Are you sure you want to leave this community? Leaving the community will revoke any permissions you have been granted in this community.
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.
http://www.oreganno.org/oregano/
Open source, open access database and literature curation system for community based annotation of experimentally identified DNA regulatory regions, transcription factor binding sites and regulatory variants. Automatically cross referenced against PubMED, Entrez Gene, EnsEMBL, dbSNP, eVOC: Cell type ontology, and Taxonomy database. Community driven resource for curated regulatory annotation.
Proper citation: Open Regulatory Annotation Database (RRID:SCR_007835) Copy
http://www.med.upenn.edu/genetics/dnaseq/index.shtml
Core facility that provides the following services: Large sequencing project support, Sanger sequencing service, High throughput DNA sequencing, Ion Torrent Personal Genome Machine sequencing, Template preparation and purification, Roche 454 sequencing, Sequence analysis and database search support, Construction of targeting vector for gene targeting, Genotyping and Fragment Analysis service, Molecular biology services, Mouse genotyping, and Ion Personal Genome Machine sequencing data analysis. The DNA Sequencing Facility provides long read, automated Sanger sequencing; microsatellite-based genotyping and fragment analysis; plasmid and BAC DNA preparation and purification; and related molecular biological services including PCR, cloning, sub-cloning, site-directed mutagenesis, and preparation of targeting vectors for gene targeting in mice. Core also provides services and support for analysis and interpretation of sequence data as well as the design of approaches to complex sequencing projects. For the last four years the facility has been providing Roche 454 sequencing service that includes library preparation, emulsion PCR and pyrosequencing for both genomic DNA and amplicons.
Proper citation: University of Pennsylvania Genomics Analysis Core (RRID:SCR_011061) Copy
https://lsom.uthscsa.edu/dcsa/research/cores-facilities/optical-imaging/
Service resource which makes imaging technology available to investigators on UTHSCSA campus and neighboring scientific community. Core Optical Imaging Facility offers access to technology for imaging of living cells, tissues, and animals, consultation, education and assistance regarding theory and application of optical imaging techniques, technical advice on specimen preparation techniques and probe selection.
Proper citation: Texas University Health Science Center at San Antonio Long School of Medicine Department of Cell Systems and Anatomy Optical Imaging Core Facility (RRID:SCR_012171) Copy
https://cellrank.readthedocs.io/en/stable/
Software package for directed single cell fate mapping in diverse scenarios, including regeneration, reprogramming and disease. Automatically detects initial, intermediate and terminal populations, predicts fate potentials and visualizes continuous gene expression trends along individual lineages. Applied to lineage traced cellular reprogramming data, predicted fate probabilities correctly recover reprogramming outcomes.
Proper citation: CellRank (RRID:SCR_022827) Copy
Software tool as scalable, modular image processing pipeline for multiplexed tissue imaging. Transforms multi channel whole slide images into single cell data.
Proper citation: MCMICRO (RRID:SCR_022832) Copy
https://github.com/JonathanIrish/MEMv3
Software tool to calculate enrichment scores. Generates human and machine readable labels that quantify features enriched in sample. Used to identify multiple populations of cells and to compare each population to all of other remaining cells from original sample.
Proper citation: Marker Enrichment Modeling (RRID:SCR_022495) Copy
https://github.com/raphael-group/chisel
Software tool to infer allele and haplotype specific copy numbers in individual cells from low coverage single cell DNA sequencing data. Integrates weak allelic signals across individual cells, powering strength of single cell sequencing technologies to overcome weakness. Includes global clustering of RDRs and BAFs, and rigorous model selection procedure for inferring genome ploidy that improves both inference of allele specific and total copy numbers.
Proper citation: CHISEL (RRID:SCR_023220) Copy
https://github.com/mhammell-laboratory/TEtranscripts
Software package for including transposable elements in differential enrichment analysis of sequencing datasets. Used for including transposable elements in differential expression analysis of RNA-seq datasets. RNAseq TE quantification tool.
