue probabilities maps. Also included lobe atlas used for ANIMAL+INSECT segmentation, brain mask, eye mask and face mask. Intensity inhomogeneity was performed using N3 version 1.11. Sampling is different from 2009a template. * ICBM 2009c Nonlinear Asymmetric template - template which includes T1w,T2w,PDw modalities, and tissue probabilities maps. Intensity inhomogeneity was performed using N3 version 1.11 Also included brain mask, eye mask and face mask.Sampling is different from 2009a template. All templates are describing the same anatomy, but sampling is different. Also, different versions of N3 algorithm produces slightly different tissue probability maps. Tools for using these atlases can be found in the Software section. Viewing the multiple atlas volumes online requires Java browser support. You may also download the templates - see licensing information.

Proper citation: ICBM 152 Nonlinear atlases version 2009 (RRID:SCR_008796) Copy   

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http://www.bic.mni.mcgill.ca/ServicesAtlases/NIHPD-obj1

An unbiased standard magnetic resonance imaging template brain volume for pediatric data from the 4.5 to 18.5y age range. These volumes were created using data from 324 children enrolled in the NIH-funded MRI study of normal brain development (Almli et al., 2007, Evans and Group 2006). Tools for using these atlases can be found in the Software section. To view the atlases online, click on the appropriate JIV2 link in the Download section. You can download templates constructed for different age ranges. For each age range you will get an average T1w, T2w, PDw maps normalized between 0 and 100 and tissue probability maps, with values between 0 and 1. Also each age range includes a binary brain mask.

Proper citation: NIHPD Objective 1 atlases (4.5 - 18.5y) (RRID:SCR_008794) Copy   

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http://www.neuroethics.ubc.ca/

It is an interdisciplinary research group dedicated to tackling the ethical, legal, policy and social implications of frontier technological developments in the neurosciences. Our objective is to align innovations in the brain sciences with societal, cultural and individual human values through high impact research, education and outreach. The Core''s major research projects are focused on high impact, high visibility areas including the use of drugs and devices for neuroenhancement, ethics in neurodegenerative disease and regenerative medicine research, international and cross-cultural challenges in brain research, neuroimaging in the private sector, and the ethics of personalized medicine, among others. Members of the Core also lead initiatives aside from their research projects. Sponsors: This Core is supported by the University of Brititsh Columbia.

Proper citation: UBC National Core for Neuroethics (RRID:SCR_008063) Copy   

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https://www.broadinstitute.org/ccle/

A collaborative project between the Broad Institute and the Novartis Institutes for Biomedical Research and its Genomics Institute of the Novartis Research Foundation, with the goal of conducting a detailed genetic and pharmacologic characterization of a large panel of human cancer models. The CCLE also works to develop integrated computational analyses that link distinct pharmacologic vulnerabilities to genomic patterns and to translate cell line integrative genomics into cancer patient stratification. The CCLE provides public access to genomic data, analysis and visualization for about 1000 cell lines.

Proper citation: Cancer Cell Line Encyclopedia (RRID:SCR_013836) Copy   

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http://icmic.rad.jhmi.edu/

The vision of the JHU ICMIC is to combine state-of-the-art imaging capabilities with powerful molecular biology techniques to define strategies with intent to cure. It has drawn upon its human resources at JHU to create a center consisting of a multidisciplinary group of premier individuals with diverse skills focused on translating molecular capabilities into imaging possibilities with the single purpose of understanding and curing cancer. Nearly all of the investigators participating in this ICMIC have interactive collaborative projects with one or more of the other investigators. The synergism generated by the collective skills of this unique group of individuals will lead to significant advances in the understanding of cancer and its treatment. The JHU ICMIC structure consists of four interactive and closely related research components focused on hypoxia, HIF-1, and exploiting the hypoxia response element to target cancer cells through choline kinase inhibition. These research components are anchored by the participation of world renowned expertise in HIF-1. The research components utilize MR, PET and Optical Imaging technology to understand cancer vascularization, invasion and metastasis, to achieve effective cancer therapy. The center has selected developmental projects which are highly relevant to the goals of the ICMIC and interactive with the research components. Five resources devoted to adminstration, molecular biology, imaging, probes, and translational application provide the infrastructure to support the research activities of the ICMIC. Research Components in the JHU ICMIC: - Combining Anti-angiogenic therapy with siRNA targeting of choline kinase. - Imaging the Role of HIF-1 in Breast Cancer Progression - Imaging and Targeting Hypoxia in Solid Tumors - Molecular and Functional Imaging of the HER-2/neu Receptor The following are developmental projects currently taking place in ICMIC 1. Receptor imaging using nonparamagnetic MRI contrast agents (2003) 2. New imaging agents for prostate cancer (2003) 3. Non-invasive monitoring of therapeutic effect of siRNA-mediated radiation sensitization in human prostate cancer xenografts (2003) 4. Imaging of the endothelin receptor in cancer (2003) 5. Imaging studies of c-myc regulation of tumor metabolism (2003) 6. Imaging studies of anti-tumorigenic effects of anti-oxidants in vivo (2005) 7. Molecular Imaging with Magnetic Resonance Microsystems (2005) 8. Endogenous angiogenesis inhibitors (2005) 9. MR imaging and spectroscopy in detection and localization of prostate cancer: a prospective trial in patients undergoing cystoprostatectomy and radical prostatectomy. (2005) 10. A versatile visualization system for the analysis of multi-modality and multidimensional cancer imaging (2007) 11. Non-invasive imaging of CXCR4 expression in breast cancer (2007)

