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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/FINDTHECAT

Software that conducts a jspsych test for response time evaluation. Used in the ABCD Study.

Proper citation: FINDTHECAT (RRID:SCR_016036) Copy   

•   Source: SciCrunch Registry

https://github.com/ABCD-STUDY/stroop-task

Software that conducts the Stroop Color Task. Used in the ABCD Study.

Proper citation: stroop-task (RRID:SCR_016033) Copy   

•   Source: SciCrunch Registry

https://github.com/QTIM-Lab/DeepNeuro

Software Python package for neuroimaging data. Framework to design and train neural network architectures. Used in medical imaging community to ensure consistent performance of networks across variable users, institutions, and scanners.

Proper citation: DeepNeuro (RRID:SCR_016911) Copy   

•   Source: SciCrunch Registry

https://github.com/compbiolabucf/omicsGAN

Software generative adversarial network to integrate two omics data and their interaction network to generate one synthetic data corresponding to each omics profile that can result in better phenotype prediction. Used to capture information from interaction network as well as two omics datasets and fuse them to generate synthetic data with better predictive signals.

Proper citation: OmicsGAN (RRID:SCR_022976) Copy   

•   Source: SciCrunch Registry

https://painseq.shinyapps.io/harmonized_painseq_v1/

Harmonized cell atlases using sc/snRNA-seq data obtained from dorsal root ganglia and trigeminal ganglio mammalian datasets.

Proper citation: Harmonized DRG and TG Reference Atlas (RRID:SCR_025720) Copy   

•   Source: SciCrunch Registry

https://gseapy.readthedocs.io/en/latest/

Software Python package for performing gene set enrichment analysis. Used for characterizing gene expression changes by analysis of large single-cell datasets.

Proper citation: GSEApy (RRID:SCR_025803) Copy   

•   Source: SciCrunch Registry

https://github.com/smorabit/hdWGCNA

Software R package for performing weighted gene co-expression network analysis in high dimensional transcriptomics data such as single-cell RNA-seq or spatial transcriptomics.

Proper citation: hdWGCNA (RRID:SCR_027496) Copy   

•   Source: SciCrunch Registry

http://bellsouthpwp.net/c/a/capowski//NTSPublic.html

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 23, 2016. A hardware and software package with which a scientist could trace the structure of neurons and other neuroscientific features directly from tissue sections or from a stack of their images into a computer. Then it also could edit, merge, filter, display in 3D, and make realistic plots of the structures. The NTS also includes a substantial statistical package that provided many, now standardized, mathematical and statistical summaries that described each neuron and compared one population to another. Additionally, NTS also provided an embryonic electrotonic modeler that simulates and displayes the electrical functioning of a cell. The NTS uses a special purpose graphics display processor called the VDP3 whose output is presented on a very high resolution CRT. During tracing, the VDP3 presents a variable-diameter cursor and other information directly in the microscope and enables tracing at a high spatial resolution and with measurement of process diameters limited only by the microscope''s optics. Control of tracing is done with a 3D joystick that allows easy control of five input variables: X,Y,Z position, cursor diameter, and a numeric tag. Finally, superb 3D interactive displays of completed cells are provided on the VDP3.

Proper citation: Eutectic NTS (RRID:SCR_008062) Copy   

•   Source: SciCrunch Registry

http://knowledge-space.org/

A community encyclopaedia that links brain research concepts with data, models and literature from around the world. It is an open project where users can participate and contribute to the global research community.

