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https://github.com/dorianps/LESYMAP

Software R package to conduct lesion-to-symptom mapping from human MRI data.Takes lesion maps and cognitive performance scores from patients with stroke, and maps brain areas responsible for cognitive deficit.

Proper citation: LESYMAP (RRID:SCR_017967) 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://ww2.sanbi.ac.za/Dbases.html

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 23, 2016. The STACKdb is knowledgebase generated by processing EST and mRNA sequences obtained from GenBank through a pipeline consisting of masking, clustering, alignment and variation analysis steps. The STACK project aims to generate a comprehensive representation of the sequence of each of the expressed genes in the human genome by extensive processing of gene fragments to make accurate alignments, highlight diversity and provide a carefully joined set of consensus sequences for each gene. The STACK project is comprised of the STACKdb human gene index, a database of virtual human transcripts, as well as stackPACK, the tools used to create the database. STACKdb is organized into 15 tissue-based categories and one disease category. STACK is a tool for detection and visualization of expressed transcript variation in the context of developmental and pathological states. The data system organizes and reconstructs human transcripts from available public data in the context of expression state. The expression state of a transcript can include developmental state, pathological association, site of expression and isoform of expressed transcript. STACK consensus transcripts are reconstructed from clusters that capture and reflect the growing evidence of transcript diversity. The comprehensive capture of transcript variants is achieved by the use of a novel clustering approach that is tolerant of sub-sequence diversity and does not rely on pairwise alignment. This is in contrast with other gene indexing projects. STACK is generated at least four times a year and represents the exhaustive processing of all publicly available human EST data extracted from GenBank. This processed information can be explored through 15 tissue-specific categories, a disease-related category and a whole-body index

Proper citation: Sequence Tag Alignment and Consensus Knowledgebase Database (RRID:SCR_002156) Copy   

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http://www.ibiblio.org/dnam/mainpage.html

This site provides access to mutation databases and software including the human hprt database, Human p53 database, Transgenic lacZ database, and Transgenic lacI database. Other avaialble programs include Mutational spectra comparison and relational database data entry. The most recent hprt database contains information on over 2,300 mutations found in vivo and in vitro in the human hprt gene and runs under Windows. The version for evaluation on this homepage has fewer mutations and is a DOS program. The database contains information on the mutagen, dose, spontaneous and induced mutant fraction, base position, amino acid position, amino acid change, local DNA sequence, cell type, citation, and other items. In addition, information regarding the cause and effect of mutations affecting splicing is given. Routines have been developed for the analysis of single base substitutions. The p53 database contains information on nearly 5,867 mutations found in the human p53 gene. The database itself has been updated in April of 1997. The database contains information on the cancer type, loss of heterozygosity, base position, amino acid position, amino acid change, local DNA sequence,citation, and other items. Routines have been developed for the analysis of single base substitutions. The Transgenic lacZ database contains information on 405 mutations found in vivo in the transgenic lacZ gene. It has last been updated in January of 1998. It provides information on the mutagen, dose, organ, mutant fraction, base position, amino acid position, amino acid change, local DNA sequence, citation, and other items. The Transgenic lacI database contains information on over 1700 mutations found in vivo in the transgenic lacI gene and on nearly 8000 mutations in the lacI gene in native E. coli. The database was updated in January 1998. The database contains information on the mutagen, dose, organ, mutant fraction, base position, amino acid position, amino acid change, local DNA sequence, citation, and other items. Routines have been developed for the analysis of single base substitutions for each of the databases. The software runs only on IBM-compatible PCs.

Proper citation: Neal's DNA Mutation Site (RRID:SCR_002947) Copy   

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http://www.loni.ucla.edu/~thompson/thompson.html

The UCLA laboratory of neuroimaging is working in several areas to enhance knowledge of anatomy, including brain mapping in large human populations, HIV, Schizophrenia, methamphetamine, tumor growth and 4d brain mapping, genetics and detection of abnormalities.

