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http://www.cristudy.org/Chronic-Kidney-Disease/Chronic-Renal-Insufficiency-Cohort-Study/

A prospective observational national cohort study poised to make fundamental insights into the epidemiology, management, and outcomes of chronic kidney disease (CKD) in adults with intended long-term follow up. The major goals of the CRIC Study are to answer two important questions: * Why does kidney disease get worse in some people, but not in others? * Why do persons with kidney disease commonly experience heart disease and stroke? The CRIC Scientific and Data Coordinating Center at Penn receives data and provides ongoing support for a number of Ancillary Studies approved by the CRIC Cohort utilizing both data collected about CRIC study participants as well as their biological samples. The CRIC Study has enrolled over 3900 men and women with CKD from 13 recruitment sites throughout the country. Following this group of individuals over the past 10 years has contributed to the knowledge of kidney disease, its treatment, and preventing its complications. The NIDDKwill be extending the study for an additional 5 years, through 2018. An extensive set of study data is collected from CRIC Study participants. With varying frequency, data are collected in the domains of medical history, physical measures, psychometrics and behaviors, biomarkers, genomics/metabolomics, as well as renal, cardiovascular and other outcomes. Measurements include creatinine clearance and iothalamate measured glomerular filtration rate. Cardiovascular measures include blood pressure, ECG, ABI, ECHO, and EBCT. Clinical CV outcomes include MI, ischemic heart disease-related death, acute coronary syndromes, congestive heart failure, cerebrovascular disease, peripheral vascular disease, and composite outcomes. The CRIC Study has delivered in excess of 150,000 bio-samples and a dataset characterizing all 3939 CRIC participants at the time of study entry to the NIDDKnational repository. The CRIC Study will also be delivering a dataset to NCBI''''s Database for Genotypes and Phenotypes.

Proper citation: Chronic Renal Insufficiency Cohort Study (RRID:SCR_009016) Copy   

•   Source: SciCrunch Registry

http://www.centreducancer.be/en/show/index/section/8/page/34

When a patient suffering or thought to be suffering from cancer is cared for, samples are often taken to determine the precise diagnosis and to determine any treatment necessary. After this essential stage of the patient''s care, unused biological material is sometimes left over. This material is an essential and precious tool for research into cancer. For this reason, patients can decide to make the material available to researchers the world over who study either the development mechanism of cancer or the new treatments available. Residual samples are centralized and stored in the Tumor Bank at the Cliniques Universitaires Saint-Luc Cancer Centre. The research carried out on this material primarily benefits cancer patients. It can help improve existing treatments or discover new drugs, and also allows new diagnostic tools to be tested. Any financial profits obtained from assessing the results obtained are entirely reinvested in the work of the Cancer Centre''s Tumour Bank and in new research projects at the Catholic University of Louvain. Using and sharing material, and verification and retrospective analysis of clinical data, all comply with strict rules. As with donations of blood, marrow or organs, an Ethics Committee oversees the operations of the Tumour Bank and research projects. This committee is responsible for ensuring compliance with current Belgian and legal texts, especially those concerning the protection of patient privacy and rights.

Proper citation: Saint-Luc Tumour Bank (RRID:SCR_008714) Copy   

•   Source: SciCrunch Registry

http://ki.se/en/research/spotlight-on-parkinsons-disease

The primary purpose is to assess the importance of environmental factors for Parkinson's Disease (PD) in a population-based sample of Swedish twins. In PD discordant twin pairs, what are the environmental factors that contribute to the disease in the affected twin and or protect the unaffected twin? Second, we want to investigate whether the earlier reports of low heritability for elderly male twins can be confirmed for female pairs. All twins 55 years of age and older in the Swedish Twin Registry have been screened for most complex diseases. 626 twins have screened positive for PD and most pairs are discordant. To establish diagnosis, a physician will examine all potential cases and their co-twins and their medical records will be reviewed. Environmental factors will be studied through the use of discordant pairs, where genetic susceptibility to the disease can be controlled. Environmental exposures are being secured with telephone interviews and from a questionnaire collected 30 years ago. Recent results indicate that genetic factors play a very small role. A better understanding of the etiology of PD is important for the possibility of delaying onset or even preventing the disease, as well as for providing guidance for molecular biology studies. Types of samples * DNA Number of sample donors: 333 (sample collection completed)

Proper citation: KI Biobank - Parkinson (RRID:SCR_008866) Copy   

•   Source: SciCrunch Registry

http://www.wuxiapptec.com

A commercial organization for pharmaceutical, biopharmaceutical, and medical device open-access capability and technology platform with global operations.

