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https://www.crukscotlandinstitute.ac.uk/advanced-technologies/molecular-technology.html

Core provides Next Generation Sequencing (NGS) services and Single Cell services predominantly focussing on single cell RNAseq. Processes samples for variety of cancer associated projects, in both mouse and human derived materials. Offers full end-to-end service, from initial study design and planning, through sample QC, full library preparation, sequencing and data return. Offers range of standard molecular tests covering, plasmid purifications, Sanger sequencing and mycoplasma screening.

Proper citation: Cancer Research UK Scotland Institute Molecular Technology Service Core Facility (RRID:SCR_027368) Copy   

•   Source: SciCrunch Registry

https://marmotgraph.org

Knowledge graph system developed for managing and organizing rich metadata objects, initially for the Human Brain Project (HBP) and now extended to be a more generic, domain-agnostic solution. It is associated with CSCS (Swiss National Supercomputing Centre) and aims to provide a comprehensive toolset and API for working with knowledge graphs.

Proper citation: MarmotGraph (RRID:SCR_027452) Copy   

•   Source: SciCrunch Registry

https://www.umassmed.edu/shrna/

Facility houses complete collections of human and mouse lentiviral short hairpin RNA (shRNA) libraries from Open Biosystems/GE Dharmacon, Mammalian Gene Collection (MGC) cDNA Library, and human and mouse CRISPR/Cas9 GeCKO v2 libraries from Addgene.

Proper citation: Massachusetts University Medical School RNAi Core Facility (RRID:SCR_017727) Copy   

•   Source: SciCrunch Registry

https://sdrc.stanford.edu/sdrc-research-cores/dimc/home/

Core facility that provides immune monitoring assays at the RNA, protein, and cellular level, as well as archiving, reporting, and data mining support for clinical and translational studies related to Diabetes. The DIMC is a specialized subcore of the Human Immune Monitoring Center (HIMC) at Stanford.

Proper citation: Stanford Diabetes Research Center Diabetes Immune Monitoring Core (RRID:SCR_016210) Copy   

•   Source: SciCrunch Registry

http://cmrm.med.jhmi.edu/cmrm/atlas/human_data/file/JHUtemplate_newuser.html

DTI white matter atlases with different data sources and different image processing. These include single-subject, group-averaged, B0 correction, processed atlases (White Matter Parcellation Map, Tract-probability maps, Conceptual difference between the WMPM and tract-probability maps), and linear or non-linear transformation for automated white matter segmentation. # Adam single-subject white matter atlas (old version): These are electronic versions of atlases published in Wakana et al, Radiology, 230, 77-87 (2004) and MRI Atlas of Human White Matter, Elsevier. ## Original Adam Atlas: 256 x 256 x 55 (FOV = 246 x 246 mm / 2.2 mm slices) (The original matrix is 96x96x55 (2.2 mm isotropic) which is zerofilled to 256 x 256 ## Re-sliced Adam Atlas: 246 x 246 x 121 (1 mm isotropic) ## Talairach Adam: 246 x 246 x 121 (1 mm isotropic) # New Eve single-subject white matter atlas: The new version of the single-subject white matter atlas with comprehensive white matter parcellation. ## MNI coordinate: 181 x 217 x 181 (1 mm isotropic) ## Talairach coordinate: 181 x 217 x 181 (1 mm isotropic) # Group-averaged atlases: This atlas was created from their normal DTI database (n = 28). The template was MNI-ICBM-152 and the data from the normal subjects were normalized by affine transformation. Image dimensions are 181x217x181, 1 mm isotropic. There are two types of maps. The first one is the averaged tensor map and the second one is probabilistic maps of 11 white matter tracts reconstructed by FACT. # ICBM Group-averaged atlases: This atlas was created from ICBM database. All templates follow Radiology convention. You may need to flip right and left when you use image registration software that follows the Neurology convention.

Proper citation: DTI White Matter Atlas (RRID:SCR_005279) Copy   

•   Source: SciCrunch Registry

http://blog.ketyov.com/

Bradley Voytek''''s blog is where he tries out new ideas. He will often be wrong, but that''''s the point. He is a Neuroscientist studying human cognition, neuroplasticity, and brain computer interfacing. Into really geeky stuff. World zombie neuroscience expert. Also runs brainSCANr.com with his wife, Jessica.

