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http://www.crdamc.amedd.army.mil/behav-health/strong-star.aspx

A multidisciplinary and multi-institutional research consortium to develop and evaluate the most effective early interventions possible for the detection, prevention, and treatment of combatrelated posttraumatic stress disorder (PTSD) in activeduty military personnel and recently discharged veterans. Complementary investigations are focused on the root causes of PTSD, including biological factors that influence PTSD susceptibility and recovery; the influence of comorbid physical and psychological ailments; and the interaction of cognitive-behavioral therapies and pharmacologic treatments. The full cohort of STRONG STAR trials include: Treatment Studies, Biological Studies, Epidemiological Studies, and Preclinical Studies. STRONG STAR is currently conducting three clinical treatment trials at Carl R. Darnall Army Medical Center (CRDAMC). The studies are examining the effectiveness of Cognitive Processing Therapy (CPT), Prolonged Exposure Therapy (PE) and Cognitive Behavioral Therapy for Insomnia (CBTi) with active duty service members. Treatments are offered in individual, group, and online formats, and last from two to eight weeks. Study participants must be active duty service members who will remain in the Ft Hood area for at least 34 months to complete initial assessments and treatment programs. Referrals to the treatment studies can be made through a behavioral health provider or through selfreferral., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Strong Star (RRID:SCR_003132) Copy   

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http://rostlab.org/services/nlsdb/

A database of nuclear localization signals (NLSs) and of nuclear proteins targeted to the nucleus by NLS motifs. NLSs are short stretches of residues mediating transport of nuclear proteins into the nucleus. The database contains 114 experimentally determined NLSs that were obtained through an extensive literature search. Using "in silico mutagenesis" this set was extended to 308 experimental and potential NLSs. This final set matched over 43% of all known nuclear proteins and matches no currently known non-nuclear protein. NLSdb contains over 6000 predicted nuclear proteins and their targeting signals from the PDB and SWISS-PROT/TrEMBL databases. The database also contains over 12 500 predicted nuclear proteins from six entirely sequenced eukaryotic proteomes (Homo sapiens, Mus musculus, Drosophila melanogaster, Caenorhabditis elegans, Arabidopsis thaliana and Saccharomyces cerevisiae). NLS motifs often co-localize with DNA-binding regions. This observation was used to also annotate over 1500 DNA-binding proteins. From this site you can: * Query NLSdb * Find out how to use NLSdb * Browse the entries in NLSdb * Find out if your protein has an NLS using PredictNLS * Predict subcellular localization of your protein using LOCtree

Proper citation: NLSdb: a database of nuclear localization signals (RRID:SCR_003273) Copy   

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http://braininfo.rprc.washington.edu

Portal to neuroanatomical information on the Web that helps you identify structures in the brain and provides a variety of information about each structure by porting you to the best of 1500 web pages at 100 other neuroscience sites. BrainInfo consists of three basic components: NeuroNames, a developing database of definitions of neuroanatomic structures in four species, their most common acronyms and their names in eight languages; NeuroMaps, a digital atlas system based on 3-D canonical stereotaxic atlases of rhesus macaque and mouse brains and programs that enable one to map data to standard surface and cross-sectional views of the brains for presentation and publication; and the NeuroMaps precursor: Template Atlas of the Primate Brain, a 2-D stereotaxic atlas of the longtailed (fascicularis) macaque brain that shows the locations of some 250 architectonic areas of macaque cortex. The NeuroMaps atlases will soon include a number of overlays showing the locations of cortical areas and other neuroscientific data in the standard frameworks of the macaque and mouse atlases. Viewers are encouraged to use NeuroNames as a stable source of unique standard terms and acronyms for brain structures in publications, illustrations and indexing systems; to use templates extracted from the NeuroMaps macaque and mouse brain atlases for presenting neuroscientific information in image format; and to use the Template Atlas for warping to MRIs or PET scans of the macaque brain to estimate the stereotaxic locations of structures.