Proper citation: WuXi AppTec Laboratory Services (RRID:SCR_001217) Copy   

•   Source: SciCrunch Registry

http://www.openbioinformatics.org/annovar/

An efficient software tool to utilize update-to-date information to functionally annotate genetic variants detected from diverse genomes (including human genome hg18, hg19, as well as mouse, worm, fly, yeast and many others). Given a list of variants with chromosome, start position, end position, reference nucleotide and observed nucleotides, ANNOVAR can perform: 1. gene-based annotation. 2. region-based annotation. 3. filter-based annotation. 4. other functionalities. (entry from Genetic Analysis Software)

Proper citation: ANNOVAR (RRID:SCR_012821) Copy   

•   Source: SciCrunch Registry

http://phenotips.cs.toronto.edu/

A software tool providing a Web interface and a database back-end for collecting clinical symptoms and physical findings observed in patients with genetic disorders. The main goals of this software are * To allow for collecting patient data in standard formats, enabling effortless data exchange and automated search in annotated gene and disease databases, and * To provide advanced functionalities and a friendly user interface that help reduce the clinician''''s workload, permitting seamless use of this application within the clinician''''s routine. PhenoTips uses the Human Phenotype Ontology (HPO) to express clinical phenotypes, and provides a friendly interface with error-tolerant, predictive search of phenotypic descriptions. PhenoTips closely mirrors clinician workflows: observations can be recorded directly during the patient encounter, and the interface is compatible with any device that runs a modern Web browser. The clinician can record demographic information, family history, medical history, various standard measurements, phenotypic abnormalities detected in the patient, pertinent indications that were not observed and that can be helpful for differential diagnosis, relevant images depicting manifestations of the patient''''s disorders, and additional notes for each of these categories. The software automatically plots growth curves, selects phenotypes reflecting abnormal measurements, instantly finds OMIM disorders matching the phenotypic description and suggests other symptoms to investigate in order to reach a more accurate diagnosis.

Proper citation: PhenoTips (RRID:SCR_006340) Copy   

•   Source: SciCrunch Registry

http://www.sph.umich.edu/csg/abecasis/GOLD/

Software package that provides a graphical summary of linkage disequilibrium in human genetic data. The graphical summary is well suited to the analysis of dense genetic maps, where contingency tables are cumbersome to interpret. An interface to the Simwalk2 application allows for the analysis of family data.

Proper citation: Graphical Overview of Linkage Disequilibrium (RRID:SCR_007151) Copy   

•   Source: SciCrunch Registry

http://mindboggle.info

Mindboggle (http://mindboggle.info) is open source software for analyzing the shapes of brain structures from human MRI data. The following publication in PLoS Computational Biology documents and evaluates the software: Klein A, Ghosh SS, Bao FS, Giard J, Hame Y, Stavsky E, Lee N, Rossa B, Reuter M, Neto EC, Keshavan A. (2017) Mindboggling morphometry of human brains. PLoS Computational Biology 13(3): e1005350. doi:10.1371/journal.pcbi.1005350

Proper citation: Mindboggle (RRID:SCR_002438) Copy   

•   Source: SciCrunch Registry

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

Pipeline developed for delineating the association between multiple diffusion properties along major white matter fiber bundles with a set of covariates of interest, such as age, diagnostic status and gender, and the structure of the variability of these white matter tract properties in various diffusion tensor imaging studies. FADTTS can be used to facilitate understanding of normal brain development, the neural bases of neuropsychiatric disorders, and the joint effects of environmental and genetic factors on white matter fiber bundles. The advantages of FADTTS compared with the other existing approaches are that they are capable of modelling the structured inter-subject variability, testing the joint effects, and constructing their simultaneous confidence bands.