Proper citation: Oscillatory Thoughts (RRID:SCR_005481) Copy   

•   Source: SciCrunch Registry

http://bioapps.rit.albany.edu/MITOPRED/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 16, 2013. It predicts nuclear-encoded mitochondrial proteins from all eukaryotic species including plants. Prediction is based on the occurrence patterns of Pfam domains (version 16.0) in different cellular locations, amino acid composition and pI value differences between mitochondrial and non-mitochondrial locations. Additionally, you may download MITOPRED predictions for complete proteomes. Re-calculated predictions are instantly accessible for proteomes of Saccharomyces cerevisiae, Caenorhabditis elegans, Drosophila, Homo sapiens, Mus musculus and Arabidopsis species as well as all the eukaryotic sequences in the Swiss-Prot and TrEMBL databases. Queries, at different confidence levels, can be made through four distinct options: (i) entering Swiss-Prot/TrEMBL accession numbers; (ii) uploading a local file with such accession numbers; (iii) entering protein sequences; (iv) uploading a local file containing protein sequences in FASTA format. The Mitopred algorithm works based on the differences in the Pfam domain occurrence patters and amino acid composition differences in different cellular compartments. Location specific Pfam domains have been determined from the entire eukaryotic set of Swissprot database. Similarly, differences in the amino acid composition between mitochondrial and non-mitochondrial sequences were pre-calculated. This information is used to calculate location-specific amino acid weights that are used to calculate amino acid score. Similarly, pI average values of the N-terminal 25 residues in different cellular location were also determined. This knowledge-base is accessed by the program during execution.

Proper citation: mitopred (RRID:SCR_006135) Copy   

•   Source: SciCrunch Registry

https://bioinformatics.oxfordjournals.org/content/21/4/557.full.pdf

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 18, 2016. MAP-O-MAT is a web-based server for automated linkage mapping of human polymorphic DNA markers. The server uses publicly available genotype data for over 15,000 markers. It facilitates the verification of order and map distances for custom mapping sets using genotype data from the CEPH database, and from the Marshfield, SNP Consortium and Rutgers linkage maps. The CRI-MAP program is used for likelihood calculations and some mapping algorithms, and physical map positions are provided from the human genome assembly.

Proper citation: MAP-O-MAT (RRID:SCR_008197) Copy   

•   Source: SciCrunch Registry

http://igs-server.cnrs-mrs.fr/mgdb/Rickettsia/

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 18, 2016. Rickettsia are obligate intracellular bacteria living in arthropods. They occasionally cause diseases in humans. To understand their pathogenicity, physiologies and evolutionary mechanisms, RicBase is sequencing different species of Rickettsia. Up to now we have determined the genome sequences of R. conorii, R. felis, R. bellii, R. africae, and R. massiliae. The RicBase aims to organize the genomic data to assist followup studies of Rickettsia. This website contains information on R. conorii and R. prowazekii. A R. conorii and R. prowazekii comparative genome map is also available. Images of genome maps, dendrogram, and sequence alignment allow users to gain a visualization of the diagrams.

Proper citation: Rickettsia Genome Database (RRID:SCR_007102) Copy   

•   Source: SciCrunch Registry

http://neurocritic.blogspot.com/

The Neurocritic is a blog deconstructing the most sensationalistic recent findings in Human Brain Imaging, Cognitive Neuroscience, and Psychopharmacology. Born in West Virginia in 1980, The Neurocritic embarked upon a roadtrip across America at the age of thirteen with his mother. She abandoned him when they reached San Francisco and The Neurocritic descended into a spiral of drug abuse and prostitution. At fifteen, The Neurocritic''s psychiatrist encouraged him to start writing as a form of therapy.

Proper citation: Neurocritic (RRID:SCR_006528) Copy   

•   Source: SciCrunch Registry

http://www.lgfus.ca

Provides system for Splicing isoform Annotation. This LISA platform allows high throughput annotation and functional analysis of Alternate Splicing in humans.

Proper citation: Quebeck Sherbrooke University Genomic Core Facility (RRID:SCR_017785) Copy   

•   Source: SciCrunch Registry

https://ipsc.bsd.uchicago.edu/

Core provides training to use latest episomal techniques to reprogram, expand and characterize human and mice iPS cells from skin or blood tissues of healthy subjects and diseased patients. Develops capability to differentiate iPS cells into specific somatic cells, such as neutrons, cardiomyocytes, and hepatocytes.