Proper citation: University of California at Los Angeles, School of Medicine: Neuro Imaging Lab of Thompson (RRID:SCR_001924) Copy   

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http://humanconnectome.org/connectome/connectomeDB.html

Data management platform that houses all data generated by the Human Connectome Project - image data, clinical evaluations, behavioral data and more. ConnectomeDB stores raw image data, as well as results of analysis and processing pipelines. Using the ConnectomeDB infrastructure, research centers will be also able to manage Connectome-like projects, including data upload and entry, quality control, processing pipelines, and data distribution. ConnectomeDB is designed to be a data-mining tool, that allows users to generate and test hypotheses based on groups of subjects. Using the ConnectomeDB interface, users can easily search, browse and filter large amounts of subject data, and download necessary files for many kinds of analysis. ConnectomeDB is designed to work seamlessly with Connectome Workbench, an interactive, multidimensional visualization platform designed specifically for handling connectivity data. De-identified data within ConnectomeDB is publicly accessible. Access to additional data may be available to qualified research investigators. ConnectomeDB is being hosted on a BlueArc storage platform housed at Washington University through the year 2020. This data platform is based on XNAT, an open-source image informatics software toolkit developed by the NRG at Washington University. ConnectomeDB itself is fully open source.

Proper citation: ConnectomeDB (RRID:SCR_004830) Copy   

•   Source: SciCrunch Registry

http://dels.nas.edu/ilar

The mission of ILAR is to evaluate and disseminate information on issues related to the scientific, technological, and ethical use of animals and related biological resources in research, testing, and education. Using the principles of refinement, reduction, and replacement (3Rs) as a foundation, ILAR promotes high-quality science through the humane care and use of animals and the implementation of alternatives. Through the reports of expert committees, the ILAR Journal, web-based resources, and other means of communication, ILAR functions as a component of the National Academies to provide independent, objective advice to the federal government, the international biomedical research community, and the public. ILAR supports the responsible use of animals in research, testing, and education as a key component to advancing the health and quality of life of humans and animals. It promotes high-quality science and humane care and use of research animals based upon the principles of refinement, replacement, and reduction (the 3Rs) and high ethical standards. It fosters best practices that enhance human and animal welfare by organizing and disseminating information and by facilitating dialogue among interested parties. It has developed a unique Search Engine to search for animal models and strains. This search engine surveys all the websites of vendors and repositories of laboratory animals and biological material on our Links page. The ILAR develops guidelines on laboratory animal care and use and conducts conferences, symposia, and workshops on important laboratory animal problems. ILAR publishes the ILAR Journal on a quarterly basis, as well as conference proceedings and special reports prepared by committees of experts. A list of ILAR publications on issues related to laboratory animal research is available on the Web site. As part of the Animal Models and Genetic Stocks Information Exchange Program, ILAR staff members answer direct telephone and mail inquiries and maintain a Web page containing a database on animal models and genetic stock. The Web site also offers a comprehensive search engine that enables users to find information on the existence and location of special animal models, correct nomenclature to identify animals, and related topics such as diseases of animals and relevant publications. Sponsors: ILAR receives funding from the following sponsors: -Abbott Laboratories -Abbott Fund -American College of Laboratory Animal Medicine (ACLAM) -American Society of Laboratory Animal Practitioners (ASLAP) -Association for Assessment and Accreditation of Laboratory Animal Care (AAALAC) -Bristol-Myers Squibb Co. -Charles River -Charles River Laboratories Foundation -Covance -Federation of American Societies for Experimental Biology (FASEB) -GlaxoSmithKline -Merck & Co., Inc. -National Science Foundation (NSF) -Pfizer -Scientists Center for Animal Welfare (SCAW) -U.S. Department of Agriculture (USDA) -U.S. Department of the Army -U.S. Department of Health and Human Services (DHHS) :*National Institutes of Health (NIH) :*Office of Research Integrity (ORI) -U.S. Department of the Navy -U.S. Department of Veterans Affairs -Wellcome Trust -Wyeth Pharmaceuticals

Proper citation: Institute for Laboratory Animal Research (RRID:SCR_006872) Copy   

•   Source: SciCrunch Registry

http://www.nimh.nih.gov/news/media/audio/index.shtml

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 22, 2016. Audio and video available from the National Institute of Mental Health (NIMH).