Proper citation: John Hopkins University, In-Vivo Cellular Molecular Imaging Center (RRID:SCR_013198) Copy   

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http://lincs.hms.harvard.edu/

Center that is part of the NIH Library of Integrated Network-based Cellular Signatures (LINCS) Program. Its goals are to collect and disseminate data and analytical tools needed to understand how human cells respond to perturbation by drugs, the environment, and mutation.

Proper citation: HMS LINCS Center (RRID:SCR_016370) Copy   

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http://www.bionet.umn.edu/tpf/home.html

Procure and distribute human tissue and other biological samples in support of basic, translational, and clinical cancer research at the University of Minnesota. The TPF is a centralized resource with standardized patient consent, sample collection, processing, storage, quality control, distribution, and electronic record maintenance. Since the 1996 inception of the TPF, over 61,000 tissue samples including well-preserved samples of malignant and benign tumors, organ-matched normal tissue, and other types of diseased tissues, have been collected from surgical specimens obtained at the University of Minnesota Medical Center-Fairview (UMMC-F) University Campus. Surgical pathologists are intellectually engaged in TPF functions, providing researchers with specimen-oriented medical consultation to facilitate research productivity. Prior to surgery, TPF personnel identify and consent patients for procurement of tissue, blood, urine, saliva, and ascites fluid. Within the integrated working environment of the surgical pathology laboratory, freshly obtained tissues not needed for diagnosis are selected and provided by pathologists to TPF personnel. Tissue samples are then assigned an independent code and processed. TPF staff can also work with researchers to individualize the procurement of tissues to fit specific research needs.

Proper citation: University of Minnesota Tissue Procurement Facility (RRID:SCR_004270) Copy   

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http://www.nimhans.kar.nic.in/neuropathology/neuropath2.htm#brainbank

A National Facility to promote research in Neurobiology using human nervous tissues. The brain tissues collected with informed consent of close relatives within 4-24 hours following death are frozen for Biochemical, Immuno-histochemical and Molecular Biological studies. A large number of formalin fixed brain tissues from various Neurological, Neurosurgical and Psychiatric disorders are also available for study.

Proper citation: Bangalore Brain Bank (RRID:SCR_004227) Copy   

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http://www.hgsc.bcm.tmc.edu/content/hapmap-3-and-encode-3

Draft release 3 for genome-wide SNP genotyping and targeted sequencing in DNA samples from a variety of human populations (sometimes referred to as the HapMap 3 samples). This release contains the following data: * SNP genotype data generated from 1184 samples, collected using two platforms: the Illumina Human1M (by the Wellcome Trust Sanger Institute) and the Affymetrix SNP 6.0 (by the Broad Institute). Data from the two platforms have been merged for this release. * PCR-based resequencing data (by Baylor College of Medicine Human Genome Sequencing Center) across ten 100-kb regions (collectively referred to as ENCODE 3) in 712 samples. Since this is a draft release, please check this site regularly for updates and new releases. The HapMap 3 sample collection comprises 1,301 samples (including the original 270 samples used in Phase I and II of the International HapMap Project) from 11 populations, listed below alphabetically by their 3-letter labels. Five of the ten ENCODE 3 regions overlap with the HapMap-ENCODE regions; the other five are regions selected at random from the ENCODE target regions (excluding the 10 HapMap-ENCODE regions). All ENCODE 3 regions are 100-kb in size, and are centered within each respective ENCODE region. The HapMap 3 and ENCORE 3 data are downloadable from the ftp site.