Proper citation: TEtranscripts (RRID:SCR_023208) Copy
http://www.t1diabetes.nih.gov/t1d-raid/index.shtml
NOTE: The T1D-RAID program is not currently accepting applications. Cooperative program that makes available, on a competitive basis, NCI resources for the pre-clinical development of drugs, natural products, and biologics to facilitate translation to the clinic of novel, scientifically meritorious therapeutic interventions for type 1 diabetes and its complications. A partial listing of those services includes: high-throughput screening, studies in animal models, formulation, pharmacology and toxicology studies, and bulk substances acquisition. Requests to T1D-RAID are brief (20 pages or less), and should clearly outline the resources required to ready the proposed therapeutic agent for clinical trials. T1D-RAID should enable entry into the clinic of promising molecules that are not otherwise likely to receive an adequate and timely clinical test. T1D-RAID is designed to accomplish the tasks that are rate-limiting in bringing discoveries from the laboratory to the clinic. Once a project has been approved, NIDDKstaff interact directly with the Principal Investigator (PI). NCI contractors perform the T1D-RAID-approved tasks under the direction of NIDDKand NCI staff. The required tasks will vary from project to project. In some cases T1D-RAID will support only one or two key missing steps necessary to bring a compound to the clinic; in other cases it may be necessary to supply the entire portfolio of development requirements needed to file an IND. Examples of tasks that can be supported by T1D-RAID include, but are not limited to: * Definition or optimization of dose and schedule for in vivo activity * Development of pharmacology assays * Conduct of pharmacology studies with a pre-determined assay * Acquisition of bulk substance (GMP and non-GMP) * Scale-up production from lab-scale to clinical-trials lot scale * Development of suitable formulations * Development of analytical methods for bulk substances * Production of dosage forms * Stability assurance of dosage forms * Range-finding initial toxicology * IND-directed toxicology, with correlative pharmacology and histopathology * Planning of clinical trials * Regulatory affairs, so that FDA requirements are likely to be satisfied by participating investigators seeking to test new molecular entities in the clinic * IND filing advice The output of T1D-RAID activities will be both products and information that will be made fully available to the originating investigator for support of an IND application and clinical trials. T1D-RAID does not sponsor clinical trials.
Proper citation: Type 1 Diabetes - Rapid Access to Intervention Development (RRID:SCR_000203) Copy
https://www.roswellpark.edu/shared-resources/gene-targeting-and-transgenic
Facility which provides researchers with transgenic mouse technologies, methods, and animal models. Knockout mice, transgenic mice, and mice on multiple strain backgrounds are provided.
Proper citation: RPCI Gene Targeting and Transgenic Shared Resource (RRID:SCR_001020) Copy
http://www.broad.mit.edu/mpr/lung
Data set of a molecular taxonomy of lung carcinoma, the leading cause of cancer death in the United States and worldwide. Using oligonucleotide microarrays, researchers analyzed mRNA expression levels corresponding to 12,600 transcript sequences in 186 lung tumor samples, including 139 adenocarcinomas resected from the lung. Hierarchical and probabilistic clustering of expression data defined distinct sub-classes of lung adenocarcinoma. Among these were tumors with high relative expression of neuroendocrine genes and of type II pneumocyte genes, respectively. Retrospective analysis revealed a less favorable outcome for the adenocarcinomas with neuroendocrine gene expression. The diagnostic potential of expression profiling is emphasized by its ability to discriminate primary lung adenocarcinomas from metastases of extra-pulmonary origin. These results suggest that integration of expression profile data with clinical parameters could aid in diagnosis of lung cancer patients.
