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https://github.com/ABCD-STUDY/numerical-fitting

Software for a numerical computation library that performs numerical calculations. Used in ABCD study.

Proper citation: numerical-fitting (RRID:SCR_016025) Copy   

•   Source: SciCrunch Registry

https://github.com/djamesbarker/pMAT

Open source software suite for analysis of fiber photometry data.

Proper citation: pMAT (RRID:SCR_022570) Copy   

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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

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   

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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   

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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://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   

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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   

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http://fcon_1000.projects.nitrc.org/indi/CoRR/html/

Consortium that has aggregated resting state fMRI (R-fMRI) and diffusion imaging data from laboratories around the world, creating an open science resource for the imaging community, that facilitates the assessment of test-retest reliability and reproducibility for functional and structural connectomics. Given that this was a retrospective data collection, they have focused on basic phenotypic measures that are relatively standard in the neuroimaging field, as well as fundamental for analyses and sample characterization. Their phenotypic key is organized to reflect three classifications of variables: 1) core (i.e., minimal variables required to characterize any dataset), 2) preferred (i.e., variables that were strongly suggested for inclusion due to their relative import and/or likelihood of being collected by most sites), and 3) optional (variables that are data-set specific or only shared by a few sites). CoRR includes 33 datasets consisting of: * 1629 Subjects * 3357 Anatomical Scans * 5093 Resting Functional Scans * 1302 Diffusion Scans * 300 CBF and ASL Scans

Proper citation: Consortium for Reliability and Reproducibility (RRID:SCR_003774) Copy   

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http://www.ctalearning.com/

A searchable, keyword-indexed bibliography on conditioned taste aversion learning, the avoidance of fluids and foods previously associated with the aversive effects of a variety of drugs. The database includes articles as early as 1951, and papers just published given that the database is ongoing and constantly updated. In the mid 1950''s, John Garcia and his colleagues at the Radiological Defense Laboratory at Hunters Point in San Francisco assessed the effects of ionizing radiation on a myriad of behaviors in the laboratory rat. One of their behavioral findings was that radiated rats avoided consumption of solutions that had been present during radiation, presumably due to the association of the taste of the solution with the aversive effects of the radiation. These results were published in Science and introduced to the literature the phenomenon of conditioned taste aversion learning (or the Garcia Effect). Subsequently, Garcia and his colleagues demonstrated that such learning appeared unique in a number of respects, including the fact that these aversions were acquired often in a single conditioning trial, selectively to gustatory stimuli and even when long delays were imposed between access to the solution and administration of the aversive agent. Together, these unique characteristics appeared to violate the basic tenets of traditional learning theory and along with a number of other behavioral phenomena (e.g., bird song learning, species-specific defense reactions, tonic immobility and schedule-induced polydipsia) introduced the concept of biological constraints on learning that forced a reconceptualization of the role evolution played in the acquisition of behavior (Garcia and Ervin, 1968; Revusky and Garcia, 1970; Rozin and Kalat, 1971). Although the initial investigations into conditioned taste aversion learning focused on these biological and evolutionary issues and their relation to learning, research in this area soon assessed the basic generality of the phenomenon, specifically, under what conditions such learning did or did not occur. With such research, a wide variety of gustatory stimuli were reported as effective conditioned stimuli and an extensive list of drugs with diverse consequences were reported as effective aversion-inducing agents. Aversions were established in a range of strains and species and under many experimental conditions. Research in this area continues to extend the conditions under which such learning occurs and to demonstrate its biological, neurochemical and anatomical substrates. Although the conditions under which aversion learning are reported to occur appear to generalize from the specific conditions under which they were originally reported, a number of factors including sex, age, training and testing procedures, deprivation level and drug history, all affect the rate of its acquisition and its terminal strength (Riley, 1998). In addition to these experimental demonstrations and assessments of generality, research on conditioned taste aversions has expanded to include investigations into its research and clinical applications (Braveman and Bronstein, 1985). In so doing, taste aversion learning has been applied to the characterization and classification of drug toxicity, the demonstration of the stimulus properties of abused drugs, the management of wildlife predation, the assessment of the etiology and treatment of cancer anorexia, the study of the biochemistry and molecular biology of learning, the etiology and control of alcohol use and abuse, the receptor characterization of the motivational effects of drugs, the occurrence of drug interactions, the characterization of drug withdrawal, the determination of taste psychophysics, the treatment of autoimmune diseases and the evaluation of the role of malaise in drug-induced satiety and drug-induced behavioral deficits. The speed with which aversions are acquired and the relative robustness of this preparation have made conditioned taste aversion learning a widely used, highly replicable and sensitive tool. In 1976, we published the first of three bibliographies on conditioned taste aversion learning. In this initial publication (see Riley and Baril, 1976), we listed and annotated 403 papers in this field. Subsequent lists published in 1977 (Riley and Clarke, 1977) and 1985 (Riley and Tuck, 1985) listed 632 and 1373 papers, respectively. Since that time, we have maintained a bibliography on taste aversion learning utilizing a variety of journal and on-line searches as well as benefiting from the generous contribution of preprints, reprints and pdf files from many colleagues. To date, the number of papers on conditioned taste aversion learning is approaching 3000. The present database lists these papers and provides a mechanism for searching the articles according to a number of search functions. Specifically, it was constructed to provide the reader access to these articles via a variety of search terms, including Author(s), Key Words, Date, Article Title and Journal. One can search for single or multiple items within any specific category. Further, one can search a single or combination of categories. The database is constantly being updated, and any feedback and suggestions are welcome and can be sent to CTALearning (at) american.edu.

