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Curriculum materials for an Introduction to Neurobiology course for undergraduate and graduate students.
The course focuses on the analysis of neurons and neural circuits for behavior using the fundamental principles of neuroscience. From the online course syllabus, the 24 units that make up the course may be directly accessed. Each unit contains a reading, links to at least one simulation, and a problem set.
A list of all available simulations can be found here: https://neurowiki.case.edu/wiki/Simulations. * 25 simulations are written in JavaScript and will run in any browser.
Source code: https://github.com/CWRUChielLab/JSNeuroSim * Pre-compiled executables (Windows, Mac, Linux) are available for 1 desktop simulation, the Nernst Potential Simulator.
Source code: https://github.com/CWRUChielLab/Nernst Structure of the Course * Solving problems based on simulations of neuronal components, neurons, and simple circuits to understand how they work. * For advanced students, writing a neuroscience Wikipedia article, critical review, or grant, in stages.
Proper citation: NeuroWiki (RRID:SCR_004066) Copy
The European resource for the collection, organization and dissemination of data on biological macromolecular structures. In collaboration with the other worldwide Protein Data Bank (wwPDB) partners - the Research Collaboratory for Structural Bioinformatics (RCSB) and BioMagResBank (BMRB) in the USA and the Protein Data Bank of Japan (PDBj) - they work to collate, maintain and provide access to the global repository of macromolecular structure data. The main objectives of the work at PDBe are: * to provide an integrated resource of high-quality macromolecular structures and related data and make it available to the biomedical community via intuitive user interfaces. * to maintain in-house expertise in all the major structure-determination techniques (X-ray, NMR and EM) in order to stay abreast of technical and methodological developments in these fields, and to work with the community on issues of mutual interest (such as data representation, harvesting, formats and standards, or validation of structural data). * to provide high-quality deposition and annotation facilities for structural data as one of the wwPDB deposition sites. Several sophisticated tools are also available for the structural analysis of macromolecules.
Proper citation: PDBe - Protein Data Bank in Europe (RRID:SCR_004312) Copy
http://www.mprc.umaryland.edu/mbc.asp
The Maryland Brain Collection (MBC), a resource of the Maryland Psychiatric Research Center (MPRC), is dedicated to promoting research with brain tissue obtained post-mortem from individuals with schizophrenia or related disorders. The primary goal of the MBC is to provide high-quality tissue, along with comprehensive clinical information, for hypothesis-driven research. The MBC is not conceptualized as a Brain Bank with open access but is maintained and funded through collaborative research. The Maryland Brain Collection is managed by researchers at the Maryland Psychiatric Research Center (MPRC). MPRC scientists are dedicated to understanding the causes and improving the treatment of mental illness. The Maryland Brain Collection is associated with the Office of the Chief Medical Examiner for the State of Maryland and other donor sources. MPRC scientists collaborate with scientists from around the world to understand how abnormalities in brain tissue relate to mental illness. The purpose of the MBC is to study the following: Schizophrenia, Bipolar Disorder, Depression, Suicide/Teen suicide, Substance Abuse.
Proper citation: Maryland Brain Collection (RRID:SCR_004384) Copy
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
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
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
https://github.com/jefftc/changlab
Software system for performing bioinformatics analyses. System includes knowledge base where the capabilities of bioinformatics software is explicitly and formally encoded. Backwards-chaining rule-based expert system comprised of data model that can capture richness of biological data, and inference engine that reasons on knowledge base to produce workflows. Knowledge base is populated with rules to analyze microarray and next generation sequencing data.
Proper citation: BETSY (RRID:SCR_026239) Copy
neurospy is a free software for functional imaging of fast neuronal activity. neurospy is a modular cross-platform application framework written in Java for the NetBeans Platform. At this time it runs on Windows XP-based LeCroy oscilloscopes and drives acousto-optic scanners via USB using the Analog Devices 9959 Direct Digital Synthesis chip. This combination makes one of the most powerful systems for scanning microscopy available today at any price. neurospy is very easy to port to other kinds of acquisition and scanning hardware.
Proper citation: neurospy (RRID:SCR_007016) Copy
http://www.sb.fsu.edu/~rsref/Distribution/roadmap_distribution.htm
Software tool to display surface of macromolecule and its properties. Uses projections to map van der Waals or solvent accessible surface of macromolecule onto plane., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.
Proper citation: Roadmap (RRID:SCR_017207) Copy
https://ncats.nih.gov/grdr/rdhub
A database of biospecimens collected, stored, and distributed by biorepositories in the United States and around the globe. Its goals are: To help and assist interested parties and investigators search, locate, and identify desired biospecimens needed for their research; to facilitate collaboration and sharing of material and data among investigators across the globe; to accelerate research to facilitate the discovery of new treatments, therapeutics and eventually cures for rare diseases as well as common diseases; to identify, locate and increase the awareness of existing biorepositories across the globe; and to link the RD-HUB with the Global Rare Diseases Patient Registry and Data Repository (GRDR).