Proper citation: Classification of Human Lung Carcinomas by mRNA Expression Profiling Reveals Distinct Adenocarcinoma Sub-classes (RRID:SCR_003010) Copy
http://www.census.gov/did/www/nlms/
A database based on a random sample of the noninstitutionalized population of the United States, developed for the purpose of studying the effects of demographic and socio-economic characteristics on differentials in mortality rates. It consists of data from 26 U.S. Current Population Surveys (CPS) cohorts, annual Social and Economic Supplements, and the 1980 Census cohort, combined with death certificate information to identify mortality status and cause of death covering the time interval, 1979 to 1998. The Current Population Surveys are March Supplements selected from the time period from March 1973 to March 1998. The NLMS routinely links geographical and demographic information from Census Bureau surveys and censuses to the NLMS database, and other available sources upon request. The Census Bureau and CMS have approved the linkage protocol and data acquisition is currently underway. The plan for the NLMS is to link information on mortality to the NLMS every two years from 1998 through 2006 with research on the resulting database to continue, at least, through 2009. The NLMS will continue to incorporate data from the yearly Annual Social and Economic Supplement into the study as the data become available. Based on the expected size of the Annual Social and Economic Supplements to be conducted, the expected number of deaths to be added to the NLMS through the updating process will increase the mortality content of the study to nearly 500,000 cases out of a total number of approximately 3.3 million records. This effort would also include expanding the NLMS population base by incorporating new March Supplement Current Population Survey data into the study as they become available. Linkages to the SEER and CMS datasets are also available. Data Availability: Due to the confidential nature of the data used in the NLMS, the public use dataset consists of a reduced number of CPS cohorts with a fixed follow-up period of five years. NIA does not make the data available directly. Research access to the entire NLMS database can be obtained through the NIA program contact listed. Interested investigators should email the NIA contact and send in a one page prospectus of the proposed project. NIA will approve projects based on their relevance to NIA/BSR''s areas of emphasis. Approved projects are then assigned to NLMS statisticians at the Census Bureau who work directly with the researcher to interface with the database. A modified version of the public use data files is available also through the Census restricted Data Centers. However, since the database is quite complex, many investigators have found that the most efficient way to access it is through the Census programmers. * Dates of Study: 1973-2009 * Study Features: Longitudinal * Sample Size: ~3.3 Million Link: *ICPSR: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/00134
Proper citation: National Longitudinal Mortality Study (RRID:SCR_008946) Copy
https://www.moffitt.org/research-science/shared-resources/tissue/
Biorepository resource with mission of proper collection, handling, processing and storage of irreplaceable biological specimens to support spectrum of related basic science, translational and clinical research. Provides expertise in nucleic acid extractions, quantification, aliquoting and quality assurance; liquid specimen centrifugation, processing and aliquoting; histological tissue processing, immunohistochemistry and tissue microarray microtomy; pathologist consultation services. Tissue Core operations are divided into four distinct pillars of service that work collaboratively to ensure specimen quality is maintained from procurement to preservation.
Proper citation: Moffitt Cancer Center Tissue Core Facility (RRID:SCR_012364) Copy
https://www.mskcc.org/research/ski/core-facilities/monoclonal-antibody-core-facility
ABCF can provide MAbs from established hybridomas for RESEARCH PURPOSES ONLY, can assist in generating MAbs, offers a weekly mycoplasmal contamination screening service for tissue culture samples, distributes cell lines developed at Memorial Sloan Kettering Cancer Center and Rockefeller University.
Proper citation: Memorial Sloan Kettering Cancer Center Antibody and Bioresource Core Facility (RRID:SCR_017691) Copy
Core mass spec and proteomic services include open access lab for trained users with GC/MS, LC/MS, high resolution LC/MS, and MALDI-TOF instruments, help with intact protein analysis, targeted quantitation, drug discovery support, pathway analysis, protein interactions, FFPE tissue analysis, both labeled and label-free proteomics, and more. Please contact SUMS to discuss these and other custom projects including new application development.