Proper citation: KnowledgeSpace (RRID:SCR_014539) Copy   

•   Source: SciCrunch Registry

http://www.pediatricmri.nih.gov/

Data sets of clinical / behavioral and image data are available for download by qualified researchers from a seven year, multi-site, longitudinal study using magnetic resonance technologies to study brain maturation in healthy, typically-developing infants, children, and adolescents and to correlate brain development with cognitive and behavioral development. The information obtained in this study is expected to provide essential data for understanding the course of normal brain development as a basis for understanding atypical brain development associated with a variety of developmental, neurological, and neuropsychiatric disorders affecting children and adults. This study enrolled over 500 children, ranging from infancy to young adulthood. The goal was to study each participant at least three times over the course of the project at one of six Pediatric Centers across the United States. Brain MR and clinical/behavioral data have been compiled and analyzed at a Data Coordinating Center and Clinical Coordinating Center. Additionally, MR spectroscopy and DTI data are being analyzed. The study was organized around two objectives corresponding to two age ranges at the time of enrollment, each with its own protocols. * Objective 1 enrolled children ages 4 years, 6 months through 18 years (total N = 433). This sample was recruited across the six Pediatric Study Centers using community based sampling to reflect the demographics of the United States in terms of income, race, and ethnicity. The subjects were studied with both imaging and clinical/behavioral measures at two year intervals for three time points. * Objective 2 enrolled newborns, infants, toddlers, and preschoolers from birth through 4 years, 5 months, who were studied three or more times at two Pediatric Study Centers at intervals ranging from three months for the youngest subjects to one year as the children approach the Objective 1 age range. Both imaging and clinical/behavioral measures were collected at each time point. Participant recruitment used community based sampling that included hospital venues (e.g., maternity wards and nurseries, satellite physician offices, and well-child clinics), community organizations (e.g., day-care centers, schools, and churches), and siblings of children participating in other research at the Pediatric Study Centers. At timepoint 1, of those enrolled, 114 children had T1 scans that passed quality control checks. Staged data release plan: The first data release included structural MR images and clinical/behavioral data from the first assessments, Visit 1, for Objective 1. A second data release included structural MRI and clinical/behavioral data from the second visit for Objective 1. A third data release included structural MRI data for both Objective 1 and 2 and all time points, as well as preliminary spectroscopy data. A fourth data release added cortical thickness, gyrification and cortical surface data. Yet to be released are longitudinally registered anatomic MRI data and diffusion tensor data. A collaborative effort among the participating centers and NIH resulted in age-appropriate MR protocols and clinical/behavioral batteries of instruments. A summary of this protocol is available as a Protocol release document. Details of the project, such as study design, rationale, recruitment, instrument battery, MRI acquisition details, and quality controls can be found in the study protocol. Also available are the MRI procedure manual and Clinical/Behavioral procedure manuals for Objective 1 and Objective 2.

Proper citation: NIH MRI Study of Normal Brain Development (RRID:SCR_003394) Copy   

•   Source: SciCrunch Registry

http://www.cpc.unc.edu/projects/addhealth

Longitudinal study of a nationally representative sample of adolescents in grades 7-12 in the United States during the 1994-95 school year. Public data on about 21,000 people first surveyed in 1994 are available on the first phases of the study, as well as study design specifications. It also includes some parent and biomarker data. The Add Health cohort has been followed into young adulthood with four in-home interviews, the most recent in 2008, when the sample was aged 24-32. Add Health combines longitudinal survey data on respondents social, economic, psychological and physical well-being with contextual data on the family, neighborhood, community, school, friendships, peer groups, and romantic relationships, providing unique opportunities to study how social environments and behaviors in adolescence are linked to health and achievement outcomes in young adulthood. The fourth wave of interviews expanded the collection of biological data in Add Health to understand the social, behavioral, and biological linkages in health trajectories as the Add Health cohort ages through adulthood. The restricted-use contract includes four hours of free consultation with appropriate staff; after that, there''s a fee for help. Researchers can also share information through a listserv devoted to the database.

Proper citation: Add Health (National Longitudinal Study of Adolescent Health) (RRID:SCR_007434) Copy   

•   Source: SciCrunch Registry

https://scicrunch.org/scicrunch/about/sources/nlx_144509-1

Interactive portal for finding and submitting biomedical resources. Resources within SciCrunch have assigned RRIDs which are used to cite resources in scientific manuscripts. SciCrunch Registry, formerly NIF Registry, provides resources catalog. Allows to add new resources. Allows edit existing resources after registration. Curators are tasked with identifying and registering resources, examining data, writing configuration files to index and display data and keeping contents current.

