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http://rarediseasesnetwork.epi.usf.edu/index.htm

The Rare Diseases Clinical Research Network (RDCRN) was created to facilitate collaboration among experts in many different types of rare diseases. Our goal is to contribute to the research and treatment of rare diseases by working together to identify biomarkers for disease risk, disease severity and activity, and clinical outcome, while also encouraging development of new approaches to diagnosis, prevention, and treatment. The Rare Diseases Clinical Research Network (RDCRN) is made up of 19 distinctive consortia that are working in concert to improve availability of rare disease information, treatment, clinical studies, and general awareness for both patients and the medical community. The RDCRN also aims to provide up-to-date information for patients and to assist in connecting patients with advocacy groups, expert doctors, and clinical research opportunities.

Proper citation: Rare Diseases Clinical Research Network (RRID:SCR_004372) Copy   

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http://www.usidnet.org/

Research consortium to advance scientific research in the primary immune deficiency diseases (PIDD) and: * Assemble and maintain a registry of patients with primary immunodeficiency diseases to provide a minimum estimate of the prevalence of each disorder in the United States. Provide a comprehensive clinical picture of each disorder and act as a resource for clinical and laboratory research. * Establish a multifaceted mentoring program to introduce new investigators into the field and stimulate interest and research in primary immune deficiency diseases. * Establish an advisory/review committee to maintain a cell/DNA Repository of biologic material from well-characterized PIDD patients for the advancement of scientific research USIDNET operates a large database of patient information for your use. The purpose and scope of this project is to assemble and maintain a registry of residents with primary immunodeficiency diseases. The project was started with the Registry of U.S. Residents with Chronic Granulomatous Disease. Since then, the registry has been expanded and now collects data on all primary immunodeficiency disorders. The following are just a few of the diseases housed in the registry: Chronic Granulomatous Disease, Common Variable Immunodeficiency Disease, DiGeorge Anomaly, Hyper IgM Syndrome, Leukocyte Adhesion Defect, Severe Combined Immunodeficiency Disease, Wiskott-Aldrich Syndrome, X-Linked Agammaglobulinemia Physicians who would like to register their patients or access the registry are encouraged to contact Onika Davis or Lamar Hamilton, USIDNET team, at odavis (at) primaryimmune.org, or lhamilton (at) primaryimmune.org

Proper citation: USIDNET: US Immunodeficiency Network (RRID:SCR_004672) Copy   

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http://em.emory.edu/protect/index.cfm

Recently, our team completed an NINDS-funded, Phase IIa double-blinded, placebo-controlled pilot clinical trial that examined the pharmacokinetics, safety, and activity of progesterone, a steroid found to have powerful neuroprotective effects in multiple animal models of brain injury. Our pilot study demonstrated a 50% reduction in death among severe TBI patients and less disability among moderate TBI patients treated with progesterone. Based on these promising results and supportive preclinical data, we are conducting a large, phase III clinical trial (ProTECT III) to definitively assess the safety and efficacy of this treatment for adults with moderate to severe acute TBI. The study is slated to begin August 2008. WHY Progesterone: Although progresterone is widely considered a sex steroid, it is also a potent neurosteroid. Progesterone is naturally synthesized in the CNS. A large and growing body of animal studies indicate that early administration of progesterone after TBI reduces cerebral edema, neuronal loss, and behavioral deficits in laboratory animals. Certain properties of progesterone make it an ideal therapeutic candidate. First, in contrast to most drugs tested to date, progesterone rapidly enters the brain and reaches equilibrium with the plasma within an hour of administration. Second, unlike other experimental agents, progesterone has a long history of safe use in humans. Finally, the findings of our pilot clinical trial (presented in the Preliminary Data Section, below) indicate that progesterone has consistent and predictable pharmacokinetic properties, is unlikely to produce harm, and may be efficacious for treating acute TBI in humans.

