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http://www.cjdats.org

A cooperative research program to explore the issues related to the complex system of offender treatment services. Nine research centers and a Coordinating Center were created in partnership with researchers, criminal justice professionals, and drug abuse treatment practitioners to form a national research infrastructure. The establishment of CJ-DATS is an outstanding example of cooperation among Federal agencies with the research community... We need to understand how to provide better drug treatment services for criminal justice offenders to alter their drug use and criminal behavior. - Dr. Nora Volkow, Director of NIDA. CJ-DATS PHASE I In 2002, NIDA launched the National Criminal Justice����������Drug Abuse Treatment Studies (CJ-DATS). CJ-DATS is a multisite research program aimed at improving the treatment of offenders with drug use disorders and integrating criminal justice and public health responses to drug involved offenders. From 2002 through 2008, CJ-DATS researchers from 9 research centers, a coordinating center, and NIDA worked together with federal, state, and local criminal justice partners to develop and test integrated approaches to the treatment of offenders with drug use disorders. The areas that were studied included: * Assessing Offender Problems * Measuring Progress in Treatment and Recovery * Linking Criminal Justice and Drug Abuse Treatment * Adolescent Interventions * HIV and Hepatitis Risk Reduction * Understanding Systems CJ-DATS PHASE II In 2008, CJ-DATS began to focus on the problems of implementing research-based practices drug treatment practices. This research concerns the organizational and systems processes involved in implementing valid, evidence-based practices to reduce drug use and drug-related recidivism for individuals in the criminal justice system. 12 CJ-DATS Research Centers are conducting implementation research in three primary domains: * Research to improve the implementation of evidence-based assessment processes for offenders with drug problems * Implementing effective treatment for drug-involved offenders * Implementing evidence-based interventions to improve an HIV continuum-of-care for offenders

Proper citation: Criminal Justice Drug Abuse Treatment Studies (RRID:SCR_006996) Copy   

•   Source: SciCrunch Registry

https://github.com/KumarLabJax/JABS-behavior-classifier

Video based phenotyping platform for laboratory mouse. Provides complete details of software and hardware, including 3D designs used for data collection. Data acquisition system consists of video collection hardware and software, behavior labeling and active learning app, and online database for sharing classifiers. Hardware and software solution collects high quality data for behavior analysis.

Proper citation: JAX Animal Behavior System (RRID:SCR_023721) Copy   

•   Source: SciCrunch Registry

https://github.com/SciCrunch/Antibody-Watch

Text mining antibody specificity from literature. Helps researchers identify potential problems with antibody specificity. By mining the scientific literature and linking findings to Research Resource Identifiers (RRIDs), it provides alerts on antibodies that may yield unreliable results, supporting reproducibility in biomedical research.

Proper citation: Antibody Watch (RRID:SCR_027424) Copy   

•   Source: SciCrunch Registry

https://neuinfo.org/mynif/search.php?q=nlx_149462&t=indexable&list=cover&nif=nlx_144509-1

A virtual database that indexes both BioNOT for negation data, and the Resource Discovery Pipeline: an automated resource discovery and semi-automated type characterization with text-mining scripts that facilitate curation team efforts to discover, integrate and display new content. This virtual database currently indexes the following resources: * BioNOT, http://snake.ims.uwm.edu/bionot/index.php?searchterm=mecp2+autism&submit=Search * Resource Discovery Pipeline, http://lucene1.neuinfo.org/nif_resource/current/

Proper citation: Integrated Auto-Extracted Annotation (RRID:SCR_005892) Copy   

•   Source: SciCrunch Registry

http://mialab.mrn.org/data/index.html

An MRI data set that demonstrates the utility of a mega-analytic approach by identifying the effects of age and gender on the resting-state networks (RSNs) of 603 healthy adolescents and adults (mean age: 23.4 years, range: 12-71 years). Data were collected on the same scanner, preprocessed using an automated analysis pipeline based in SPM, and studied using group independent component analysis. RSNs were identified and evaluated in terms of three primary outcome measures: time course spectral power, spatial map intensity, and functional network connectivity. Results revealed robust effects of age on all three outcome measures, largely indicating decreases in network coherence and connectivity with increasing age. Gender effects were of smaller magnitude but suggested stronger intra-network connectivity in females and more inter-network connectivity in males, particularly with regard to sensorimotor networks. These findings, along with the analysis approach and statistical framework described, provide a useful baseline for future investigations of brain networks in health and disease.