Proper citation: Biospecimens/Biorepositories: Rare Disease-HUB (RD-HUB) (RRID:SCR_004327) Copy
The MiND: Metadata in NIfTI for DWI framework enables data sharing and software interoperability for diffusion-weighted MRI. This site provides specification details, tools, and examples of the MiND mechanism for representing important metadata for DWI data sets at various stages of post-processing. MiND framework provides a practical solution to the problem of interoperability between DWI analysis tools, and it effectively expands the analysis options available to end users. To assist both users and developers in working with MiND-formatted files, we provide a number of software tools for download. * MiNDHeader A utility for inspecting MiND-extended files. * I/O Libraries Programming libraries to simplify writing and parsing MiND-formatted data. * Sample Files Example files for each MiND schema. * DIRAC LONI''s Diffusion Imaging Reconstruction and Analysis Collection is a DWI processing suite which utilizes the MiND framework.
Proper citation: LONI MiND (RRID:SCR_004820) Copy
http://ccr.coriell.org/Sections/Collections/USIDNET/?SsId=15
The USIDNET DNA and Cell Repository has been established as part of an NIH-funded program - the US Immunodeficiency Network - to provide a resource of DNA and functional lymphoid cells obtained from patients with various primary immunodeficiency diseases. These uncommon disorders include patients with defects in T cell, B cell and/or granulocyte function as well as patients with abnormalities in antibodies / immunoglobulins, complement and other host defense mechanisms. All samples in this Repository have been de-identified to protect the privacy of the individual donors. The USIDNET also operates a Patient Data Registry in addition to this Repository and certain clinical data relating to a specific sample may be available through the Registry for some of the patient samples in the Repository collection. Materials in the collection are being made available at modest cost to qualified investigators in academic and commercial organizations in an effort to stimulate research to increase understanding of these orphan diseases and to promote development of new treatments. Requestors are required to complete a Statement of Research Intent briefly describing their proposed use of materials obtained from the Repository and must sign an Assurance agreeing to conditions established by USIDNET for distribution of samples from its collection. Requestors wishing to obtain additional clinical data specific to individual samples in the Repository collection must make a separate application for that information to the Registry (see www.usidnet.org) Physicians or Patients wishing to submit cell samples for the Repository collection should first contact Coriell to arrange for the Repository to send them the correct sample collection tubes as well as prepaid mailers for returning the collected sample(s) to Coriell. Separate collection and shipping procedures may be involved depending on how many samples are to be shipped at one time and whether the shipment will involve freshly obtained blood or already established cell lines.
Proper citation: USIDNET DNA and Cell Repository (RRID:SCR_004661) Copy
http://ki.se/en/meb/twingene-and-genomeeutwin
In collaboration with GenomeEUtwin, the TwinGene project investigates the importance of quantitative trait loci and environmental factors for cardiovascular disease. It is well known that genetic factors are of considerable importance for some familial lipid syndromes and that Type A Behavior pattern and increased lipid levels infer increased risk for cardiovascular disease. It is furthermore known that genetic factors are of importance levels of blood lipid biomarkers. The interplay of genetic and environmental effects for these risk factors in a normal population is less well understood and virtually unknown for the elderly. In the TwinGene project twins born before 1958 are contacted to participate. Health and medication data are collected from self-reported questionnaires, and blood sampling material is mailed to the subject who then contacts a local health care center for blood sampling and a health check-up. In the simple health check-up, height, weight, circumference of waist and hip, and blood pressure are measured. Blood is sampled for DNA extraction, serum collection and clinical chemistry tests of C-reactive protein, total cholesterol, triglycerides, HDL and LDL cholesterol, apolipo��protein A1 and B, glucose and HbA1C. The TwinGene cohort contains more than 10000 of the expected final number of 16000 individuals. Molecular genetic techniques are being used to identify Quantitative Trait Loci (QTLs) for cardiovascular disease and biomarkers in the TwinGene participants. Genome-wide linkage and association studies are ongoing. DZ twins have been genome-scanned with 1000 STS markers and a subset of 300 MZ twins have been genome-scanned with Illumina 317K SNP platform. Association of positional candidate SNPs arising from these genomscans are planned. The TwinGene project is associated with the large European collaboration denoted GenomEUtwin (www.genomeutwin.org, see below) which since 2002 has aimed at gathering genetic data on twins in Europe and setting up the infrastructure needed to enable pooling of data and joint analyses. It has been the funding source for obtaining the genome scan data. Types of samples: * EDTA whole blood * DNA * Serum Number of sample donors: 12 044 (sample collection completed)
Proper citation: KI Biobank - TwinGene (RRID:SCR_006006) Copy
http://www.sph.umich.edu/csg/abecasis/CaTS
Software tool for carrying out power calculations for large genetic association studies, including two stage genome wide association studies.
