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https://github.com/ABCD-STUDY/Fast-Track-Image-Sharing

Software for sharing the ABCD (Adolescent Brain Cognitive Development) study data on the National Data Archive (NDA).

Proper citation: Fast-Track-Image-Sharing (RRID:SCR_016021) Copy   

•   Source: SciCrunch Registry

https://github.com/ABCD-STUDY/eprime-data-clean

Software to convert E-Prime (software tool for psychology computerized experiment design, data collection, and analysis) generated files to CSV files without errors during conversion. The ABCD project is using E-Prime to run behavioral tests.

Proper citation: eprime-data-clean (RRID:SCR_016020) Copy   

•   Source: SciCrunch Registry

https://github.com/ABCD-STUDY/geocoding

Software that uses a geo-location database to determine individuals' residential environment in Adolescent Brain Cognitive Development (ABCD) study. It performs queries given individuals' residential history in longitude and latitude.

Proper citation: geocoding (RRID:SCR_016007) Copy   

•   Source: SciCrunch Registry

https://github.com/ABCD-STUDY/redcap-importer

Software that automates the process of retrieving and converting data to the format of a RedCap table and allows selection of directories and files for import.

Proper citation: redcap-importer (RRID:SCR_016032) Copy   

•   Source: SciCrunch Registry

https://github.com/ABCD-STUDY/ABCDreport

Software application as a simple system to review study progress. Used in ABCD study.

Proper citation: ABCDreport (RRID:SCR_016030) 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

https://github.com/ABCD-STUDY/FIONA-protocol-compliance

Software that contains multiple sequential lines of MATLAB commands and function calls for numerical computing for ABCD study protocol compliance.

Proper citation: FIONA-protocol-compliance (RRID:SCR_016027) Copy   

•   Source: SciCrunch Registry

https://exrna-atlas.org

Software tool as data and metadata repository of Extracellular RNA Communication Consortium. Atlas includes small RNA sequencing and qPCR derived exRNA profiles from human and mouse biofluids. All RNAseq datasets are processed using version 4 of exceRpt small RNAseq pipeline. Atlas accepts submissions for RNAseq or qPCR data.

Proper citation: exRNA Atlas (RRID:SCR_017221) Copy   

•   Source: SciCrunch Registry

http://www.genenetwork.org/

Web platform that provides access to data and tools to study complex networks of genes, molecules, and higher order gene function and phenotypes. Sequence data (SNPs) and transcriptome data sets (expression genetic or eQTL data sets). Quantitative trait locus (QTL) mapping module that is built into GN is optimized for fast on-line analysis of traits that are controlled by combinations of gene variants and environmental factors. Used to study humans, mice (BXD, AXB, LXS, etc.), rats (HXB), Drosophila, and plant species (barley and Arabidopsis). Users are welcome to enter their own private data.

Proper citation: GeneNetwork (RRID:SCR_002388) 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://learn.genetics.utah.edu/content/addiction/

A physiologic and molecular look at drug addiction involving many factors including: basic neurobiology, a scientific examination of drug action in the brain, the role of genetics in addiction, and ethical considerations. Designed to be used by students, teachers and members of the public, the materials meet selected US education standards for science and health. Drug addiction is a chronic disease characterized by changes in the brain which result in a compulsive desire to use a drug. A combination of many factors including genetics, environment and behavior influence a person's addiction risk, making it an incredibly complicated disease. The new science of addiction considers all of these factors - from biology to family - to unravel the complexities of the addicted brain. * Natural Reward Pathways Exist in the Brain: The reward pathway is responsible for driving our feelings of motivation, reward and behavior. * Drugs Alter the Brain's Reward Pathway: Drugs work over time to change the reward pathway and affect the entire brain, resulting in addiction. * Genetics Is An Important Factor In Addiction: Genetic susceptibility to addiction is the result of the interaction of many genes. * Timing and Circumstances Influence Addiction: If you use drugs when you are an adolescent, you are more likely to develop lifetime addiction. An individual's social environment also influences addiction risk. * Challenges and Issues in Addiction: Addiction impacts society with many ethical, legal and social issues.

Proper citation: New Science of Addiction: Genetics and the Brain (RRID:SCR_002770) Copy   

•   Source: SciCrunch Registry

http://www.macaque.org/

THIS RESOURCE IS NO LONGER IN SERVICE, documented May 10, 2017. A pilot effort that has developed a centralized, web-based biospecimen locator that presents biospecimens collected and stored at participating Arizona hospitals and biospecimen banks, which are available for acquisition and use by researchers. Researchers may use this site to browse, search and request biospecimens to use in qualified studies. The development of the ABL was guided by the Arizona Biospecimen Consortium (ABC), a consortium of hospitals and medical centers in the Phoenix area, and is now being piloted by this Consortium under the direction of ABRC. You may browse by type (cells, fluid, molecular, tissue) or disease. Common data elements decided by the ABC Standards Committee, based on data elements on the National Cancer Institute''s (NCI''s) Common Biorepository Model (CBM), are displayed. These describe the minimum set of data elements that the NCI determined were most important for a researcher to see about a biospecimen. The ABL currently does not display information on whether or not clinical data is available to accompany the biospecimens. However, a requester has the ability to solicit clinical data in the request. Once a request is approved, the biospecimen provider will contact the requester to discuss the request (and the requester''s questions) before finalizing the invoice and shipment. The ABL is available to the public to browse. In order to request biospecimens from the ABL, the researcher will be required to submit the requested required information. Upon submission of the information, shipment of the requested biospecimen(s) will be dependent on the scientific and institutional review approval. Account required. Registration is open to everyone.. Documented on June 8, 2020.Macaque genomic and proteomic resources and how they are providing important new dimensions to research using macaque models of infectious disease. The research encompasses a number of viruses that pose global threats to human health, including influenza, HIV, and SARS-associated coronavirus. By combining macaque infection models with gene expression and protein abundance profiling, they are uncovering exciting new insights into the multitude of molecular and cellular events that occur in response to virus infection. A better understanding of these events may provide the basis for innovative antiviral therapies and improvements to vaccine development strategies.

Proper citation: Macaque.org (RRID:SCR_002767) 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

http://www.drugabuse.gov/news-events/podcasts

Audio clips that highlight research efforts at the National Institute on Drug Abuse and include interviews with prominent NIDA scientists. To listen to these clips, just click Listen Now under the clip summary. You must have Real Media Player or Windows Media Player installed to download these clips. To view a printable transcript of a clip, click View Transcript under the clip summary.

Proper citation: NIDA Podcasts (RRID:SCR_005660) 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://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://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

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