Proper citation: MIALAB - Resting State Data (RRID:SCR_008914) Copy   

•   Source: SciCrunch Registry

http://pingstudy.ucsd.edu/

A large multi-site pediatric MRI and genetics data resource to facilitate studies of the genomic landscape of the developing human brain. It includes information about the developing mental and emotional functions of the children to understand the genetic basis of individual differences in brain structure and connectivity, cognition, and personality. Investigators on the project are studying 1400 children between the ages of 3 and 20 years so that links between genetic variation and developing patterns of brain connectivity can be examined. Investigators interested in the effects of a particular gene will be able to search the database for any brain areas or connections between areas that differ as a function of variation in a particular gene, and also to determine if the genes appear to affect the course of brain development at some point during childhood. A data exploration tool has been created for mapping and analyzing MRI data sets collected for PING and related developmental studies. Approved investigators will be able to view raw image sets and derived 3D brain maps of MRI and DTI data, conduct hypothesis testing, and graph brain area measures as they change across the time course of development. PING Cores * Coordinating Core: Functions include project management, screening of participants and maintaining the database * Neuroimaging Core: applying a standardized high-resolution structural MRI protocol involving 3-D T1-weighted scans, a T2-weighted volume, and a set of diffusion-weighted scans with multiple b values and diffusion directions, scans to estimate MRI relaxation rates, and gradient echo EPI scans for resting state fMRI. Importantly, adaptive motion compensation, using ����??PROMO����??, a novel real-time motion correction algorithm will be used. Specific PING protocols for each scanner manufacturer: ** PING MRI Protocol - GE ** PING MRI Protocol - Philips ** PING MRI Protocol - Siemens * Assessment Core: Cognitive assessments for the PING project are conducted using the NIH Toolbox for Cognition. * Genomics Core: functions as a central repository for receipt of saliva samples collected for each study participant. Once received, samples are catalogued, maintained, and DNA is extracted using state-of-the-field laboratory techniques. Ultimately, genome-wide genotyping is performed on the extracted DNA using the Illumina Human660W-Quad BeadChip. PING involves 10 sites throughout the country including UCSD, University of Hawaii, Scripps Genomics, UCLA, UC Davis, Kennedy Krieger Institute/Johns Hopkins, Sacker Institute/Cornell University, University of Massachusetts, Massachusetts General Hospital/Harvard, and Yale. Families who may want to participate in the study, or others who want to know more about it, may email questions to ping (at) ucsd.edu.

Proper citation: Pediatric Imaging Neurocognition and Genetics (RRID:SCR_008953) Copy   

•   Source: SciCrunch Registry

https://www.ohsu.edu/custom/library/digital-collections/projectionmap

Data set of thalamo-centric mesoscopic projection maps to the cortex and striatum. The maps are established through two-color, viral (rAAV)-based tracing images and high throughout imaging.

Proper citation: Mouse Thalamic Projectome Dataset (RRID:SCR_015702) Copy   

•   Source: SciCrunch Registry

https://abcdstudy.org

Long-term study of brain development and child health in the United States. The study tracks subjects' biological and behavioral development through adolescence into young adulthood to determine how childhood experiences (such as sports, videogames, social media, unhealthy sleep patterns, and smoking) interact with each other and with a child’s changing biology to affect brain development and social, behavioral, academic, health, and other outcomes.