Proper citation: Chicago University iPSC Core Facility (RRID:SCR_017918) Copy   

•   Source: SciCrunch Registry

https://ki.mit.edu/sbc/escell

Core provides service support to all MIT investigators who utilize specialized in vitro cells such as stem cells, organoids, or primary cell lines and/or novel mouse models to study human diseases such as cancer. Projects involve generation of new model system, such as CRISPR-mediated gene editing in mouse to introduce mutation that mimics one found in patients. Helps with projects required optimization of finicky cell cultures and other challenges.Provides customizable set of service options to match specific needs of each project, including consultative advice and troubleshooting, complete tissue culture and microinjection services within our facilities or hands-on training to enable investigators to perfom these experiments either at their own laboratory or within our facilities.Services Include:Gene Targeting genomic modification through traditional or CRISPR/Cas9 locus targeting, assistance with targeting strategies and vector designs;Embryonic Stem Cells generation of new ES lines from mouse strains, importation and testing of lines from outside sources, differentiation of ES lines into specific cell lineages or cell types and more;Microinjection injection of mouse ES cells into blastocysts to generate chimeras and injection of DNA, RNA or CRISPR RNPs into the pronucleus of fertilized mouse eggs to generate transgenic and edited mice;Specialized Tissue Culture establishemnt of new primary cell cultures from a tumor, tissue or organ; Isolation of fibroblasts (MEFs) from mice for culture and analysis;Tissue Culture for Xenograft and Syngenic Modeling optimization, validation and testing of cell lines for orthotopic placement into mice, coordinated with Preclinical Testing Facility;Repository of Reagent Mice Commonly used wild type mice such as C57BL/6j as well as KrasG12D-based models of cancers are maintained on campus for efficient distrubution;Training and Troubleshooting for all aspects of embryonic stem cells, primary cultures, animal breeding etc.;Serum, DMEM, LIF and other media components that have been tested and verified for use with ES cells.

Proper citation: Massachusetts Institute of Technology Koch Institute Preclinical Modeling Core Facility (RRID:SCR_017899) Copy   

•   Source: SciCrunch Registry

http://www.cti.northwestern.edu/

Core is Northwestern Radiology research facility providing translational imaging capabilities that promote pre-clinical and clinical research efforts. CTI occupies space in basement of Olson building housing imaging equipment along with research staff. Services include Cardiovascular Imaging for development, analysis and application of MRI methods providing insights into structure and function of cardiovascular system,NeuroImaging for functional MRI using spectroscopy and diffusion-weighted imaging to studying human anatomy and physiology during development and disease,Small Animal Imaging for molecular and functional imaging of biological processes in living animal models to study diseases and responses to intervention.

Proper citation: Northwestern University Center for Translational Imaging Core Facility (RRID:SCR_017878) Copy   

•   Source: SciCrunch Registry

http://www.loni.usc.edu/

Biomedical technology resource center specializing in novel approaches and tools for neuroimaging. It develops novel strategies to investigate brain structure and function in their full multidimensional complexity. There is a rapidly growing need for brain models comprehensive enough to represent brain structure and function as they change across time in large populations, in different disease states, across imaging modalities, across age and sex, and even across species. International networks of collaborators are provided with a diverse array of tools to create, analyze, visualize, and interact with models of the brain. A major focus of these collaborations is to develop four-dimensional brain models that track and analyze complex patterns of dynamically changing brain structure in development and disease, expanding investigations of brain structure-function relations to four dimensions.

Proper citation: Laboratory of Neuro Imaging (RRID:SCR_001922) Copy   

•   Source: SciCrunch Registry

http://www.cs.tau.ac.il/~shlomito/tissue-net/

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 23, 2016. Network visualizations in which the expression and predicted flux data are projected over the global human network. These network visualizations are accessible through the supplemental website using the publicly available Cytoscape software (Cline, Smoot et al. 2007). Since many high degree nodes exist in the network, special layouts are required to produce network visualizations that are readily interpretable. To this end we produced network visualizations in which hub nodes are repeated multiple times and hence layouts with a small number of edge crossings can be generated. Contains entries for brain compartments and brain pathways.