Proper citation: NIMH Multimedia (RRID:SCR_005467) Copy   

•   Source: SciCrunch Registry

http://www.roslin.ed.ac.uk/alan-archibald/porcine-genome-sequencing-project/

Map of identifyied genes controlling traits of economic and welfare significance in the pig. The project objectives were to produce a genetic map with markers spaced at approximately 20 centiMorgan intervals over at least 90% of the pig genome; to produce a physical map with at least one distal and one proximal landmark locus mapped on each porcine chromosome arm and also genetically mapped; to develop a flow karyotype for the pig based on FACS sorted chromosomes; to develop PCR based techniques to enable rapid genotyping for polymorphic markers; to evaluate synteny conservation between pigs, man, mice and cattle; to develop and evaluate the statistical techniques required to analyze data from QTL mapping experiments and to plan and initiate the mapping of QTLs in the pig; to map loci affecting traits of economic and biological significance in the pig; and to develop the molecular tools to allow the future identification and cloning of mapped loci. Animal breeders currently assume that economically important traits such as growth, carcass composition and reproductive performance are controlled by an infinite number of genes each of infinitessimal effect. Although this model is known to be unrealistic, it has successfully underpinned the genetic improvement of livestock, including pigs, over recent decades. A map of the pig genome would allow the development of more realistic models of the genetic control of economic traits and the ultimately the identification of the major trait genes. This would allow the development of more efficient marker assisted selection which may be of particular value for traits such as disease resistance and meat quality.

Proper citation: Pig Genome Mapping (RRID:SCR_012884) Copy   

•   Source: SciCrunch Registry

http://harvester.fzk.de/harvester/

Harvester is a Web-based tool that bulk-collects bioinformatic data on human proteins from various databases and prediction servers. It is a meta search engine for gene and protein information. It searches 16 major databases and prediction servers and combines the results on pregenerated HTML pages. In this way Harvester can provide comprehensive gene-protein information from different servers in a convenient and fast manner. As full text meta search engine, similar to Google trade mark, Harvester allows screening of the whole genome proteome for current protein functions and predictions in a few seconds. With Harvester it is now possible to compare and check the quality of different database entries and prediction algorithms on a single page. Sponsors: This work has been supported by the BMBF with grants 01GR0101 and 01KW0013.

Proper citation: Bioinformatic Harvester IV (beta) at Karlsruhe Institute of Technology (RRID:SCR_008017) Copy   

•   Source: SciCrunch Registry

https://www.amazon.com/How-Brain-Works-Mark-Dubin/dp/0632044411

THIS RESOURCE IS NO LONGER IN SERVCE, documented September 2, 2016. Is the Brain (Like) a Computer is an e-book written by Prof. Mark Dubin. It consists of the following: Introduction. Why do we consider the relationship of brains and computers and what does this have to do with consciousness? What's a Brain Made Of? A thought experiment. Test Drive a Turing Machine. A theoretical approach. Interim Summary. Many of the main pages have links to additional information. When you click on one of those links a NEW page will open ON TOP of the page you are clicking from. This convention is adopted so that you can look at the additional information and then easily return to the main page you got there from.

Proper citation: Is the Brain (Like) a Computer (RRID:SCR_008809) Copy   

•   Source: SciCrunch Registry

https://nidagenetics.org/

Site for collection and distribution of clinical data related to genetic analysis of drug abuse phenotypes. Anonymous data on family structure, age, sex, clinical status, and diagnosis, DNA samples and cell line cultures, and data derived from genotyping and other genetic analyses of these clinical data and biomaterials, are distributed to qualified researchers studying genetics of mental disorders and other complex diseases at recognized biomedical research facilities. Phenotypic and Genetic data will be made available to general public on release dates through distribution mechanisms specified on website.