Proper citation: Functional Analysis of Diffusion Tensor (RRID:SCR_008888) Copy   

•   Source: SciCrunch Registry

http://owlsim.org

Software package that provides the ability to do a number of standard semantic similarity methods and includes novel methods for combining these with dynamic selection of anonymous grouping classes. Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: OwlSim (RRID:SCR_006819) Copy   

•   Source: SciCrunch Registry

http://www.loni.usc.edu/Software/IO_Plugins

Decoders and encoders written in Java for the AFNI, ANALYZE, DICOM, ECAT, GE, MINC, NIFTI and other neuroimaging file formats.The plugins use Java Image I/O interfaces to read and write metadata and image data and can read and write AFNI, ANALYZE 7.5, DICOM, ECAT 7.2, GE 5.0, INTERFILE (including hrrt), MINC, NIFTI, and UCLA PACS file formats. All source code is provided and usage examples are included.

Proper citation: LONI Java Image I/O Plugins (RRID:SCR_008277) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://www.opencolleges.edu.au/

A resource for online accredited courses in a wide variety of areas, including accounting, animal care, beauty, building and construction, business, education, design and writing. This resource is based in Australia.

Proper citation: Open Colleges (RRID:SCR_000418) Copy   

•   Source: SciCrunch Registry

http://www.scienceexchange.com/facilities/tubingen-ageing-and-tumour-immunology-group-tati

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on April 19,2024. TATI is located at the Center for Medical Research (Zentrum fuer Medizinische Forschung, ZMF) within the University of Tuebingen Clinical School (Universitaetsklinikum Tuebingen) . We are engaged in immune monitoring (cancer immunotherapy, vaccination of elderly, Alzheimer) using 14-colour flow cytometry.

Proper citation: Tubingen Ageing and Tumour Immunology Group (RRID:SCR_012627) Copy   

•   Source: SciCrunch Registry

http://www.loni.usc.edu/Software/jViewbox

A portable software framework for medical imaging research. jViewbox consists of a set of Java classes organized under a simple but extensive API that provides the core functionality of 2D image presentation needed by most imaging applications. It follows Java's Swing model closely to make it easy for application developers to build GUIs where end users can use various tools in a tool bar to manipulate the image displays. No optional add-ons or native code is used, which makes jViewBox compatible with any standard Java 2 Runtime Environment (version 1.3 or later).

Proper citation: jViewbox (RRID:SCR_008274) Copy   

•   Source: SciCrunch Registry

http://compgenomics.utsa.edu/gene/gene_1.php

A Bayesian decision fusion algorithm for microRNA target prediction that combines the prediction of TargetScan, miRanda, PicTar, mirTarget, PITA, and DianamicroT. Users enter a Ref_seq ID for a query target gene and select a miRNA, which BCmicrO will use in its predictive algorithm. The prediction results can then be downloaded.

Proper citation: BCmicrO (RRID:SCR_010838) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://www.callisto-science.org/NSI/Neuroscience_Image_Database/Images%20of%20the%20Human%20Nervous%20System%20-%20Disease%20&%20Injury.html

A collection of images of the human nervous system focusing on disease and injury.

Proper citation: Human Nervous System Disease and Injury (RRID:SCR_006370) Copy   

•   Source: SciCrunch Registry

http://www.thevirtualbrain.org/

Simulation software for modeling the entire human brain by combining structural and functional data from empirical neuroimaging data. It can generate local field potentials, EEG, MEG and fMRI BOLD data based on neural mass models. The user can also modify the model parameters to match clinical conditions from focal lesions or degenerative disorders.

Proper citation: Virtual brain (RRID:SCR_002249) Copy   

•   Source: SciCrunch Registry

https://simtk.org/home/contrack

An algorithm for identifying pathways that are known to exist between two regions within DTI data of anisotropic tissue, e.g., muscle, brain, spinal cord. The ConTrack algorithms use knowledge of DTI scanning physics and apriori information about tissue architecture to identify the location of connections between two regions within the DTI data. Assuming a course of connection or pathway between these two regions is known to exist within the measured tissue, ConTrack can be used to estimate properties of these connections in-vivo.

Proper citation: ConTrack (RRID:SCR_002681) Copy   

•   Source: SciCrunch Registry