Proper citation: Network-based Prediction of Human Tissue-specific Metabolism (RRID:SCR_007392) Copy   

•   Source: SciCrunch Registry

http://aws.amazon.com/1000genomes/

A dataset containing the full genomic sequence of 1,700 individuals, freely available for research use. The 1000 Genomes Project is an international research effort coordinated by a consortium of 75 companies and organizations to establish the most detailed catalogue of human genetic variation. The project has grown to 200 terabytes of genomic data including DNA sequenced from more than 1,700 individuals that researchers can now access on AWS for use in disease research free of charge. The dataset containing the full genomic sequence of 1,700 individuals is now available to all via Amazon S3. The data can be found at: http://s3.amazonaws.com/1000genomes The 1000 Genomes Project aims to include the genomes of more than 2,662 individuals from 26 populations around the world, and the NIH will continue to add the remaining genome samples to the data collection this year. Public Data Sets on AWS provide a centralized repository of public data hosted on Amazon Simple Storage Service (Amazon S3). The data can be seamlessly accessed from AWS services such Amazon Elastic Compute Cloud (Amazon EC2) and Amazon Elastic MapReduce (Amazon EMR), which provide organizations with the highly scalable compute resources needed to take advantage of these large data collections. AWS is storing the public data sets at no charge to the community. Researchers pay only for the additional AWS resources they need for further processing or analysis of the data. All 200 TB of the latest 1000 Genomes Project data is available in a publicly available Amazon S3 bucket. You can access the data via simple HTTP requests, or take advantage of the AWS SDKs in languages such as Ruby, Java, Python, .NET and PHP. Researchers can use the Amazon EC2 utility computing service to dive into this data without the usual capital investment required to work with data at this scale. AWS also provides a number of orchestration and automation services to help teams make their research available to others to remix and reuse. Making the data available via a bucket in Amazon S3 also means that customers can crunch the information using Hadoop via Amazon Elastic MapReduce, and take advantage of the growing collection of tools for running bioinformatics job flows, such as CloudBurst and Crossbow.

Proper citation: 1000 Genomes Project and AWS (RRID:SCR_008801) Copy   

•   Source: SciCrunch Registry

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

Data tables providing an overview of information about stem cells that have been derived from mice and humans. The tables summarize published research that characterizes cells that are capable of developing into cells of multiple germ layers (i.e., multipotent or pluripotent) or that can generate the differentiated cell types of another tissue (i.e., plasticity) such as a bone marrow cell becoming a neuronal cell. The tables do not include information about cells considered progenitor or precursor cells or those that can proliferate without the demonstrated ability to generate cell types of other tissues. The tables list the tissue from which the cells were derived, the types of cells that developed, the conditions under which differentiation occurred, the methods by which the cells were characterized, and the primary references for the information.

Proper citation: National Institutes of Health Stem Cell Tables (RRID:SCR_008359) Copy   

•   Source: SciCrunch Registry

http://harvard.eagle-i.net/i/0000012a-2518-fb6c-5617-794280000000

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on October 27, 2023. Core provides services: RT PCR service, Gene expression profiling service, Proteomics analysis service, Bioinformatics and Systems Biology analyses, Next Generation Sequencing Service, Affymetrix Human and Mouse Gene 2.0 ST Arrays and 2.1 ST Arrayplates. Core proteomics facility for the Dana-Farber/Harvard Cancer Center. Workflows and algorithms for analysis of next-generation sequencing data including RNA-Seq, ChIP-Seq, Epigenetics-Seq and DNA seq, Comprehensive workflow for analysis of Microbiome sequencing data, Integrated systems biology analysis of transcriptome, miRNA, epigenome, metabolomics and proteomics data. Pipelines: MALDI Tissue imaging and targeted quantitative proteomics.

Proper citation: Beth Israel Deaconess Medical Center Genomics Proteomics Bioinformatics and Systems Biology Center (RRID:SCR_009668) Copy   

•   Source: SciCrunch Registry

http://www.accp.com/

A professional and scientific society that provides leadership, education, advocacy, and resources enabling clinical pharmacists to achieve excellence in practice and research. Their membership is composed of practitioners, scientists, educators, administrators, students, residents, fellows, and others committed to excellence in clinical pharmacy and patient pharmacotherapy. The Practice and Research Networks (PRNs) represent focused interest groups of ACCP members, providing a means for clinical pharmacists with common practice and research interests to gather for professional interaction, networking, and continuing education. Activities within individual PRNs may vary depending on the interests and perceived needs of their members. All PRNs conduct educational programs within their interest areas at the ACCP Annual Meeting and the Spring Practice and Research Forum.

Proper citation: American College of Clinical Pharmacy (RRID:SCR_003957) Copy   

•   Source: SciCrunch Registry