Proper citation: National Institute on Drug Abuse Center for Genetic Studies (RRID:SCR_013061) Copy   

•   Source: SciCrunch Registry

http://rarediseases.info.nih.gov/GARD/Default.aspx

Genetic and Rare Diseases Information Center (GARD) is a collaborative effort of two agencies of the National Institutes of Health, The Office of Rare Diseases Research (ORDR) and the National Human Genome Research Institute (NHGRI) to help people find useful information about genetic conditions and rare diseases. GARD provides timely access to experienced information specialists who can furnish current and accurate information about genetic and rare diseases. So far, GARD has responded to 27,635 inquiries on about 7,147 rare and genetic diseases. Requests come not only from patients and their families, but also from physicians, nurses and other health-care professionals. GARD also has proved useful to genetic counselors, occupational and physical therapists, social workers, and teachers who work with people with a genetic or rare disease. Even scientists who are studying a genetic or rare disease and who need information for their research have contacted GARD, as have people who are taking part in a clinical study. Community leaders looking to help people find resources for those with genetic or rare diseases and advocacy groups who want up-to-date disease information for their members have contacted GARD. And members of the media who are writing stories about genetic or rare diseases have found the information GARD has on hand useful, accurate and complete. GARD has information on: :- What is known about a genetic or rare disease. :- What research studies are being conducted. :- What genetic testing and genetic services are available. :- Which advocacy groups to contact for a specific genetic or rare disease. :- What has been written recently about a genetic or rare disease in medical journals. GARD information specialists get their information from: :- NIH resources. :- Medical textbooks. :- Journal articles. :- Web sites. :- Advocacy groups, and their literature and services. :- Medical databases.

Proper citation: Genetic and Rare Diseases Information Center (RRID:SCR_008695) Copy   

•   Source: SciCrunch Registry

http://www.hmpdacc.org/

Common repository for diverse human microbiome datsets and minimum reporting standards for Common Fund Human Microbiome Project.

Proper citation: HMP Data Analysis and Coordination Center (RRID:SCR_004919) Copy   

•   Source: SciCrunch Registry

http://vision.ucsf.edu/hortonlab/index.html

Devise better ways to prevent and treat vision loss due to amblyopia and strabismus, and to advance medical science by understanding the human visual system. Various Images, Videos and Talks related to the research are available. In the Laboratory for Visual Neuroscience at the University of California, San Francisco, we are seeking to discover how visual perception occurs in the human brain. The function of the visual system is to guide our behavior by providing an efficient means for the rapid assimilation of information from the environment. As we navigate through our surroundings, a continuous stream of light images impinges on our eyes. In the back of each eye a light-sensitive tissue, the retina, converts patterns of light energy into electrical discharges known as action potentials. These signals are conveyed along the axons of retinal ganglion cells to the lateral geniculate body, a relay nucleus in the thalamus. Most of the output of the lateral geniculate body is relayed directly to the primary visual cortex (striate cortex, V1), and then to surrounding visual association areas. To understand the function of the visual pathways, our research is focused on 5 major themes: * Organization of Primary Visual Cortex * Mapping of Extrastriate Visual Cortex * Amblyopia and Visual Development * Strabismus and Visual Suppression * The Human Visual Cortex

Proper citation: UCSF Laboratory for Visual Neuroscience (RRID:SCR_004913) Copy   

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http://en.wikibooks.org/wiki/MINC/Atlases