Proper citation: ProTECT (RRID:SCR_004531) Copy   

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http://krasnow1.gmu.edu/cn3/hippocampus3d/

Data files for a high resolution three dimensional (3D) structure of the rat hippocampus reconstructed from histological sections. The data files (supplementary data for Ropireddy et al., Neurosci., 2012 Mar 15;205:91-111) are being shared on the Windows Live cloud space provided by Microsoft. Downloadable data files include the Nissl histological images, the hippocampus layer tracings that can be visualized alone or superimposed to the corresponding Nissl images, the voxel database coordinates, and the surface rendering VRML files. * Hippocampus Nissl Images: The high resolution histological Nissl images obtained at 16 micrometer inter-slice distance for the Long-Evans rat hippocampus can be downloaded or directly viewed in a browser. This dataset consists of 230 jpeg images that cover the hippocampus from rostral to caudal poles. This image dataset is uploaded in seven parts as rar files. * Hippocampus Layer Tracings: The seven hippocampus layers ''ML, ''GC'', ''HILUS'' in DG and ''LM'', ''RAD'', ''PC'', ''OR'' in CA were segmented (traced) using the Reconstruct tool which can be downloaded from Synapse web. This tool outputs all the tracings for each image in XML format. The XML tracing files for all these seven layers for each of the above Nissl images are zipped into one file and can be downloaded. * Hippocampus VoxelDB: The 3D hippocampus reconstructed is volumetrically transformed into 16 micrometer sized voxels for all the seven layers. Each voxel is reported according to multiple coordinate systems, namely in Cartesian, along the natural hippocampal dimensions, and in reference to the canonical brain planes. The voxel database file is created in ascii format. The single voxel database file was split into three rar archive files. Please note that the three rar archive files should be downloaded and decompressed in a single directory in order to obtain the single voxel data file (Hippocampus-VoxelDB.txt). * 3D Surface Renderings: This is a rar archive file with a single VRML file containing the surface rendering of DG and CA layers. This VRML file can be opened and visualized in any VRML viewer, e.g. the open source software view3dscene. * 3D Hippocampus Movie: This movie contains visualization of the 3D surface renderings of CA (blue) and DG (red) inner and outer boundaries; neuronal embeddings of DG granule and CA pyramidal dendritic arbors; potential synapses between CA3b interneuron axon and pyramidal dendrite, and between CA2 pyramidal axon and CA pyramidal dendrites.

Proper citation: Hippocampus 3D Model (RRID:SCR_005083) Copy   

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http://www.stanford.edu/group/brainsinsilicon/neurogrid.html

A specialized hardware platform that will perform cortex-scale emulations while offering software-like flexibility. With sixteen 12x14 sq-mm chips (Neurocores) assembled on a 6.5x7.5 sq-in circuit board that can model a slab of cortex with up to 16x256x256 neurons - over a million! The chips are interconnected in a binary tree by 80M spike/sec links. An on-chip RAM (in each Neurocore) and an off-chip RAM (on a daughterboard, not shown) softwire vertical and horizontcal cortical connections, respectively. It provides an affordable option for brain simulations that uses analog computation to emulate ion-channel activity and uses digital communication to softwire synaptic connections. These technologies impose different constraints, because they operate in parallel and in serial, respectively. Analog computation constrains the number of distinct ion-channel populations that can be simulatedunlike digital computation, which simply takes longer to run bigger simulations. Digital communication constrains the number of synaptic connections that can be activated per secondunlike analog communication, which simply sums additional inputs onto the same wire. Working within these constraints, Neurogrid achieves its goal of simulating multiple cortical areas in real-time by making judicious choices.

Proper citation: Neurogrid (RRID:SCR_005024) Copy   

•   Source: SciCrunch Registry

http://www.phrap.org/consed/consed.html

A graphical tool for sequence finishing (BAM File Viewer, Assembly Editor, Autofinish, Autoreport, Autoedit, and Align Reads To Reference Sequence)

Proper citation: Consed (RRID:SCR_005650) Copy   

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http://www.webarraydb.org/webarray/index.html

An open source integrated microarray database and analysis suite that features convenient uploading of data for storage in a MIAME (Minimal Information about a Microarray Experiment) compliant fashion. It allows data to be mined with a large variety of R-based tools, including data analysis across multiple platforms. Different methods for probe alignment, normalization and statistical analysis are included to account for systematic bias. Student's t-test, moderated t-tests, non-parametric tests and analysis of variance or covariance (ANOVA/ANCOVA) are among the choices of algorithms for differential analysis of data. Users also have the flexibility to define new factors and create new analysis models to fit complex experimental designs. All data can be queried or browsed through a web browser. The computations can be performed in parallel on symmetric multiprocessing (SMP) systems or Linux clusters.