Proper citation: Calculator for Association with Two Stage design (RRID:SCR_007238) Copy
http://ki-su-arc.se/dementia-in-swedish-twins-harmony/
A twin study characterizing the importance of genetic factors for dementia and using discordant twin pairs to study other putative risk factors which control for genetic propensity to develop the disease. Molecular genetic studies have identified a number of mutations and other markers associated with early age of onset Alzheimer''''s disease. However, most cases of late age of onset dementia are considered sporadic, that is, without a clear genetic basis. Twin studies provide a unique opportunity to characterize the importance of genetic factors for dementia. Discordant twin pairs additionally provide the opportunity to study other putative risk factors which controlling for genetic propensity to develop the disease. In the first wave of the Study of Dementia in Swedish Twins, all SATSA twins born before 1935 have been screened for dementia symptoms. Over 190 suspects have been identified. This pilot study has been expanded to the entire registry in the study known as HARMONY. All twins aged 65 and older were invited to participate in a computer assisted telephone screening interview. A total of 13,519 individuals completed the interview (response rate = 75.9%). Dementia screening was based on the TELE, which includes the 10-item MSQ, other cognitive items (counting backwards, recalling three words, and similarities), and questions about health and daily functioning; or on Blessed scores obtained from a proxy interview. Among those screened, 1565 were positive for suspicion of dementia and were referred for complete clinical evaluation by a physician and a nurse. Once the preliminary in-person evaluation suggested that the suspected case was demented, the twin partner was also invited for an identical clinical work-up. Response rate for clinical evaluations is 71.4%. Approximately half of those visited for evaluation have been diagnosed as demented according to DSM-IV criteria, of which two-thirds have Alzheimer''''s disease. An extensive assessment of probable risk exposure is also included. Longitudinal follow-up is yet another feature of the study. Association studies with candidate genes are also being performed. Types of samples * DNA Number of sample donors * 1154 (sample collection completed)
Proper citation: KI Biobank - HARMONY (RRID:SCR_008884) Copy
http://ccb.jhu.edu/software/glimmerhmm/
A gene finder based on a Generalized Hidden Markov Model (GHMM). Although the gene finder conforms to the overall mathematical framework of a GHMM, additionally it incorporates splice site models adapted from the GeneSplicer program and a decision tree adapted from GlimmerM. It also utilizes Interpolated Markov Models for the coding and noncoding models . Currently, GlimmerHMM's GHMM structure includes introns of each phase, intergenic regions, and four types of exons (initial, internal, final, and single).
Proper citation: GlimmerHMM (RRID:SCR_002654) Copy
geWorkbench (genomics Workbench) is a Java-based open-source platform for integrated genomics. Using a component architecture it allows individually developed plug-ins to be configured into complex bioinformatic applications. At present there are more than 70 available plug-ins supporting the visualization and analysis of gene expression and sequence data. Example use cases include: * loading data from local or remote data sources. * visualizing gene expression, molecular interaction networks, protein sequence and protein structure data in a variety of ways. * providing access to client- and server-side computational analysis tools such as t-test analysis, hierarchical clustering, self organizing maps, regulatory networks reconstruction, BLAST searches, pattern/motif discovery, etc. * validating computational hypothesis through the integration of gene and pathway annotation information from curated sources as well as through Gene Ontology enrichment analysis. geWorkbench is the Bioinformatics platform of MAGNet, the National Center for the Multi-scale Analysis of Genomic and Cellular Networks (one of the 7 National Centers for Biomedial Computing funded through the NIH Roadmap). Additionally, geWorkbench is supported by caBIG, NCI''s cancer Biomedical Informatics Grid initiative.
Proper citation: genomics Workbench (RRID:SCR_013599) Copy
http://www.metabolomicsworkbench.org
Repository for metabolomics data and metadata which provides analysis tools and access to various resources. NIH grantees may upload data and general users can search metabolomics database. Provides protocols for sample preparation and analysis, information about NIH Metabolomics Program, data sharing guidelines, funding opportunities, services offered by its Regional Comprehensive Metabolomics Resource Cores (RCMRC)s, and training workshops.
Proper citation: Metabolomics Workbench (RRID:SCR_013794) Copy
A consortium whose goal is to further HIV research and accelerate the development of a preventative HIV vaccine. Its main research target is to define immunogens and immunization regimens that induce sustained HIV cross-protective B cell and CD4+ T cell responses.
Proper citation: CHAVI-ID (RRID:SCR_014047) Copy
MATLAB and Python 3 high-level programming interface for MySQL databases to support data processing chains in science labs. Specifically designed to provide robust and intuitive data model for scientific data processing chains.Used for scientific data pipelines and workflow management.
Proper citation: DataJoint (RRID:SCR_014543) Copy
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