A linear average model atlas produced by the International Consortium for Brain Mapping (ICBM) project. A set of full- brain volumetric images from a normative population specifically for the purposes of generating a model were collected by the Montreal Neurological Institute (MNI), UCLA, and University of Texas Health Science Center at San Antonio Research Imaging Center (RIC). 152 new subjects were scanned using T1, T2 and PD sequences using a specific protocol. These images were acquired at a higher resolution than the original average 305 data and exhibit improved contrast due predominately to advances in imaging technology. Each individual was linearly registered to the average 305 and a new model was formed. In total, three models were created at the MNI, the ICBM152_T1, ICBM152_T2 and ICBM152_PD from 152 normal subjects. This resulting model is now known as the ICBM152 (although the model itself has not been published). One advantage of this model is that it exhibits better contrast and better definition of the top of the brain and the bottom of the cerebellum due to the increased coverage during acquisition. The entirely automatic analysis pipeline of this data also included grey/white matter segmentation via spatial priors. The averaged results of these segmentations formed the first MNI parametric maps of grey and white matter. The maps were never made publicly available in isolation but have formed parts of other packages for some time including SPM, FSL AIR and as models of grey matter for EEG source location in VARETTA and BRAINWAVE. Again, as these models are an approximation of Talairach space, there are differences in varying areas, to continue our use of origin shift as an example, the ICBM models are approximately 152: +3.5mm in Z and +-co-ordinate -3.5mm and 2.0mm in Y as compared to the original Talairach origin. In addition to the standard analysis performed on the ICBM data, 64 of the subjects data were segmented using model based segmentation. 64 of the original 305 were manually outlined and a resulting parametric VOI atlas built. The native data from these acquisitions was 256x256 with 1mm slices. The final image resolution of this data was 181x217x181 with 1mm isotropic voxels. Refer to the ICBM152 NonLinear if you are fitting an individual to model and do not care about left/right comparisons. A short history of the various atlases that have been produced at the BIC (McConnell Brain Imaging Center, Montreal Neurological Institute) is provided.

Proper citation: MINC/Atlases (RRID:SCR_005281) Copy   

•   Source: SciCrunch Registry

http://brainethics.org/

There are a lot of fine blogs out there covering the avalance of current neuroscience research. With this blog Thomas Rams��y & Martin Skov want to highlight the many consequences of this growing understanding of the human brain. We are especially interested in two types of consequences: Tinkering with the brain and What is it like to be a human being? * Tinkering with the brain: First and foremost, with an understanding of how the brain works comes the possibility of tinkering with it. We already use billions of dollars every year on psychopharmocologia trying to treat depression, schizophrenia, obsessive-compulsive disorder and other mental diseases. But should we also use our knowledge of the brain to treat undesirable mental traits such as pedophilia or sociopathy? And what about enhancing normal brains? Clearly, evolution hasn''t endowed us with the most efficient brain imaginable. Shouldn''t we do something about its many shortcomings? * What is it like to be a human being?: Secondly, our view of human behavior is sure to change with our improved understanding of the human brain. Our knowledge of core human faculties such as language, social reasoning, aesthetics, and economics is already being challenged by modern neuroscience, yielding multiple hard questions. Do we have a free will? Is the mind innate or plastic? If people are not responsible for their actions (since all actions are caused by blind molecular processes) does our legal system still make sense? In short, will modern neuroscience come to completely redefine human nature? We try to discuss contemporary research literature, not just news reports. Although we will occasionally also target popular science reports, since we believe they play an important role in dissemining lessons from the lab. And in the future we plan to also post interviews with interesting researchers, as well as link to our own publications in journals and books. Additionally, the latest and most important books in the multidisciplinary field of neuroscience, cognition, psychology, ethics and economics are presented.

Proper citation: BrainEthics (RRID:SCR_005530) Copy   

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http://fcon_1000.projects.nitrc.org/

Collection of resting state fMRI (R-fMRI) datasets from sites around world. It demonstrates open sharing of R-fMRI data and aims to emphasize aggregation and sharing of well-phenotyped datasets.

Proper citation: 1000 Functional Connectomes Project (RRID:SCR_005361) Copy   

•   Source: SciCrunch Registry