Proper citation: WebArrayDB (RRID:SCR_005577) Copy   

•   Source: SciCrunch Registry

http://cs.nyu.edu/~bingsun/

NYU Bioinformatics group applies algorithmic, statistical, and mathematical techniques to solve problems of interest to biology, biotechnology and biomedicine. The group focuses on bioinformatics, computational biology and systems biology with many active projects in areas ranging from single molecules to entire populations: Analysis of Single-Molecule/Single-Cell Data, SPM-based Transcriptomic Profiling, Whole-Genome Haplotype Sequencing using SMASH (Single Molecule Approaches to Haplotype Sequencing), SUTTA (Scoring and Unfolding Trimmed Tree Assembler) assembly algorithm, Analysis of Spatio-Temporal Data, Model Checking and Model Building for Systems Biology, GOALIE-based Phenomenological Models and their Verification, Causality Analysis, Causal Models and their Verification, Analysis of EHR (Electronic Health Record Data) and Disease Models (e.g., Chronic Fatigue Syndrome, Congestive Heart Failure, Deep Vein Thrombosis, etc.), Models of Cancer, Applications to Pancreatic Cancer, Polymorphisms and Biomarkers, Strategies for Group Testing, Epidemiological and Bio-Warfare Models, Planning with Large Agent Networks against Catastrophes (PLAN C), Population Genomics, and Genome Wide Association Studies (GWAS). The group has received its funding from Air Force, Army, CCPR, DARPA, NIH, NIST, NSF, NYSTAR, etc. and various other governmental and commercial entities. Currently, the group is part of an NSF funded Expedition in Computing project (CMACS: Center for Modeling and Analysis of Complex Systems at CMU) and collaborates widely, both nationally and internationally. The group is highly multi-disciplinary, attracting researchers and students from mathematics, statistics, computer science, and biology who team up with physicians, physicists, and chemists as well as professionals in their own disciplines. This group is led by Prof. Bud Mishra, a professor of computer science and mathematics at NYU''s Courant Institute of Mathematical Sciences.

Proper citation: NYU Bioinformatics Group (RRID:SCR_005697) Copy   

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http://www.chori.org/

CHORI is the internationally renowned biomedical research institute of Children''s Hospital and Research Center at Oakland. With world-class scientists and research centers known both nationally and internationally in multiple fields, CHORI is 5th in the nation for National Institutes of Health pediatric research funding. Bridging basic science and clinical research in the treatment and prevention of human disease, CHORI is a leader in translational research, providing cures for blood diseases, developing new vaccines for infectious diseases, and discovering new treatment protocols for previously fatal or debilitating conditions. Striving to provide the highest standard of excellence and innovation, CHORI brings together a multidisciplinary collaborative of distinguished investigators in six different Centers of Research: The Center for Cancer Research, The Center for Genetics, The Center for Immunobiology & Vaccine Development, The Center for Nutrition & Metabolism, The Center for Prevention of Obesity, Cardiovascular Disease & Diabetes, and The Center for Sickle Cell Disease & Thalassemia. Within these major areas of focus, CHORI pushes the frontiers of science and of excellence beyond their borders. Among the leading biotech enterprises in the Bay Area, CHORI produced 25 patents in the last 5 years alone. In addition to providing world-class research, CHORI is also a teaching institute, offering unique educational opportunities to high school, college, doctoral and post-doctoral students.

Proper citation: Childrens Hospital Oakland Research Institute (RRID:SCR_005582) Copy   

•   Source: SciCrunch Registry

http://www.na-mic.org/Wiki/index.php/SoftwareInventory

A free open source software platform consisting of the 3D Slicer application software, a number of tools and toolkits such as VTK and ITK, and a software engineering methodology that enables multiplatform implementations. It also draws on other best practices from the community to support automatic testing for quality assurance. The NA-MIC kit uses a modular approach, where the individual components can be used by themselves or together. The NA-MIC kit is fully-compatible with local installation (behind institutional firewalls) and installation as an internet service. Significant effort has been invested to ensure compatibility with standard file formats and interoperability with a large number of external applications. Users of the NAMIC Kit will typically use a combination of its many modular components. * 3D Slicer is a general purpose application. Biomedical researchers will typically use this software tool to load, view, analyze, process and save image data. Slicer has been implemented to interoperate with many other tools, including XNAT, which is an open source image database. * Slicer modules, which are dynamically loaded by Slicer at run-time, can be used to extend Slicer''''s core functionality including defining graphical user interfaces. Modules are typically used by algorithms and application developers. * Application and algorithms developers may also use NA-MIC Kit toolkits and libraries. For example, the Insight Segmentation and Registration Toolkit ITK can be used to develop slicer modules for medical image analysis. The Visualization Toolkit can be used to process, visualize and graphically interact with data. KWWidgets is a 2D graphical user interface toolset that can be used to build applications. Teem is a library of general purpose command-line tools that are useful for processing data. Finally, those individuals wishing to create and manage complex software, the NAMIC-Kit software process is available as embodied in CMake, CTest, CPack, DART and the various documentation, bug tracking and communication tools.

