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https://cosmiic.org/

Open source neurostimulation and recording hardware instrument platform. Part of the SPARC project. COSMIIC is based on the Networked Neuroprosthesis developed at Case Western Reserve University.

Proper citation: COSMIIC HORNET (RRID:SCR_023679) Copy   

•   Source: SciCrunch Registry

https://github.com/VH-Lab/vhlab-microscopyimageanalysis-matlab

Software Matlab app for analysis of high density imaging data like that from Array Tomography.

Proper citation: vhlab-microscopyimageanalysis-matlab (RRID:SCR_024450) Copy   

•   Source: SciCrunch Registry

http://www.biosyn.com/

A commercial supplier of custom synthetic molecules. They specialize in peptides, oligonucleotides, bioconjugation, molecular biology services, proteins and specialty chemistry.

Proper citation: Bio-Synthesis (RRID:SCR_000820) Copy   

•   Source: SciCrunch Registry

http://www.midasplatform.org/

Open-source toolkit that enables the rapid creation of tailored, web-enabled data storage and provides a cohesive system for data management, visualization, and processing. At its core, Midas Platform is implemented as a PHP modular framework with a backend database (PostGreSQL, MySQL and non-relational databases). While the Midas Platform system can be installed and deployed without any customization, the framework has been designed with customization in mind. As building one system to fit all is not optimal, the framework has been extended to support plugins and layouts. Through integration with a range of other open-source toolkits, applications, or internal proprietary workflows, Midas Platform offers a solid foundation to meet the needs of data-centric computing. Midas Platform provides a variety of data access methods, including web, file system and DICOM server interfaces, and facilitates extending the methods in which data is stored to other relational and non-relational databases.

Proper citation: Midas Platform (RRID:SCR_002186) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://www.nlm.nih.gov/NIHbmic/nih_data_sharing_repositories.html

A listing of NIH supported data sharing repositories that make data accessible for reuse. Most accept submissions of appropriate data from NIH-funded investigators (and others), but some restrict data submission to only those researchers involved in a specific research network. Also included are resources that aggregate information about biomedical data and information sharing systems. The table can be sorted according by name and by NIH Institute or Center and may be searched using keywords so that you can find repositories more relevant to your data. Links are provided to information about submitting data to and accessing data from the listed repositories. Additional information about the repositories and points-of-contact for further information or inquiries can be found on the websites of the individual repositories.

Proper citation: NIH Data Sharing Repositories (RRID:SCR_003551) Copy   

•   Source: SciCrunch Registry

http://neurospy.org

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   

•   Source: SciCrunch Registry

http://dockground.bioinformatics.ku.edu/

Data sets, tools and computational techniques for modeling of protein interactions, including docking benchmarks, docking decoys and docking templates. Adequate computational techniques for modeling of protein interactions are important because of the growing number of known protein 3D structures, particularly in the context of structural genomics. The first release of the DOCKGROUND resource (Douguet et al., Bioinformatics 2006; 22:2612-2618) implemented a comprehensive database of cocrystallized (bound) protein-protein complexes in a relational database of annotated structures. Additional releases added features to the set of bound structures, such as regularly updated downloadable datasets: automatically generated nonredundant set, built according to most common criteria, and a manually curated set that includes only biological nonobligate complexes along with a number of additional useful characteristics. Also included are unbound (experimental and simulated) protein-protein complexes. Complexes from the bound dataset are used to identify crystallized unbound analogs. If such analogs do not exist, the unbound structures are simulated by rotamer library optimization. Thus, the database contains comprehensive sets of complexes suitable for large scale benchmarking of docking algorithms. Advanced methodologies for simulating unbound conformations are being explored for the next release. The Dockground project is developed by the Vakser lab at the Center for Bioinformatics at the University of Kansas. Parts of Dockground were co-developed by Dominique Douguet from the Center of Structural Biochemistry (INSERM U554 - CNRS UMR5048), Montpellier, France.

Proper citation: Dockground: Benchmarks, Docoys, Templates, and other knowledge resources for DOCKING (RRID:SCR_007412) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://compbio.cs.princeton.edu/conservation/

Software for scoring protein sequence conservation using the Jensen-Shannon divergence. It can be used to predict catalytic sites and residues near bound ligands.

Proper citation: Conservation (RRID:SCR_016064) Copy   

•   Source: SciCrunch Registry

http://immport.org/immport-open/public/reference/cytokineRegistry

A registry of cytokines, chemokines, and receptors generated for the purpose of collecting, integrating, and mapping between entity names and synonyms from several resources. These resources include MeSH, the Protein Ontology, EntrezGene, HGNC, MGI, UniProt and others.

Proper citation: Cytokine Registry (RRID:SCR_014368) Copy   

•   Source: SciCrunch Registry

https://bioinformatics.niaid.nih.gov/chemokinedb/

Resource of chemokines and receptors with detailed information including taxonomy, nomenclature, structure, physiological function, tissue information, and phenotype, collected from IUPHAR/BPS, UniGene, and UniProt public databases.

Proper citation: ChemokineDB (RRID:SCR_016593) Copy   

•   Source: SciCrunch Registry

http://software.broadinstitute.org/gsea/msigdb/index.jsp

Collection of annotated gene sets for use with Gene Set Enrichment Analysis (GSEA) software.

Proper citation: Molecular Signatures Database (RRID:SCR_016863) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://mind.loni.usc.edu

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

https://nationalmaglab.org/user-facilities/icr

Facility provides service operations for sample analysis that requires ultrahigh resolution and high mass accuracy of Fourier Transform Ion Cyclotron Resonance. Used for research in biomolecular analysis, hydrogen-deuterium exchange and environmental and petrochemical analysis. Four FT-ICR mass spectrometers feature high magnetic fields including the world-record 21 tesla and are compatible with multiple ionization and fragmentation techniques.

Proper citation: National High Magnetic Field Laboratory Ion Cyclotron Resonance Core Facility (RRID:SCR_017361) Copy   

•   Source: SciCrunch Registry