Proper citation: BrainInfo (RRID:SCR_003142) Copy   

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http://dip.doe-mbi.ucla.edu/

Database to catalog experimentally determined interactions between proteins combining information from a variety of sources to create a single, consistent set of protein-protein interactions that can be downloaded in a variety of formats. The data were curated, both, manually and also automatically using computational approaches that utilize the the knowledge about the protein-protein interaction networks extracted from the most reliable, core subset of the DIP data. Because the reliability of experimental evidence varies widely, methods of quality assessment have been developed and utilized to identify the most reliable subset of the interactions. This CORE set can be used as a reference when evaluating the reliability of high-throughput protein-protein interaction data sets, for development of prediction methods, as well as in the studies of the properties of protein interaction networks. Tools are available to analyze, visualize and integrate user's own experimental data with the information about protein-protein interactions available in the DIP database. The DIP database lists protein pairs that are known to interact with each other. By interact they mean that two amino acid chains were experimentally identified to bind to each other. The database lists such pairs to aid those studying a particular protein-protein interaction but also those investigating entire regulatory and signaling pathways as well as those studying the organization and complexity of the protein interaction network at the cellular level. Registration is required to gain access to most of the DIP features. Registration is free to the members of the academic community. Trial accounts for the commercial users are also available.

Proper citation: Database of Interacting Proteins (DIP) (RRID:SCR_003167) Copy   

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https://rdrr.io/bioc/yaqcaffy/

Software package for quality control of Affymetrix GeneChip expression data and reproducibility analysis of human whole genome chips with the MAQC reference datasets.

Proper citation: yaqcaffy (RRID:SCR_001295) Copy   

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http://pathology.wustl.edu/VirusHunter/

A fully automated and modular software package for mining sequence data to identify sequences of microbial origin. The pipeline was optimized for analysis of data generated by the Roche/454 next-generation sequencing platform but can be applied to longer sequences (Sanger sequencing data or assembled contigs) as well. Microbial sequences are identified on the basis of BLAST alignments and the taxonomic classification of the reference sequence(s) to which a read is aligned. Viruses are the focal point of VirusHunter as released, but it can be easily modified to generate parallel outputs for bacterial or parasitic species. To date, VirusHunter has been applied to thousands of specimens, including human, animal and environmental samples, resulting in the detection of many known and novel viruses.

Proper citation: VirusHunter (RRID:SCR_001198) Copy   

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http://www.biobase-international.com/product/genome-trax

Service that provides a comprehensive compilation of variant knowledge that allows you to identify pathogenic variants in human whole genome or exome sequences. It makes it easy to upload a complete genome?s worth of variations and identify the biologically relevant subset of known mutations, mutations that are novel and appear in a candidate disease genes, or mutations that are predicted to have a deleterious effect. The database includes a comprehensive collection of disease causing mutations from HGMD Professional, regulatory sites from TRANSFAC , and disease genes, drug targets and pathways from PROTEOME, as well as pharmacogenomic variants. It integrates the best public data-sets on somatic mutations, allele frequencies and clinical variants, in their most up-to-date version, for a total of more than 165 million annotations. It is possible to identify known pathogenic variants, remove harmless common variants, and obtain deleterious predictions for novel variants. With family data, it is possible to identify variants that are de novo, compound heterozygous only in the offspring. All of the results can be downloaded to Excel for further review. For core facilities and bioinformaticians, the complete underlying data is made available for download and easy integration into custom analysis pipelines. Genome Trax data is optimized to work with many other software packages, such as ANNOVARTM, CLC bio, Alamut, SimulConsult, and Cartagenia.

Proper citation: Genome Trax (RRID:SCR_001234) Copy   

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http://www.bioconductor.org/packages/release/bioc/html/ITALICS.html

Software package to normalize of Affymetrix GeneChip Human Mapping 100K and 500K set.

Proper citation: ITALICS (RRID:SCR_001274) Copy   

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https://www.mristudio.org/

An image processing program running under Windows suitable for such tasks as tensor calculation, color mapping, fiber tracking, and 3D visualization. Most of operations can be done with only a few clicks. This tool evolved from DTI Studio. Tools in the program can be grouped in the following way: * Image Viewer * Diffusion Tensor Calculations * Fiber Tracking and Editing * 3D Visualization * Image File Management * Region of Interesting (ROI) Drawing and Statistics * Image Registration

Proper citation: MRI Studio (RRID:SCR_001398) Copy   

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http://bmsr.usc.edu/software/pneuma/