Proper citation: ABCD Study (RRID:SCR_015769) Copy   

•   Source: SciCrunch Registry

http://compbio.uthsc.edu/miRSNP/

Database of naturally occurring DNA variations in microRNA (miRNA) seed regions and miRNA target sites. MicroRNAs pair to the transcripts of protein-coding genes and cause translational repression or mRNA destabilization. SNPs and INDELs in miRNAs and their target sites may affect miRNA-mRNA interaction, and hence affect miRNA-mediated gene repression. The PolymiRTS database was created by scanning 3'UTRs of mRNAs in human and mouse for SNPs and INDELs in miRNA target sites. Then, the potential downstream effects of these polymorphisms on gene expression and higher-order phenotypes are identified. Specifically, genes containing PolymiRTSs, cis-acting expression QTLs, and physiological QTLs in mouse and the results of genome-wide association studies (GWAS) of human traits and diseases are linked in the database. The PolymiRTS database also includes polymorphisms in target sites that have been supported by a variety of experimental methods and polymorphisms in miRNA seed regions.

Proper citation: PolymiRTS (RRID:SCR_003389) Copy   

•   Source: SciCrunch Registry

http://proteomics.ucsd.edu/Software/NeuroPedia/index.html

A neuropeptide encyclopedia of peptide sequences (including genomic and taxonomic information) and spectral libraries of identified MS/MS spectra of homolog neuropeptides from multiple species.

Proper citation: NeuroPedia (RRID:SCR_001551) Copy   

•   Source: SciCrunch Registry

http://lucene1.neuinfo.org/nif_resource/monthly_results/current/

An automatic pipeline based on an algorithm that identifies new resources in publications every month to assist the efficiency of NIF curators. The pipeline is also able to find the last time the resource's webpage was updated and whether the URL is still valid. This can assist the curator in knowing which resources need attention. Additionally, the pipeline identifies publications that reference existing NIF Registry resources as this is also of interest. These mentions are available through the Data Federation version of the NIF Registry, http://neuinfo.org/nif/nifgwt.html?query=nlx_144509 The RDF is based on an algorithm on how related it is to neuroscience. (hits of neuroscience related terms). Each potential resource gets assigned a score (based on how related it is to neuroscience) and the resources are then ranked and a list is generated.

Proper citation: NIF Registry Automated Crawl Data (RRID:SCR_012862) Copy   

•   Source: SciCrunch Registry

https://doi.org/10.17605/OSF.IO/WDR78

Open source resource of manually curated and expert reviewed infant brain segmentations hosted on OpenNeuro.org. and OSF.io. Anatomical MRI data was segmented from 71 infant imaging visits across 51 participants, using both T1w and T2w images per visit. Images showed dramatic differences in myelination and intensities across 1–9 months, emphasizing the need for densely sampled gold-standard segmentations across early life. This dataset provides a benchmark for evaluating and improving pipelines dependent upon segmentations in the youngest populations. As such, this dataset provides a vitally needed foundation for early-life large-scale studies such as HBCD.

Proper citation: Baby Open Brains (RRID:SCR_027836) Copy   

•   Source: SciCrunch Registry

http://brainarchitecture.org/

Evolving portal that will provide interactive tools and resources to allow researchers, clinicians, and students to discover, analyze, and visualize what is known about the brain's organization, and what the evidence is for that knowledge. This project has a current experimental focus: creating the first brainwide mesoscopic connectivity diagram in the mouse. Related efforts for the human brain currently focus on literature mining and an Online Brain Atlas Reconciliation Tool. The primary goal of the Brain Architecture Project is to assemble available knowledge about the structure of the nervous system, with an ultimate emphasis on the human CNS. Such information is currently scattered in research articles, textbooks, electronic databases and datasets, and even as samples on laboratory shelves. Pooling the knowledge across these heterogeneous materials - even simply getting to know what we know - is a complex challenge that requires an interdisciplinary approach and the contributions and support of the greater community. Their approach can be divided into 4 major thrusts: * Literature Curation and Text Mining * Computational Analysis * Resource Development * Experimental Efforts