Proper citation: NA-MIC Kit (RRID:SCR_005616) Copy   

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http://www.pbrc.edu/default.asp

Research institute which investigates chronic disease and its triggers.

Proper citation: Pennington Biomedical Research Center (RRID:SCR_002946) Copy   

•   Source: SciCrunch Registry

http://hapmap.ncbi.nlm.nih.gov/

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 22, 2016. A multi-country collaboration among scientists and funding agencies to develop a public resource where genetic similarities and differences in human beings are identified and catalogued. Using this information, researchers will be able to find genes that affect health, disease, and individual responses to medications and environmental factors. All of the information generated by the Project will be released into the public domain. Their goal is to compare the genetic sequences of different individuals to identify chromosomal regions where genetic variants are shared. Public and private organizations in six countries are participating in the International HapMap Project. Data generated by the Project can be downloaded with minimal constraints. HapMap project related data, software, and documentation include: bulk data on genotypes, frequencies, LD data, phasing data, allocated SNPs, recombination rates and hotspots, SNP assays, Perlegen amplicons, raw data, inferred genotypes, and mitochondrial and chrY haplogroups; Generic Genome Browser software; protocols and information on assay design, genotyping and other protocols used in the project; and documentation of samples/individuals and the XML format used in the project.

Proper citation: International HapMap Project (RRID:SCR_002846) Copy   

•   Source: SciCrunch Registry

http://www.compucell3d.org/

Open-source simulation environment for multi-cell, single-cell-based modeling of tissues, organs and organisms. It uses Cellular Potts Model to model cell behavior.

Proper citation: CompuCell3D (RRID:SCR_003052) Copy   

•   Source: SciCrunch Registry

http://www.broadinstitute.org/gsea/

Software package for interpreting gene expression data. Used for interpretation of a large-scale experiment by identifying pathways and processes.

Proper citation: Gene Set Enrichment Analysis (RRID:SCR_003199) Copy   

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http://compgen.bscb.cornell.edu/phast/

A freely available software package for comparative and evolutionary genomics that consists of about half a dozen major programs, plus more than a dozen utilities for manipulating sequence alignments, phylogenetic trees, and genomic annotations. For the most part, PHAST focuses on two kinds of applications: the identification of novel functional elements, including protein-coding exons and evolutionarily conserved sequences; and statistical phylogenetic modeling, including estimation of model parameters, detection of signatures of selection, and reconstruction of ancestral sequences. It consists of over 60,000 lines of C code.

Proper citation: PHAST (RRID:SCR_003204) Copy   

•   Source: SciCrunch Registry

https://bioportal.bioontology.org/ontologies/NEMO/?p=summary

Ontology that describes classes of event-related brain potentials (ERP) and their properties, including spatial, temporal, and functional (cognitive / behavioral) attributes, and data-level attributes (acquisition and analysis parameters). Its aim is to support data sharing, logic-based queries and mapping/integration of patterns across data from different labs, experiment paradigms, and modalities (EEG/MEG).

Proper citation: NEMO Ontology (RRID:SCR_003386) Copy   

•   Source: SciCrunch Registry

http://www.humanconnectomeproject.org/

A multi-center project comprising two distinct consortia (Mass. Gen. Hosp. and USC; and Wash. U. and the U. of Minn.) seeking to map white matter fiber pathways in the human brain using leading edge neuroimaging methods, genomics, architectonics, mathematical approaches, informatics, and interactive visualization. The mapping of the complete structural and functional neural connections in vivo within and across individuals provides unparalleled compilation of neural data, an interface to graphically navigate this data and the opportunity to achieve conclusions about the living human brain. The HCP is being developed to employ advanced neuroimaging methods, and to construct an extensive informatics infrastructure to link these data and connectivity models to detailed phenomic and genomic data, building upon existing multidisciplinary and collaborative efforts currently underway. Working with other HCP partners based at Washington University in St. Louis they will provide rich data, essential imaging protocols, and sophisticated connectivity analysis tools for the neuroscience community. This project is working to achieve the following: 1) develop sophisticated tools to process high-angular diffusion (HARDI) and diffusion spectrum imaging (DSI) from normal individuals to provide the foundation for the detailed mapping of the human connectome; 2) optimize advanced high-field imaging technologies and neurocognitive tests to map the human connectome; 3) collect connectomic, behavioral, and genotype data using optimized methods in a representative sample of normal subjects; 4) design and deploy a robust, web-based informatics infrastructure, 5) develop and disseminate data acquisition and analysis, educational, and training outreach materials.

