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SciCrunch Registry is a curated repository of scientific resources, with a focus on biomedical resources, including tools, databases, and core facilities - visit SciCrunch to register your resource.
SchistoDB is a genomic database for the parasitic organism Schistosoma mansoni, one of the major causative agents of schistosomiasis worldwide. It currently incorporates sequences and annotation for S. mansoni in a single user-friendly database. Several genomic scale analyses are available as well as ESTs, oligonucleotides, metabolic pathways and drugs. Make your data available: If you''d like to have your updates and/or datasets integrated in SchistoDB, drop us an email.
Proper citation: Schistosoma mansoni Database (RRID:SCR_004341) Copy
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
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
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
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
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
Data archive of more than 500,000 files of research in the social sciences, hosting 16 specialized collections of data in education, aging, criminal justice, substance abuse, terrorism, and other fields. ICPSR comprises a consortium of about 700 academic institutions and research organizations providing training in data access, curation, and methods of analysis for the social science research community. ICPSR welcomes and encourages deposits of digital data. ICPSR's educational activities include the Summer Program in Quantitative Methods of Social Research external link, a comprehensive curriculum of intensive courses in research design, statistics, data analysis, and social methodology. ICPSR also leads several initiatives that encourage use of data in teaching, particularly for undergraduate instruction. ICPSR-sponsored research focuses on the emerging challenges of digital curation and data science. ICPSR researchers also examine substantive issues related to our collections, with an emphasis on historical demography and the environment.
Proper citation: Inter-university Consortium for Political and Social Research (ICPSR) (RRID:SCR_003194) Copy
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
Open platform for analyzing and sharing neuroimaging data from human brain imaging research studies. Brain Imaging Data Structure ( BIDS) compliant database. Formerly known as OpenfMRI. Data archives to hold magnetic resonance imaging data. Platform for sharing MRI, MEG, EEG, iEEG, and ECoG data.
Proper citation: OpenNeuro (RRID:SCR_005031) Copy
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
http://www.nida.nih.gov/mediaguide/index.html
The latest findings on the science of drug abuse and addiction and commonly abused drugs, and lists resources for more information. They are committed to bringing timely, factual information on addiction and treatment to the press and public. NIDA''s Public Information and Liaison Branch (PILB) is part of NIDA''s Office of Science Policy and Communications. Linking scientists, the scientific community, and the media, PILB supports the rapid dissemination of research information to inform policy and to improve practice. NIDA''s goal is to ensure that science - not ideology or anecdote - forms the foundation of public information on drug abuse and addiction. NIDAs online MEDIA GUIDE provides answers on how to find what you need to know about drug abuse and addiction, including information on the basics (The Science of Drug Abuse and Addiction and Commonly Abused Drugs), resources (Where to Find Nationwide Trends and Statistics, NIDA Resources, and Other Government Web Sites for Health and Science Information), NIDAs history and background, a glossary and relevant contact information. NIDA is pleased to offer this guide to the important findings that are emerging as a result of research on addiction and its treatment. NIDA, part of the National Institutes of Health under the U.S. Department of Health and Human Services, supports most of the world''s research on drug abuse and addiction, including basic and behavioral science research that addresses fundamental and essential questions relevant to drug abuse, ranging from its causes and consequences to its treatment and prevention. The purpose of this guide is to give journalists fast and user-friendly access to the latest scientific information but it is useful for anyone interested in how to access accurate information about drug abuse and addiction. In more than three decades as a researcher, I have seen the impact that science and health journalists have had in bringing scientific research to the public. It is through information that Americans gain hope and understanding. I have come to know many of you over the years and remain committed to releasing scientific information as quickly as possible for rapid dissemination to the public. Please keep this guide nearby as a useful tool and let us know how NIDA''s public liaison staff can help you reach your information and deadline needs. A PDF version is available for download.
Proper citation: National Institute on Drug Abuse Media Guide (RRID:SCR_006850) Copy
http://hendrix.imm.dtu.dk/software/lyngby/
Matlab toolbox for the analysis of functional neuroimages (PET, fMRI). The toolbox contains a number of models: FIR-filter, Lange-Zeger, K-means clustering among others, visualizations and reading of neuroimaging files.
Proper citation: Lyngby (RRID:SCR_007143) Copy
http://jaxmice.jax.org/list/ra1642.html
Produce new neurological mouse models that could serve as experimental models for the exploration of basic neurobiological mechanisms and diseases. The impetus for the program resulted from the recognition that: * The value of genomic data would remain limited unless more information about the functionality of its individual components became available. * The task of linking genes to specific behavior would best be accomplished by employing a combination of different approaches. In an effort to complement already existing programs, the Neuroscience Mutagenesis Facility decided to use: a random, genome-wide approach to mutagenesis, i.e.N-ethyl-N-nitrosourea (ENU) as the mutagen; a three-generation back-cross breeding scheme to focus on the detection of recessive mutations; behavioral screens selective for the detection of phenotypes deemed useful for the program goals. The resulting mutant mouse lines have been available to the scientific community for the last five years and over 700 NMF mice have been sent to interested investigators for research; these mutant mouse lines will remain available as frozen embryos (which can be re-derived on request) and can be ordered through the JAX customer service at 1-800-422-6423 (or 207-288-5845). The results of the work of the Neuroscience Mutagenesis Facility and that of two other neurogenesis centers, i.e. The Neurogenomics Project at Northwestern University, and the Neuromutagenesis Project of the Tennessee Mouse Genome Consortium, can also be seen at Neuromice.org, a common web site of these three research centers; in addition, information about all mutants produced by these groups has been recorded in MGI.