Proper citation: Conditioned Taste Aversion: An Annotated Bibliography (RRID:SCR_005953) Copy   

•   Source: SciCrunch Registry

http://sparkinsight.org

A clustering and visualization tool that enables the interactive exploration of genome-wide data, with a specialization in epigenomics data. Spark is also available as a service within the Epigenome toolset of the Genboree Workbench. The approach utilizes data clusters as a high-level visual guide and supports interactive inspection of individual regions within each cluster. The cluster view links to gene ontology analysis tools and the detailed region view connects to existing genome browser displays taking advantage of their wealth of annotation and functionality.

Proper citation: Spark (RRID:SCR_006207) Copy   

•   Source: SciCrunch Registry

http://antibodyregistry.org/

Public registry of antibodies with unique identifiers for commercial and non-commercial antibody reagents to give researchers a way to universally identify antibodies used in publications. The registry contains antibody product information organized according to genes, species, reagent types (antibodies, recombinant proteins, ELISA, siRNA, cDNA clones). Data is provided in many formats so that authors of biological papers, text mining tools and funding agencies can quickly and accurately identify the antibody reagents they and their colleagues used. The Antibody Registry allows any user to submit a new antibody or set of antibodies to the registry via a web form, or via a spreadsheet upload.

Proper citation: Antibody Registry (RRID:SCR_006397) Copy   

•   Source: SciCrunch Registry

https://www.phenxtoolkit.org/

Set of measures intended for use in large-scale genomic studies. Facilitate replication and validation across studies. Includes links to standards and resources in effort to facilitate data harmonization to legacy data. Measurement protocols that address wide range of research domains. Information about each protocol to ensure consistent data collection.Collections of protocols that add depth to Toolkit in specific areas.Tools to help investigators implement measurement protocols.

Proper citation: Phenotypes and eXposures Toolkit (RRID:SCR_006532) Copy   

•   Source: SciCrunch Registry

http://trans.nih.gov/bmap/index.htm

The Brain Molecular Anatomy Project is a trans-NIH project aimed at understanding gene expression and function in the nervous system. BMAP has two major scientific goals: # Gene discovery: to catalog of all the genes expressed in the nervous system, under both normal and abnormal conditions. # Gene expression analysis: to monitor gene expression patterns in the nervous system as a function of cell type, anatomical location, developmental stage, and physiological state, and thus gain insight into gene function. In pursuit of these goals, BMAP has launched several initiatives to provide resources and funding opportunities for the scientific community. These include several Requests for Applications and Requests for Proposals, descriptions of which can be found in this Web site. BMAP is also in the process of establishing physical and electronic resources for the community, including repositories of cDNA clones for nervous system genes, and databases of gene expression information for the nervous system. Most of the BMAP initiatives so far have focused on the mouse as a model species because of the ease of experimental and genetic manipulation of this organism, and because many models of human disease are available in the mouse. However, research in humans, other mammalian species, non-mammalian vertebrates, and invertebrates is also being funded through BMAP. For the convenience of interested investigators, we have established this Web site as a central information resource, focusing on major NIH-sponsored funding opportunities, initiatives, genomic resources available to the research community, courses and scientific meetings related to BMAP initiatives, and selected reports and publications. When appropriate, we will also post initiatives not directly sponsored by BMAP, but which are deemed relevant to its goals. Posting decisions are made by the Trans-NIH BMAP Committee

