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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://ccr.coriell.org/Sections/Collections/CSCB/Default.aspx

Biospecimen repository that provides scientists with the opportunity to bank their pluripotent stem cell lines and develops in-house induced pluripotent stem cell (iPSC) lines for distribution. They have developed core capabilities to maintain, characterize, bank, and distribute important stem cell resources. The SCB performs extensive identification and characterization testing for all submitted human induced pluripotent stem cell (iPSC) and mouse embryonic stem cell (mES) lines. The identification and quality control measures include karyotype analysis, microsatellite analysis for parental cell line identity matching, sterility testing, and assessment of viability after cryopreservation. Pluripotency characterizations performed by SCB vary depending upon the distributing repository. * NIGMS iPSCs: Surface antigen expression, Embryoid body formation, Pluritest Gene Expression assay * NINDS iPSCs: Surface antigen expression, Embryoid body formation * NIA mES: Surface antigen expression, Embryoid body formation, Transgene induction Each characterized human iPSC line and mES line released for distribution is provided with a Certificate of Analysis, which includes information regarding characterization and quality of the line, images and links to original publications. The human iPSCs distributed by Coriell are strictly for research purposes and cannot be used in human subjects. All terms described in the Material Transfer Agreement (NIGMS and NINDS Repositories) or Assurance Form (NIA Repository) for the stem cell line must be agreed to prior to using stem cell lines from Coriell.

Proper citation: Coriell Institute Stem Cell Biobank (RRID:SCR_008745) Copy   

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http://nimhstemcells.org/

Induced Pluripotent Stem Cell (iPSC) and Source Cells available for distribution for postnatal-to-adult human control and patient-derived cells and their reprogrammed derivatives in support of stem cell research relevant to mental disorders. This includes but is not limited to anxiety disorders, attention deficit hyperactivity disorder, autism spectrum disorders, bipolar disorder, borderline personality disorder, depression, eating disorders, obsessive-compulsive disorder, panic disorder, post-traumatic stress disorder, and schizophrenia. The capabilities of the repository range from derivation and banking of primary source cells from postnatal through adult human subject tissue to more comprehensive banking and validation of induced pluripotent stem cells (iPSCs) or similar reprogrammed / de-differentiated cells. Please send a message with the Contact page if you wish to contribute source cells or iPSC.

Proper citation: NIMH Stem Cell Center (RRID:SCR_006682) Copy   

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http://www.genboree.org/epigenomeatlas/index.rhtml

Collection of human reference epigenomes and results of their integrative and comparative analyses. Successive releases of the Atlas will provide progressively more detailed insights into locus-specific epigenomic states, including histone marks and DNA methylation marks across specific tissues and cell types, developmental stages, physiological conditions, genotypes, and disease states. The Human Epigenome Atlas is produced by the NIH Epigenomics Roadmap Consortium.

Proper citation: Human Epigenome Atlas (RRID:SCR_006153) Copy   

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http://www.iit.edu/~mri/

Atlas that contains new anatomical, DTI, HARDI templates and probabilistic gray matter labels of the adult human brain in ICBM-152 space. Artifact-free MRI data from 72 human subjects was used in the development of the atlas. All diffusion MRI data collection was conducted using Turboprop, and spatial normalization was accomplished in a population-based fashion. A description of the contents of the atlas can be found in the Downloads link. NOTE: The files of the older IIT2 DTI Brain Template are still available. However, the new DTI template of the IIT Human Brain Atlas (v.3) is of superior quality and allows more accurate registration across subjects.

Proper citation: IIT Human Brain Atlas (RRID:SCR_009587) Copy   

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http://surfer.nmr.mgh.harvard.edu/fswiki/Tracula

Software tool developed for automatically reconstructing a set of major white matter pathways in the brain from diffusion weighted images using probabilistic tractography. This method utilizes prior information on the anatomy of the pathways from a set of training subjects. By incorporating this prior knowledge in the reconstruction procedure, our method obviates the need for manual intervention with the tract solutions at a later stage and thus facilitates the application of tractography to large studies. The trac-all script is used to preprocess raw diffusion data (correcting for eddy current distortion and B0 field inhomogenities), register them to common spaces, model and reconstruct major white matter pathways (included in the atlas) without any manual intervention. trac-all may be used to execute all the above steps or parts of it depending on the dataset and user''''s preference for analyzing diffusion data. Alternatively, scripts exist to execute chunks of each processing pipeline, and individual commands may be run to execute a single processing step. To explore all the options in running trac-all please refer to the trac-all wiki. In order to use this script to reconstruct tracts in Diffusion images, all the subjects in the dataset must have Freesurfer Recons.