Proper citation: HapMap 3 and ENCODE 3 (RRID:SCR_004563) Copy   

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http://www.tbi-impact.org/?p=impact%2Fcalc&btn_calc=GO+TO+CALCULATOR

A calculator that calculates the prediction models for 6 month outcome after Traumatic Brain Injury. Based on extensive prognostic analysis the IMPACT investigators have developed prognostic models for predicting 6 month outcome in adult patients with moderate to severe head injury (Glasgow Coma Scale <=12) on admission. By entering the characteristics into the calculator, the models will provide an estimate of the expected outcome at 6 months. We present three models of increasing complexity (Core, Core + CT, Core + CT + Lab). These models were developed and validated in collaboration with the CRASH trial collaborators on large numbers of individual patient data (the IMPACT database). The models discriminate well, and are particularly suited for purposes of classification and characterization of large cohorts of patients. Extreme caution is required when applying the estimated prognosis to individual patients. The sequential prediction models may be used as an aid to estimate 6 month outcome in patients with severe or moderate traumatic brain injury (TBI). However, the prediction rule can only complement, never replace, clinical judgment and can therefore be used only as a decision-support system.

Proper citation: IMPACT Prognostic Calculator (RRID:SCR_004730) Copy   

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http://www.phenologs.org/

Database for identifying orthologous phenotypes (phenologs). Mapping between genotype and phenotype is often non-obvious, complicating prediction of genes underlying specific phenotypes. This problem can be addressed through comparative analyses of phenotypes. We define phenologs based upon overlapping sets of orthologous genes associated with each phenotype. Comparisons of >189,000 human, mouse, yeast, and worm gene-phenotype associations reveal many significant phenologs, including novel non-obvious human disease models. For example, phenologs suggest a yeast model for mammalian angiogenesis defects and an invertebrate model for vertebrate neural tube birth defects. Phenologs thus create a rich framework for comparing mutational phenotypes, identify adaptive reuse of gene systems, and suggest new disease genes. To search for phenologs, go to the basic search page and enter a list of genes in the box provided, using Entrez gene identifiers for mouse/human genes, locus ids for yeast (e.g., YHR200W), or sequence names for worm (e.g., B0205.3). It is expected that this list of genes will all be associated with a particular system, trait, mutational phenotype, or disease. The search will return all identified model organism/human mutational phenotypes that show any overlap with the input set of the genes, ranked according to their hypergeometric probability scores. Clicking on a particular phenolog will result in a list of genes associated with the phenotype, from which potential new candidate genes can identified. Currently known phenotypes in the database are available from the link labeled ''Find phenotypes'', where the associated gene can be submitted as queries, or alternately, can be searched directly from the link provided.

Proper citation: Phenologs (RRID:SCR_005529) Copy   

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http://blog.ketyov.com/

Bradley Voytek''''s blog is where he tries out new ideas. He will often be wrong, but that''''s the point. He is a Neuroscientist studying human cognition, neuroplasticity, and brain computer interfacing. Into really geeky stuff. World zombie neuroscience expert. Also runs brainSCANr.com with his wife, Jessica.

Proper citation: Oscillatory Thoughts (RRID:SCR_005481) Copy   

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http://cmrm.med.jhmi.edu/cmrm/atlas/human_data/file/JHUtemplate_newuser.html

DTI white matter atlases with different data sources and different image processing. These include single-subject, group-averaged, B0 correction, processed atlases (White Matter Parcellation Map, Tract-probability maps, Conceptual difference between the WMPM and tract-probability maps), and linear or non-linear transformation for automated white matter segmentation. # Adam single-subject white matter atlas (old version): These are electronic versions of atlases published in Wakana et al, Radiology, 230, 77-87 (2004) and MRI Atlas of Human White Matter, Elsevier. ## Original Adam Atlas: 256 x 256 x 55 (FOV = 246 x 246 mm / 2.2 mm slices) (The original matrix is 96x96x55 (2.2 mm isotropic) which is zerofilled to 256 x 256 ## Re-sliced Adam Atlas: 246 x 246 x 121 (1 mm isotropic) ## Talairach Adam: 246 x 246 x 121 (1 mm isotropic) # New Eve single-subject white matter atlas: The new version of the single-subject white matter atlas with comprehensive white matter parcellation. ## MNI coordinate: 181 x 217 x 181 (1 mm isotropic) ## Talairach coordinate: 181 x 217 x 181 (1 mm isotropic) # Group-averaged atlases: This atlas was created from their normal DTI database (n = 28). The template was MNI-ICBM-152 and the data from the normal subjects were normalized by affine transformation. Image dimensions are 181x217x181, 1 mm isotropic. There are two types of maps. The first one is the averaged tensor map and the second one is probabilistic maps of 11 white matter tracts reconstructed by FACT. # ICBM Group-averaged atlases: This atlas was created from ICBM database. All templates follow Radiology convention. You may need to flip right and left when you use image registration software that follows the Neurology convention.

Proper citation: DTI White Matter Atlas (RRID:SCR_005279) Copy   

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