Proper citation: JAX Neuroscience Mutagenesis Facility (RRID:SCR_007437) Copy
Next generation sequencing and genotyping services provided to investigators working to discover genes that contribute to disease. On-site statistical geneticists provide insight into analysis issues as they relate to study design, data production and quality control. In addition, CIDR has a consulting agreement with the University of Washington Genetics Coordinating Center (GCC) to provide statistical and analytical support, most predominantly in the areas of GWAS data cleaning and methods development. Completed studies encompass over 175 phenotypes across 530 projects and 620,000 samples. The impact is evidenced by over 380 peer-reviewed papers published in 100 journals. Three pathways exist to access the CIDR genotyping facility: * NIH CIDR Program: The CIDR contract is funded by 14 NIH Institutes and provides genotyping and statistical genetic services to investigators approved for access through competitive peer review. An application is required for projects supported by the NIH CIDR Program. * The HTS Facility: The High Throughput Sequencing Facility, part of the Johns Hopkins Genetic Resources Core Facility, provides next generation sequencing services to internal JHU investigators and external scientists on a fee-for-service basis. * The JHU SNP Center: The SNP Center, part of the Johns Hopkins Genetic Resources Core Facility, provides genotyping to internal JHU investigators and external scientists on a fee-for-service basis. Data computation service is included to cover the statistical genetics services provided for investigators seeking to identify genes that contribute to human disease. Human Genotyping Services include SNP Genome Wide Association Studies, SNP Linkage Scans, Custom SNP Studies, Cancer Panel, MHC Panels, and Methylation Profiling. Mouse Genotyping Services include SNP Scans and Custom SNP Studies.
Proper citation: Center for Inherited Disease Research (RRID:SCR_007339) Copy
http://www.jneurosci.org/supplemental/18/12/4570/
THIS RESOURCE IS NO LONGER IN SERVICE, documented on January 29, 2013. Supplemental data for the paper Changes in mitochondrial function resulting from synaptic activity in the rat hippocampal slice, by Vytautas P. Bindokas, Chong C. Lee, William F. Colmers, and Richard J. Miller that appears in the Journal of Neuroscience June 15, 1998. You can view digital movies of changes in fluorescence intensity by clicking on the title of interest.
Proper citation: Hippocampal Slice Wave Animations (RRID:SCR_008372) Copy
An infrastructure for managing of diverse computational biology resources - data, software tools and web-services. The iTools design, implementation and meta-data content reflect the broad NCBC needs and expertise (www.NCBCs.org).
Proper citation: iTools (RRID:SCR_009626) Copy
http://umcd.humanconnectomeproject.org
Web-based repository and analysis site for connectivity matrices that have been derived from neuroimaging data including different imaging modalities, subject groups, and studies. Users can analyze connectivity matrices that have been shared publicly and upload their own matrices to share or analyze privately.
Proper citation: USC Multimodal Connectivity Database (RRID:SCR_012809) Copy
https://github.com/djamesbarker/pMAT
Open source software suite for analysis of fiber photometry data.
Proper citation: pMAT (RRID:SCR_022570) Copy
https://cloudreg.neurodata.io/
Software automated, terascale, cloud based image analysis pipeline for preprocessing and cross modal, nonlinear registration between volumetric datasets with artifacts. Automatic terabyte scale cross modal brain volume registration.
Proper citation: CloudReg (RRID:SCR_022795) Copy
http://murphylab.web.cmu.edu/services/SLIF/
SLIF finds fluorescence microscope images in on-line journal articles, and indexes them according to cell line, proteins visualized, and resolution. Images can be accessed via the SLIF Web database. SLIF takes on-line papers and scans them for figures that contain fluorescence microscope images (FMIs). Figures typically contain multiple FMIs, to SLIF must segment these images into individual FMIs. When the FMI images are extracted, annotations for the images (for instance, names of proteins and cell-lines) are also extracted from the accompanying caption text. Protein annotation are also used to link to external databases, such as the Gene Ontology DB. The more detailed process includes: segmentation of images into panels; panel classification, to find FMIs; segmentation of the caption, to find which portions of the caption apply to which panels; text-based entity extraction; matching of extracted entities to database entries; extraction of panel labels from text and figures; and alignment of the text segments to the panels. Extracted FMIs are processed to find subcellular location features (SLFs), and the resulting analyzed, annotated figures are stored in a database, which is accessible via SQL queries.
Proper citation: Subcellular Location Image Finder (RRID:SCR_006723) Copy
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