Proper citation: TRACULA (RRID:SCR_013152) Copy   

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http://narayanahospitals.com/cellsofhope/

Narayana Hrudayalaya Tissue Bank and Stem Cell Research Center (NHTB-SCRC) is a joint venture between Rotary Bangalore Health City (RBHC) and Narayana Hrudayalaya. Our mission is to create awareness on Cord Blood Banking among the masses. Our vision is to make sure that every pregnant mother in India is able to afford to bank her child''s cord blood and cord tissue in a novel form of ������??Biological Insurance������??. The center would also assist in research and development of newer stem cell therapies. These goals are met while ensuring patient safety and well being by maintaining compliance with ICMR guidelines, Good Manufacturing Practice (GMP) guidelines, strict confidentiality and adherence to ethical standards. The private cord blood bank would store cord-blood and cord tissue derived stem cells for the exclusive use of clients who would pay for the cryo-storage, for a period of 21 years. These samples would be used for the child or its siblings anytime in the future, for therapy of various medical conditions. The public cord blood bank would enable us to collect cord blood from delivery and birthing centers, process these specimens, type their HLA signature and store them in ultra-low temperature conditions for use on prospective recipients. These recipients would have to be matched against their HLA signature with the stored stem cell concentrate. Patients with a disease treatable by stem cell therapy would have to have their HLA type known and they approach us for treatment. Such patients would be matched against our library of samples to identify a suitable match which would then be issued at a nominal cost. The cost of therapy would however be separate and informed to the patient before embarking on the treatment.

Proper citation: Narayana Hrudayalaya Tissue Bank and Stem Cell Research Center (RRID:SCR_010680) Copy   

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http://www.nitrc.org/projects/r-spit/

Group ICA (Independent Component Analysis) was used to generate spatial templates for 12 common resting-state networks in 62 typically-developing children, ages 9-15. They have made these available for those that will find them useful for masking and spatial template matching procedures. Basic demographic data on the sample is provided along with the protocol used to generate the templates.

Proper citation: resting-state pediatric imaging template (RRID:SCR_009647) Copy   

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http://www.nitrc.org/projects/autoseg/

A novel C++ based application developped at UNC-Chapel Hill that performs automatic brain tissue classification and structural segmentation. AutoSeg is designed for use with human and non-human primate pediatric, adolescent and adult data. AutoSeg uses a BatchMake pipeline script that includes the main steps of the framework entailing N4 bias field correction, rigid registration to a common coordinate image, tissue segmentation, skull-stripping, intensity rescaling, atlas-based registration, subcortical segmentation and lobar parcellation, regional cortical thickness and intensity statistics. AutoSeg allows efficient batch processing and grid computing to process large datasets and provides quality control visualizations via Slicer3 MRML scenes.

Proper citation: AutoSeg (RRID:SCR_009438) Copy   

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http://www.biobancusa.com/

BioBancUSA is a leading biotechnology company specializing in white blood cell collection, processing, cryopreservation and storage service. BioBancUSA, a private company headquartered in Monterey, California, is the exclusive licensee of the original patent for the collection, processing and cryopreservation technology of white blood cells, giving you the assurance of both technical integrity and legal legitimacy that you can count on. BioBancUSA is dedicated to providing our clients with the highest quality immune cell preservation for their future medical use. We are committed to the most advanced technology, exceptional, personalized service and leading-edge innovation to benefit our customers, health care providers, shareholders and employees.

Proper citation: Biobanc USA (RRID:SCR_010622) Copy   

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http://www.rucdr.org/

RUCDR is a biobank and a service organization that maintains human blood, serum, saliva, tissue and the genetic products derived from those. Services include technical consultation and logistical support for biobanking. Researchers can order biomaterials and apply for phenotypic / genotypic data.