Proper citation: Brain Architecture Project (RRID:SCR_004283) Copy   

•   Source: SciCrunch Registry

http://okcam.cbi.pku.edu.cn/ontology.php

CAMO (Cell Adhesion Molecule Ontology) is a set of standard vocabulary that provide a hierarchical description of cell adhesion molecules and their functions. We compiled a list for cell adhesion molecules by integrating Gene Ontology annotations, domain structure information, and keywords query against NCBI Entrez Gene annotations. Totally 496 unique human genes were identified to function as cell adhesion molecules, which is by far the most comprehensive dataset including cadherin, immunoglobulin/FNIII, integrin, neurexin, neuroligan, and catenin families. CAMO was constructed as a directed acyclic graph (DAG) using DAG-Edit to input, manage and update data. We annotated each term with name, definition and source references, as well as the relationship to other terms, based on manual reviews of domain architecture and functional annotations. If vertices represent terms and the relationships between terms are represented by edges, the terms in a DAG can be connected via a directed graph without cycles. CAMO thus provides a hierarchical description of functions of CAMs with five top-level categories: CAM gene families, CAM genetics, CAM regulation, CAM expression and CAM diseases. Each top-level term is further divided into several categories to describe the functions in detail.

Proper citation: CAMO - Cell Adhesion Molecule Ontology (RRID:SCR_004392) Copy   

•   Source: SciCrunch Registry

https://neuinfo.org/mynif/search.php?list=cover&q=*

Service that partners with the community to expose and simultaneously drill down into individual databases and data sets and return relevant content. This type of content, part of the so called hidden Web, is typically not indexed by existing web search engines. Every record links back to the originating site. In order for NIF to directly query these independently maintained databases and datasets, database providers must register their database or dataset with the NIF Data Federation and specify permissions. Databases are concept mapped for ease of sharing and to allow better understanding of the results. Learn more about registering your resource, http://neuinfo.org/nif_components/disco/interoperation.shtm Search results are displayed under the Data Federation tab and are categorized by data type and nervous system level. In this way, users can easily step through the content of multiple resources, all from the same interface. Each federated resource individually displays their query results with links back to the relevant datasets within the host resource. This allows users to take advantage of additional views on the data and tools that are available through the host database. The NIF site provides tutorials for each resource, indicated by the Professor Icon professor icon showing users how to navigate the results page once directed there through the NIF. Additionally, query results may be exported as an Excel document. Note: NIF is not responsible for the availability or content of these external sites, nor does NIF endorse, warrant or guarantee the products, services or information described or offered at these external sites. Integrated Databases: Theses virtual databases created by NIF and other partners combine related data indexed from multiple databases and combine them into one view for easier browsing. * Integrated Animal View * Integrated Brain Gene Expression View * Integrated Disease View * Integrated Nervous System Connectivity View * Integrated Podcasts View * Integrated Software View * Integrated Video View * Integrated Jobs * Integrated Blogs For a listing of the Federated Databases see, http://neuinfo.org/mynif/databaseList.php or refer to the Resources Listed by NIF Data Federation table below.

Proper citation: NIF Data Federation (RRID:SCR_004834) Copy   

•   Source: SciCrunch Registry

http://www.zfishbook.org/NGP/journalcontent/SCORE/SCORE.html

Narrative resource describing a visual data analysis and collection approach that takes advantage of the cylindrical nature of the zebrafish allowing for an efficient and effective method for image capture called, Specimen in a Corrected Optical Rotational Enclosure (SCORE) Imaging. To achieve a non-distorted image, zebrafish were placed in a fluorinated ethylene propylene (FEP) tube with a surrounding, optically corrected imaging solution: water. By similarly matching the refractive index of the housing (FEP tubing) to that of the inner liquid and outer liquid (water), distortion was markedly reduced, producing a crisp imagable specimen that is able to be fully rotated 360 degrees. A similar procedure was established for fixed zebrafish embryos using convenient, readily available borosilicate capillaries surrounded by 75% glycerol. The method described could be applied to chemical genetic screening and other, related high-throughput methods within the fish community and among other scientific fields.

Proper citation: Zebrafish - SCORE Imaging: Specimen in a Corrected Optical Rotational Enclosure (RRID:SCR_001300) Copy   

•   Source: SciCrunch Registry

https://medicine.yale.edu/keck/nida/yped/

Open source system for storage, retrieval, and integrated analysis of large amounts of data from high throughput proteomic technologies. YPED currently handles LCMS, MudPIT, ICAT, iTRAQ, SILAC, 2D Gel and DIGE. The repository contains data sets which have been released for public viewing and downloading by the responsible Primary Investigators. It includes proteomic data generated by the Yale NIDA Neuroproteomics Center (http://medicine.yale.edu/keck/nida/index.aspx). Sample descriptions are compatible with the evolving MIAPE standards.