Proper citation: MGH-USC Human Connectome Project (RRID:SCR_003490) Copy   

•   Source: SciCrunch Registry

http://ccdb.ucsd.edu/SAO

Ontology that describes structures from the dimensional range encompassing cellular and subcellular structure, supracellular domains, and macromolecules. It is built according to ontology development best practices (re-use of existing ontologies; formal definitions of terms; use of foundational ontologies). It describes the parts of neurons and glia and how these parts come together to define supracellular structures such as synapses and neuropil. Molecular specializations of each compartment and cell type are identified. The SAO was designed with the goal of providing a means to annotate cellular and subcellular data obtained from light and electron microscopy, including assigning macromolecules to their appropriate subcellular domains. The SAO thus provides a bridge between ontologies that describe molecular species and those concerned with more gross anatomical scales. Because it is intended to integrate into ontological efforts at these other scales, particular care was taken to construct the ontology in a way that supports such integration.

Proper citation: Subcellular Anatomy Ontology (RRID:SCR_003486) Copy   

•   Source: SciCrunch Registry

http://www.msmc.com/neurosciences/wien-center-for-alzheimers-disease-memory-disorders

A joint program between Mount Sinai Medical Center and the University of Miami Department of Psychiatry that seeks an end to Alzheimer's disease and similar disorders through research, diagnosis, education and treatment. The goals are to improve memory and mental responsiveness of Alzheimer's patients, delay the onset of the disease and, ultimately, find a cure. The Wien Center typically conducts multidisciplinary initiatives utilizing clinical trials.

Proper citation: Wien Center For Alzheimer's Disease and Memory Disorders (RRID:SCR_008755) Copy   

•   Source: SciCrunch Registry

http://mli.nih.gov/mli/

High throughput screening services to identify small molecules that can be optimized as chemical probes to study the functions of genes, cells, and biochemical pathways, along with medicinal chemistry and informatics. This will lead to new ways to explore the functions of genes and signaling pathways in health and disease. The NIH Molecular Libraries Initiative NIH is designed to discover small molecules that interact with biologically important proteins and pathways and to provide open access to the bioassay and chemical data generated by its research centers. This will lead to new ways to explore the functions of genes and signaling pathways in health and disease. As these HTS Technologies were not previously available to the public sector, many investigators may not be familiar with the components and requirements of high throughput screening. A key challenge is to identify small molecules effective at modulating a given biological process or disease state. The Molecular Libraries Roadmap, through one of its components, the Molecular Libraries Probe Production Centers Network (MLPCN), offers biomedical researchers access to the large-scale screening capacity, along with medicinal chemistry and informatics necessary to identify chemical probes to study the functions of genes, cells, and biochemical pathways. This will lead to new ways to explore the functions of genes and signaling pathways in health and disease. There are two kinds of data that are available to the scientific community through a dedicated database: Chemical Compounds and Bioassay Results (NCBI). Various types of data, including informative records on substances, compound structures, and biologically active properties of small molecules are housed respectively within PubChem''''s three primary databases: PCSubstance, PCCompound, and PCBioAssay. To date, PubChem contains over 11 million substance records, details about approximately 5.5 million unique compound structures with links to bioassay descriptions, relevant literature, references, and assay data points and over 250 bioassays, a good percentage of which were contributed by the pilot phase of the MLP. The deposition will continue during the current MLPCN phase. NIH anticipates that these projects will also facilitate the development of new drugs, by providing early stage chemical compounds that will enable researchers in the public and private sectors to validate new drug targets, which could then move into the drug-development pipeline. This is particularly true for rare diseases, which may not be attractive for development by the private sector. Funding opportunities are available through the site.

Proper citation: Molecular Libraries Program (RRID:SCR_008847) Copy   

•   Source: SciCrunch Registry