Proper citation: Stanford University Vincent Coates Foundation Mass Spectrometry Laboratory Core Facility (RRID:SCR_017801) Copy
http://rhlccflow.facilities.northwestern.edu
Provides 6 cell sorters and 5 benchtop analyzers. Helps investigators to define their projects in the early stages of development to make optimal and efficient use of flow cytometry. Educates ALL users (faculty and staff) in the science and technology of flow cytometry.
Proper citation: Northwestern University Cancer Center Flow Cytometry Core Facility (RRID:SCR_017766) Copy
http://cancer.northwestern.edu/research/shared-resources/pathology-core-facility.html
Centralized, comprehensive, core laboratory providing histology, immunohistochemistry, molecular analysis and extraction and microscopic evaluation services for human tissue-based studies. Serves integral marker studies that require biomarker-based treatment arm assignment. Performs procurement of fresh biospecimens for clinical trials and biobanking.
Proper citation: Northwestern University School of Medicine Lurie Cancer Center Pathology Core Facility (RRID:SCR_017769) Copy
http://www.med.unc.edu/csb/sbi
Core provides consultations and collaborations on research studies requiring computational structural biology methods. Analyses available are to study of static structures, molecular dynamics studies for analyzing contribution of dynamic and collective motions to macromolecular functionality. Trains researchers in computational structural biology techniques, or works in collaborative manner with researchers.Provides access to software tools for protein and DNA sequence analysis, protein fold determination, homology modeling, active site identification, and analysis of effects of various mutations on structure and function of protein, along with additional computational analyses.
Proper citation: North Carolina University at Chapel Hill R.L. Juliano Structural Bioinformatics Core Facility (RRID:SCR_017836) Copy
https://www.med.unc.edu/csb/nmr/
Core to support academic and industrial users. Spectrometer time is available to trained users for an hourly fee. Lab manager trains new users, consults to determine whether NMR will be useful in their research, and helps design experimental plan to obtain information they need. Manager also operates spectrometer for users whose experiments do not justify time and expense of individual training.
Proper citation: North Carolina University at Chapel Hill School of Medicine Biomolecular NMR Laboratory Core Facility (RRID:SCR_017841) Copy
http://www.med.unc.edu/csb/pep
Core specializes in production of pure, functional proteins for structural, biophysical, and biochemical studies. Facility offers three categories of service:Protein Expression,Protein Purification,Scientific Consultation, Mentoring, and Training; Offers Isotope labeled proteins for NMR;High production scales for immunizations, drug discovery, structural biology;Endotoxin-free protein production;Stable cell line generation;Expert baculovirus expression;Custom packages to efficiently suit your needs.
Proper citation: North Carolina University at Chapel Hill School of Medicine Protein Expression and Purification Core Facility (RRID:SCR_017843) Copy
Can't find your Tool?
We recommend that you click next to the search bar to check some helpful tips on searches and refine your search firstly. Alternatively, please register your tool with the SciCrunch Registry by adding a little information to a web form, logging in will enable users to create a provisional RRID, but it not required to submit.
Welcome to the dkNET Resources search. From here you can search through a compilation of resources used by dkNET and see how data is organized within our community.
You are currently on the Community Resources tab looking through categories and sources that dkNET has compiled. You can navigate through those categories from here or change to a different tab to execute your search through. Each tab gives a different perspective on data.
If you have an account on dkNET then you can log in from here to get additional features in dkNET such as Collections, Saved Searches, and managing Resources.
Here is the search term that is being executed, you can type in anything you want to search for. Some tips to help searching:
You can save any searches you perform for quick access to later from here.
We recognized your search term and included synonyms and inferred terms along side your term to help get the data you are looking for.
If you are logged into dkNET you can add data records to your collections to create custom spreadsheets across multiple sources of data.
Here are the sources that were queried against in your search that you can investigate further.
Here are the categories present within dkNET that you can filter your data on
Here are the subcategories present within this category that you can filter your data on
If you have any further questions please check out our FAQs Page to ask questions and see our tutorials. Click this button to view this tutorial again.