Proper citation: Rutgers Cell and DNA Repository (RRID:SCR_010624) Copy   

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http://www.ntnu.edu/hunt

International biobank storing whole blood and DNA from 200,000 individuals, serum and plasma samples from more than 100,000 individuals as well as urine, RNA tubes, cells, buffy coat and Na-heparin tubes for environmental analysis for as many as 50,000 individuals. All bio-specimens from the HUNT surveys are collected, processed and stored at the HUNT Biobank in Levanger. The National CONOR Biobank is located on the same site, where it serves as a central research repository for DNA samples from all the largest Norwegian health surveys. These make up the Cohorts of Norway (CONOR), which include samples from more than 200,000 individuals. * HUNT 1 was carried out in 1984-1986 to establish the health history of 75,000 people. * HUNT 2, carried out in 1995-1997, focused on the evolution of the health history of 74,000 people. This included blood sample collection from 65,000 people. The data that accompany biospecimens in the biobank are stored in secured computer systems that run complex database management and analysis software. * HUNT 3 was completed in June 2008. 93,210 people were invited to participate in the study, and as of the 6th of June, 2008, 48,289 people participated (52% participation rate). The data, collected by means of questionnaires, interviews, clinical examinations and collection of blood and urine samples, will be ready for analysis in January 2009. * Young-HUNT is the adolescent part of HUNT including participants aged 13-19 years. Young-HUNT1 (1995-97) was conducted as part of HUNT2, 9141 adolescents participated (90% response rate). Young-HUNT2 (2000-01) was a follow-up study of Young-HUNT1, 2400 students participated in both studies (77% of the invited). Young-HUNT3 (2006-08) was a new cross-sectional study as part of HUNT3. This time 8677 adolescents participated (87% response rate). Data collection included self-reported questionnaires, structured interviews, clinical measurements and, in Young-HUNT3, buccal smears. All institutions with research expertise can apply for access to analyze HUNT data. Projects must have recommendations from The Regional Committee for Medical Research in Norway (REK) and be registered with The Norwegian Social Science Data Services (NSD).

Proper citation: Hunt Biobank (RRID:SCR_010626) Copy   

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http://mayoresearch.mayo.edu/mitochondrial-disease-biobank/

A biobank of blood and tissue samples from patients with known and suspected mitochondrial diseases along with data from their families. Samples are used in research to understand the family of mitochondrial disorders such as Alpers' syndrome, encephalopathy, and Friedrieich's ataxia, among many others. The goal of the biobank is to advance the understanding of mitochondrial disease and improve patient care.

Proper citation: Mayo Mitochondrial Disease Biobank (RRID:SCR_010598) Copy   

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http://www.ucl.ac.uk/ploras#annotations:QXuC2C7REeaxtw-aEPo07Q

A research project investigating the difficulties of recovering language after stroke (aphasia). The overall aim of the study is to give future stroke survivors accurate predictions of their aphasia recovery by creating clinical tools and discerning why some patients recover from aphasia better than others.

Proper citation: Predicting Language Outcome and Recovery After Stroke (PLORAS) (RRID:SCR_014498) Copy   

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http://purl.bioontology.org/ontology/DCO

Ontology that is a schema for information brokering and knowledge management in the complex field of rare diseases. On the one hand, the Dispedia schema uses semantic technologies to describe patients affected by rare diseases, and on the other hand, to record expertise concerning these particular diseases in machine-processable form. In addition to the differentiated attribution of facts to the individual need for information, Dispedia enables information brokering which adjusts to the type of recipient, its character as well as its personal attitude. The schema was initially geared to an exemplified disease, Amyotrophe Lateralsclerose (ALS).