Proper citation: SciCrunch Registry (RRID:SCR_005400) Copy   

•   Source: SciCrunch Registry

http://biositemaps.ncbcs.org/rds/search.html

Resource Discovery System is a web-accessible and searchable inventory of biomedical research resources. Powered by the Resource Discovery System (RDS) that includes a standards-based informatics infrastructure * Biositemaps Information Model * Biomedical Resource Ontology Extensions * Web Services distributed web-accessible inventory framework * Biositemap Resource Editor * Resource Discovery System Source code and project documentation to be made available on an open-source basis. Contributing institutions: University of Pittsburgh, University of Michigan, Stanford University, Oregon Health & Science University, University of Texas Houston. Duke University, Emory University, University of California Davis, University of California San Diego, National Institutes of Health, Inventory Resources Working Group Members

Proper citation: Resource Discovery System (RRID:SCR_005554) Copy   

•   Source: SciCrunch Registry

https://scicrunch.org/scicrunch/data/source/nlx_154697-7/search?q=*

Virtual database currently indexing interaction between genes and diseases from Online Mendelian Inheritance in Man (OMIM) and Comparative Toxicogenomics Database (CTD).

Proper citation: Integrated Gene-Disease Interaction (RRID:SCR_006173) Copy   

•   Source: SciCrunch Registry

http://www.exocarta.org/

Manually curated database of exosomal proteins, RNA and lipids. Web based compendium of exosomal cargo. Database catalogs information from both published and unpublished exosomal studies. Mode of exosomal purification and characterization, biophysical and molecular properties are listed.

Proper citation: ExoCarta (RRID:SCR_021960) Copy   

•   Source: SciCrunch Registry

http://www.nihpromis.org/

Repository of person centered measures that evaluates and monitors physical, mental, and social health in adults and children.

Proper citation: Patient-Reported Outcomes Measurement Information System (RRID:SCR_004718) Copy   

•   Source: SciCrunch Registry

https://confluence.crbs.ucsd.edu/display/NIF/DRG

Gene expression data from published journal articles that test hypotheses relevant to neuroscience of addiction and addictive behavior. Data types include effects of particular drug, strain, or knock out on particular gene, in particular anatomical region. Focuses on gene expression data and exposes data from investigations using DNA microarrays, polymerase chain reaction, immunohistochemistry and in-situ hybridizations. Data are available for query through NIF interface.Data submissions are welcome.

Proper citation: Drug Related Gene Database (RRID:SCR_003330) Copy   

•   Source: SciCrunch Registry

https://ratgenes.org/

Portal includes information about genetic studies of drug abuse in outbred rats. Data center created in 2014 to perform genome wide association studies on numerous behavioral traits that have well established relevance to drug abuse using outbred rats.

Proper citation: NIDA center for genetic studies of drug abuse in outbred rats (RRID:SCR_021788) Copy   

•   Source: SciCrunch Registry

http://www.clairlib.org

A suite of open-source Perl modules intended to simplify a number of generic tasks in natural language processing (NLP), information retrieval (IR), and network analysis (NA). Its architecture also allows for external software to be plugged in with very little effort. The latest version of clairlib is 1.06 which was released on March 2009 and includes about 130 modules implementing a wide range of functionalities. Clairlib is distributed in two forms: * Clairlib-core, which has essential functionality and minimal dependence on external software, and * Clairlib-ext, which has extended functionality that may be of interest to a smaller audience. Much can be done using Clairlib on its own. Some of the things that Clairlib can do are: Tokenization, Summarization, Document Clustering, Document Indexing, Web Graph Analysis, Network Generation, Power Law Distribution Analysis, Network Analysis, RandomWalks on Graphs, Tf-IDF, Perceptron Learning and Classification, and Phrase Based Retrieval and Fuzzy OR Queries.

Proper citation: Clair library (RRID:SCR_007019) Copy   

•   Source: SciCrunch Registry