A set of modules that are used to simulate the autoregulation of the cardiovascular and respiratory systems under conditions of changing sleep-wake state and a variety of physiological and pharmacological interventions. It models the dynamic interactions that take place among the various component mechanisms, including those involved in the chemical control of breathing, heart rate, and blood pressure, as well as the effects of changes in the sleep-wake state and arousal from sleep. PNEUMA includes the autonomic control of the cardiovascular system, chemoreflex and state-related control of breath-to-breath ventilation, state-related and chemoreflex control of upper airway potency, as well as respiratory and circulatory mechanics. The model is capable of simulating the cardiorespiratory responses to sleep onset, arousal, continuous positive airway pressure, the administration of inhaled carbon dioxide and oxygen, Valsalva and Mueller maneuvers, and Cheyne-Stokes respiration during sleep. In PNEUMA 3.0, we have extended the existing integrative model of respiratory, cardiovascular, and sleepwake state control, to incorporate a sub-model of glucoseinsulinfatty acid regulation. The extended model is capable of simulating the metabolic control of glucoseinsulin dynamics and its interactions with the autonomic nervous system. The interactions between autonomic and metabolic control include the circadian regulation of epinephrine secretion, epinephrine regulation on dynamic fluctuations in glucose and free fatty acids in plasma, metabolic coupling among tissues and organs mediated by insulin and epinephrine, as well as the effect of insulin on peripheral vascular sympathetic activity. This extended model represents a starting point from which further in silico investigations into the interaction between the autonomic nervous system and the metabolic control system can proceed. Features in PNEUMA 3.0 * Incorporates metabolic component based on prior models of glucose-insulin regulation and free fatty acid (FFA) regulation. * Changes in sympathetic activity from the autonomic portion of PNEUMA produce changes in epinephrine output, which in turn affects the metabolic sub-model. * Inputs from the dietary intake of glucose and external interventions, such as insulin injections, have also been incorporated. * Also incorporated is autonomic feedback from the metabolic component to the rest of PNEUMA: changes in insulin level lead to changes in sympathetic tone. System Requirements: PNEUMA requires Matlab R2007b or higher with the accompanying version of Simulink to be installed on your computer.

Proper citation: PNEUMA (RRID:SCR_001391) Copy   

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https://cde.nlm.nih.gov/

A repository of Common Data Elements (CDE). The CDE is a standardized, precisely defined question, paired with a set of allowable responses, used systematically across different sites, studies, or clinical trials to ensure consistent data collection. Multiple CDEs (from one or more Collections) can be curated into Forms. Forms in the Repository might be original, or might recreate the format of real-world data collection instruments or case report forms. NIH has endorsed collections of CDEs that meet established criteria. NIH-endorsed CDEs are designated with a gold ribbon. Users can Browse NIH-Endorsed CDEs, Browse All CDEs, or Browse Forms.

Proper citation: NIH Common Data Element Repository (RRID:SCR_001390) Copy   

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https://www.bioconductor.org/packages//2.12/bioc/html/dexus.html

Software package that identifies differentially expressed genes in RNA-Seq data under all possible study designs such as studies without replicates, without sample groups, and with unknown conditions. It works also for known conditions, for example for RNA-Seq data with two or multiple conditions. RNA-Seq read count data can be provided both by the S4 class Count Data Set and by read count matrices. Differentially expressed transcripts can be visualized by heatmaps, in which unknown conditions, replicates, and samples groups are also indicated. This software is fast since the core algorithm is written in C. For very large data sets, a parallel version of DEXUS is provided in this package. DEXUS is a statistical model that is selected in a Bayesian framework by an EM algorithm. It does not need replicates to detect differentially expressed transcripts, since the replicates (or conditions) are estimated by the EM method for each transcript. The method provides an informative/non-informative value to extract differentially expressed transcripts at a desired significance level or power.

Proper citation: DEXUS (RRID:SCR_001309) Copy   

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http://www.opencolleges.edu.au/informed/learning-strategies/

Interactive infographic of a brain exploring more than 100,000 chemical reactions, highlighted by areas and explanations of what that area is known to do.