Proper citation: Dispedia Core Ontology (RRID:SCR_010309) Copy   

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http://neurolog.i3s.unice.fr/public_namespace/ontology

An ontology for neuroimaging or medical imaging studies based on DOLCE (Descriptive Ontology for Linguistic and Cognitive Engineering), as the foundational ontology. Detailed description from web: Our aim is the design of a common semantic model providing a unified view on all data and tools to be shared between NeuroLOG partners. For this purpose, we built a multi-layered and multi-components formal ontology. We chose a design framework that structures the ontology at different levels of abstraction while respecting common conceptualization choices. At the highest level is a top-level ontology that includes abstract concepts and relationships valid across domains. We adopted DOLCE (Descriptive Ontology for Linguistic and Cognitive Engineering), as the foundational ontology. We then added Core ontologies, which provide generic, basic and minimal concepts and relations in a specific domain. By minimal we mean that core ontologies should include only the most reusable and widely applicable categories. These kinds of ontologies are essential for sharing intended meaning between different domains. We adopted I& DA (Information and Discourse Acts), a core ontology initially built for classifying documents as a function of their content.We use it to model medical images, which we consider as types of documents. Participant Roles is the core ontology we use to describe the modes of image participation in data processing. I& DA and Participant Roles are built according to DOLCE ontological commitments. On the basis of these two layers, we constructed our Domain ontology dedicated to conceptualizing a specific domain, in this case neuroimaging. Obviously, large domains such as neuroimaging can be divided into sub-domains for the sake of modularization.

Proper citation: OntoNeuroLOG (RRID:SCR_008957) Copy   

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http://www.uchicagoddrcc.org

Center whose goals include fostering collaboration among basic and clinical investigators, facilitating the use of new technologies in the study of treatment of digestive diseases, and providing education and training for improved treatment and diagnosis.

Proper citation: University of Chicago Digestive Diseases Research Core Center (RRID:SCR_015601) Copy   

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http://www.bsc.gwu.edu/dpp/index.htmlvdoc

Multicenter clinical research study aimed at discovering whether modest weight loss through dietary changes and increased physical activity or treatment with the oral diabetes drug metformin (Glucophage) could prevent or delay the onset of type 2 diabetes in study participants. At the beginning of the DPP, all 3,234 study participants were overweight and had blood glucose levels higher than normal but not high enough for a diagnosis of diabetesa condition called prediabetes. In addition, 45 percent of the participants were from minority groups-African American, Alaska Native, American Indian, Asian American, Hispanic/Latino, or Pacific Islander-at increased risk of developing diabetes. The DPP found that participants who lost a modest amount of weight through dietary changes and increased physical activity sharply reduced their chances of developing diabetes. Taking metformin also reduced risk, although less dramatically. In the DPP, participants from 27 clinical centers around the United States were randomly divided into different treatment groups. The first group, called the lifestyle intervention group, received intensive training in diet, physical activity, and behavior modification. By eating less fat and fewer calories and exercising for a total of 150 minutes a week, they aimed to lose 7 percent of their body weight and maintain that loss. The second group took 850 mg of metformin twice a day. The third group received placebo pills instead of metformin. The metformin and placebo groups also received information about diet and exercise but no intensive motivational counseling. A fourth group was treated with the drug troglitazone (Rezulin), but this part of the study was discontinued after researchers discovered that troglitazone can cause serious liver damage. The participants in this group were followed but not included as one of the intervention groups. In the years since the DPP was completed, further analyses of DPP data continue to yield important insights into the value of lifestyle changes in helping people prevent type 2 diabetes and associated conditions. For example, one analysis confirmed that DPP participants carrying two copies of a gene variant, or mutation, that significantly increased their risk of developing diabetes benefited from lifestyle changes as much as or more than those without the gene variant. Another analysis found that weight loss was the main predictor of reduced risk for developing diabetes in DPP lifestyle intervention group participants. The authors concluded that diabetes risk reduction efforts should focus on weight loss, which is helped by increased exercise.

Proper citation: Diabetes Prevention Program (RRID:SCR_001501) Copy   

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http://crispor.tefor.net

Web application that helps design, evaluate and clone guide sequences for the CRISPR/Cas9 system. This sgRNA design tool assists with guide selection in a variety of genomes and pre-calculated results for all human coding exons as a UCSC Genome Browser track.

Proper citation: CRISPOR (RRID:SCR_015935) Copy   

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https://www.med.upenn.edu/cbica/captk/

Software platform for analysis of radiographic cancer images. Used as quantitative imaging analytics for precision diagnostics and predictive modeling of clinical outcome.

Proper citation: Cancer Imaging Phenomics Toolkit (RRID:SCR_017323) Copy   

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