Proper citation: YPED (RRID:SCR_001436) Copy   

•   Source: SciCrunch Registry

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

Software package for brain image manipulation and analysis, focusing on fMRI and lesion analysis. VoxBo can be used independently or in conjunction with other packages. It provides GLM-based statistical tools, an architecture for interoperability with other tools (they encourage users to incorporate SPM and FSL into their processing pipelines), an automation system, a system for parallel distributed computing, numerous stand-alone tools, decent wiki-based documentation, and lots more.

Proper citation: VoxBo (RRID:SCR_002166) Copy   

•   Source: SciCrunch Registry

http://www.icpsr.umich.edu/icpsrweb/NAHDAP/

Archive that acquires, preserves and disseminates data relevant to drug addiction and HIV research. Collection of data on drug addiction and HIV infection in United States. Most of datasets are raw data from surveys, interviews, and administrative records. They were originally gathered in research projects and for administrative purposes. Some datasets have been used in published studies. Bibliographies of these studies are available . Provides access to research data and technical assistance for data depositors. Provides e-workshops on data preparation and data systems.

Proper citation: National Addiction and HIV Data Archive Program (NAHDAP) (RRID:SCR_000636) Copy   

•   Source: SciCrunch Registry

http://www.dd-database.org/

Database of bibliographic details of over 9,000 references published between 1951 and the present day, and includes abstracts, journal articles, book chapters and books replacing the two former separate websites for Ian Stolerman's drug discrimination database and Dick Meisch's drug self-administration database. Lists of standardized keywords are used to index the citations. Most of the keywords are generic drug names but they also include methodological terms, species studied and drug classes. This index makes it possible to selectively retrieve references according to the drugs used as the training stimuli, drugs used as test stimuli, drugs used as pretreatments, species, etc. by entering your own terms or by using our comprehensive lists of search terms. Drug Discrimination Drug Discrimination is widely recognized as one of the major methods for studying the behavioral and neuropharmacological effects of drugs and plays an important role in drug discovery and investigations of drug abuse. In Drug Discrimination studies, effects of drugs serve as discriminative stimuli that indicate how reinforcers (e.g. food pellets) can be obtained. For example, animals can be trained to press one of two levers to obtain food after receiving injections of a drug, and to press the other lever to obtain food after injections of the vehicle. After the discrimination has been learned, the animal starts pressing the appropriate lever according to whether it has received the training drug or vehicle; accuracy is very good in most experiments (90 or more correct). Discriminative stimulus effects of drugs are readily distinguished from the effects of food alone by collecting data in brief test sessions where responses are not differentially reinforced. Thus, trained subjects can be used to determine whether test substances are identified as like or unlike the drug used for training. Drug Self-administration Drug Self-administration methodology is central to the experimental analysis of drug abuse and dependence (addiction). It constitutes a key technique in numerous investigations of drug intake and its neurobiological basis and has even been described by some as the gold standard among methods in the area. Self-administration occurs when, after a behavioral act or chain of acts, a feedback loop results in the introduction of a drug or drugs into a human or infra-human subject. The drug is usually conceptualized as serving the role of a positive reinforcer within a framework of operant conditioning. For example, animals can be given the opportunity to press a lever to obtain an infusion of a drug through a chronically-indwelling venous catheter. If the available dose of the drug serves as a positive reinforcer then the rate of lever-pressing will increase and a sustained pattern of responding at a high rate may develop. Reinforcing effects of drugs are distinguishable from other actions such as increases in general activity by means of one or more control procedures. Trained subjects can be used to investigate the behavioral and neuropharmacological basis of drug-taking and drug-seeking behaviors and the reinstatement of these behaviors in subjects with a previous history of drug intake (relapse models). Other applications include evaluating novel compounds for liability to produce abuse and dependence and for their value in the treatment of drug dependence and addiction. The bibliography is updated about four times per year.

Proper citation: Comprehensive Drug Self-administration and Discrimination Bibliographic Databases (RRID:SCR_000707) Copy   

•   Source: SciCrunch Registry