Proper citation: BMAP - Brain Molecular Anatomy Project (RRID:SCR_008852) Copy   

•   Source: SciCrunch Registry

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

A fast, scalable tool developed at the Johns Hopkins University to automatically segment the major anatomical fiber tracts within the human brain from clinical quality diffusion tensor MR imaging. With an atlas-based Markov Random Field representation, DOTS directly estimates the tract probabilities, bypassing tractography and associated issues. Overlapping and crossing fibers are modeled and DOTS can also handle white matter lesions. DOTS is released as a plug-in for the MIPAV software package and as a module for the JIST pipeline environment. They are therefore cross-platform and compatible with a wide variety of file formats.

Proper citation: DOTS WM tract segmentation (RRID:SCR_009459) 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://www.webgestalt.org/

Web based gene set analysis toolkit designed for functional genomic, proteomic, and large-scale genetic studies from which large number of gene lists (e.g. differentially expressed gene sets, co-expressed gene sets etc) are continuously generated. WebGestalt incorporates information from different public resources and provides a way for biologists to make sense out of gene lists. This version of WebGestalt supports eight organisms, including human, mouse, rat, worm, fly, yeast, dog, and zebrafish.

Proper citation: WebGestalt: WEB-based GEne SeT AnaLysis Toolkit (RRID:SCR_006786) Copy   

•   Source: SciCrunch Registry

http://cancercontrol.cancer.gov/tcrb/tturc/

A transdisciplinary approach to the full spectrum of basic and applied research on tobacco use to reduce the disease burden of tobacco use, including: * Etiology of tobacco use and addiction * Impact of advertising and marketing * Prevention of tobacco use * Treatment of tobacco use and addiction * Identification of biomarkers of tobacco exposure * Identification of genes related to addiction and susceptibility to harm from tobacco Goals * Increase the number of investigators from relevant disciplines who focus on the study of tobacco use as part of transdisciplinary teams. * Generate basic research evidence to improve understanding of the etiology and natural history of tobacco use. * Produce evidence-based tobacco use interventions that can translate to the community and specific understudied or underserved populations. * Increase the number of evidence-based interventions that are novel, including the development, testing and dissemination of innovative behavioral treatments and prevention strategies based upon findings from basic research. * Train transdisciplinary investigators capable of conducting cutting-edge tobacco use research. * Increase the number of peer-reviewed publications in the areas of tobacco use, nicotine addiction, and treatment.

Proper citation: Transdisciplinary Tobacco Use Research Centers (RRID:SCR_006858) Copy   

•   Source: SciCrunch Registry

https://datashare.nida.nih.gov

Website which allows data from completed clinical trials to be distributed to investigators and public. Researchers can download de-identified data from completed NIDA clinical trial studies to conduct analyses that improve quality of drug abuse treatment. Incorporates data from Division of Therapeutics and Medical Consequences and Center for Clinical Trials Network.

Proper citation: NIDA Data Share (RRID:SCR_002002) Copy   

•   Source: SciCrunch Registry

http://www.wakeforestinnovations.com/technology-for-license/demon-voltammetry-and-analysis-software/

A software for performing fast scan cyclic voltammetry recordings in brain tissue for detection of neurotransmitters. It was written in the LabView programming language and can be used to provide command voltage to equipment and record the resulting waveforms. The analysis portion of the software can view and export data, apply noise filters, perform chemometric and waveform kinetic analysis, and create figures.

Proper citation: Demon Voltammetry and Analysis Software (RRID:SCR_014468) Copy   

•   Source: SciCrunch Registry