Proper citation: Open Colleges Interactive Brain (RRID:SCR_001427) Copy   

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https://codr.c-path.org/

A repository of de-identified control arm data of patients from clinical studies of Alzheimer's disease and Mild Cognitive Impairment. It provides the ability to analyze the data online with the R statistical analysis program, create and download standard reports, run complex queries, or download data to a desktop for further analysis. Additional data will be added to the database over time. Critical Path Institute consortia members and qualified researchers may upload and work on scientific data relevant to biomarkers of drug toxicity, neurodegenerative diseases, and patient-reported outcomes.

Proper citation: CODR: C PATH On Line Data Repository (RRID:SCR_001388) Copy   

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https://github.com/vital-ai/vital-documentation/wiki/Vital-AI-Ontology

Ontology for the four consensus human vital signs: blood pressure, body temperature, respiration rate, pulse rate. It provides a controlled structured vocabulary for describing vital signs measurement data, the various processes of measuring vital signs, and the various devices and anatomical entities participating in such measurements.

Proper citation: Vital Signs Ontology (RRID:SCR_001422) Copy   

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http://octresearch.org/

Biomedical technology research center that pioneers and provides access to microscopic imaging instruments for biologic and clinical research. Optical coherence tomography (OCT) has evolved over the last two decades to become a standard of care for diagnostic ophthalmic imaging and is poised to make significant impact in the fields of cardiology and gastrointestinal endoscopy. Access to state-of-the-art instrumentation, however, has been limited to a relatively few research laboratories and the optimization of instruments for new biomedical applications has hindered the investigation of new opportunities. A major focus of CBORT will be to cultivate strategic research collaborations and respond to a pressing need for application-specific OCT instrumentation and hardware.

Proper citation: Center for Biomedical OCT Research (RRID:SCR_001418) Copy   

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https://repository.niddk.nih.gov/study/21

Data and biological samples were collected by this consortium organizing international efforts to identify genes that determine an individual risk of type 1 diabetes. It originally focused on recruiting families with at least two siblings (brothers and/or sisters) who have type 1 diabetes (affected sibling pair or ASP families). The T1DGC completed enrollment for these families in August 2009. They completed enrollment of trios (father, mother, and a child with type 1 diabetes), as well as cases (people with type 1 diabetes) and controls (people with no history of type 1 diabetes) from populations with a low prevalence of this disease in January 2010. T1DGC Data and Samples: Phenotypic and genotypic data as well as biological samples (DNA, serum and plasma) for T1DGC participants have been deposited in the NIDDKCentral Repositories for future research.

Proper citation: Type 1 Diabetes Genetics Consortium (RRID:SCR_001557) Copy   

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http://mitraweb1.cshl.edu:8080/BrainArchitecture/pages/publications.faces

Preliminary database of neuroanatomical connectivity reports specifically for the human brain, which have been manually curated. It includes details (based on manual literature curation) of tract tracing or related connectivity studies conducted in human brain tissue. This database and user interface will be expanded and improved in the near future.

Proper citation: Human Brain Connectivity Database (RRID:SCR_001594) Copy   

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http://www.neurologychannel.com/

A topical portal which provides information about conditions that affect the nervous system (brain, spinal cord, nerves, and muscles), such as stroke (brain attack), Alzheimer's disease, and back pain. It is a physician developed and monitored source of neurology information for consumers. Additionally, it contains comprehensive condition and treatment information, as well as interactive tools.

Proper citation: Neurologychannel (RRID:SCR_001597) Copy   

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https://github.com/Ensembl

Public database that stores areas of genome that differ between individual genomes (variants) and, where available, associated disease and phenotype information. Different types of variants for several species: single nucleotide polymorphisms (SNPs), short nucleotide insertions and/or deletions, and longer variants classified as structural variants (including CNVs). Effects of variants on the Ensembl transcripts and regulatory features for each species are predicted. You can run same analysis on your own data using Variant Effect Predictor. These data are integrated with other data sources in Ensembl, and can be accessed using the API or website. For several different species in Ensembl, they import variation data (SNPs, CNVs, allele frequencies, genotypes, etc) from a variety of sources (e.g. dbSNP). Imported variants and alleles are subjected to quality control process to flag suspect data. In human, they calculate linkage disequilibrium for each variant, by population.

Proper citation: Ensembl Variation (RRID:SCR_001630) Copy   

•   Source: SciCrunch Registry