Searching the RRID Resource Information Network

Our searching services are busy right now. Please try again later

  • Register
X
Forgot Password

If you have forgotten your password you can enter your email here and get a temporary password sent to your email.

X

Leaving Community

Are you sure you want to leave this community? Leaving the community will revoke any permissions you have been granted in this community.

No
Yes

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.

Search

Type in a keyword to search

On page 3 showing 41 ~ 60 out of 455 results
Snippet view Table view Download 455 Result(s)
Click the to add this resource to a Collection
  • RRID:SCR_010236

    This resource has 1000+ mentions.

http://weblogo.berkeley.edu

Web application to generate sequence logos, graphical representations of patterns within multiple sequence alignment. Designed to make generation of sequence logos easy. Sequence logo generator.

Proper citation: WEBLOGO (RRID:SCR_010236) Copy   


  • RRID:SCR_010881

    This resource has 5000+ mentions.

http://homer.ucsd.edu/

Software tools for Motif Discovery and next-gen sequencing analysis. Used for analyzing ChIP-Seq, GRO-Seq, RNA-Seq, DNase-Seq, Hi-C and numerous other types of functional genomics sequencing data sets. Collection of command line programs for unix style operating systems written in Perl and C++.

Proper citation: HOMER (RRID:SCR_010881) Copy   


http://www.zebrafinchatlas.org

Expression atlas of in situ hybridization images from large collection of genes expressed in brain of adult male zebra finches. Goal of ZEBrA project is to develop publicly available on-line digital atlas that documents expression of large collection of genes within brain of adult male zebra finches.

Proper citation: Zebra Finch Expression Brain Atlas (RRID:SCR_012988) Copy   


https://omictools.com/l2l-tool

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 August 26, 2019.

Database of published microarray gene expression data, and a software tool for comparing that published data to a user''''s own microarray results. It is very simple to use - all you need is a web browser and a list of the probes that went up or down in your experiment. If you find L2L useful please consider contributing your published data to the L2L Microarray Database in the form of list files. L2L finds true biological patterns in gene expression data by systematically comparing your own list of genes to lists of genes that have been experimentally determined to be co-expressed in response to a particular stimulus - in other words, published lists of microarray results. The patterns it finds can point to the underlying disease process or affected molecular function that actually generated the observed changed in gene expression. Its insights are far more systematic than critical gene analyses, and more biologically relevant than pure Gene Ontology-based analyses. The publications included in the L2L MDB initially reflected topics thought to be related to Cockayne syndrome: aging, cancer, and DNA damage. Since then, the scope of the publications included has expanded considerably, to include chromatin structure, immune and inflammatory mediators, the hypoxic response, adipogenesis, growth factors, hormones, cell cycle regulators, and others. Despite the parochial origins of the database, the wide range of topics covered will make L2L of general interest to any investigator using microarrays to study human biology. In addition to the L2L Microarray Database, L2L contains three sets of lists derived from Gene Ontology categories: Biological Process, Cellular Component, and Molecular Function. As with the L2L MDB, each GO sub-category is represented by a text file that contains annotation information and a list of the HUGO symbols of the genes assigned to that sub-category or any of its descendants. You don''''t need to download L2L to use it to analyze your microarray data. There is an easy-to-use web-based analysis tool, and you have the option of downloading your results so you can view them at any time on your own computer, using any web browser. However, if you prefer, the entire L2L project, and all of its components, can be downloaded from the download page. Platform: Online tool, Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: L2L Microarray Analysis Tool (RRID:SCR_013440) Copy   


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

A repository of schizophrenia neuroimaging data collected from over 450 individuals with schizophrenia, healthy controls and their respective siblings, most with 2-year longitudinal follow-up. The data include neuroimaging data, cognitive data, clinical data, and genetic data.

Proper citation: Northwestern University Schizophrenia Data and Software Tool (NUSDAST) (RRID:SCR_014153) Copy   


  • RRID:SCR_014226

    This resource has 5000+ mentions.

http://molprobity.biochem.duke.edu

A structure-validation web application which provides an expert-system consultation about the accuracy of a macromolecular structure model, diagnosing local problems and enabling their correction. MolProbity works best as an active validation tool (used as soon as a model is available and during each rebuild/refine loop) and when used for protein and RNA crystal structures, but it may also work well for DNA, ligands and NMR ensembles. It produces coordinates, graphics, and numerical evaluations that integrate with either manual or automated use in systems such as PHENIX, KiNG, or Coot.

Proper citation: MolProbity (RRID:SCR_014226) Copy   


  • RRID:SCR_014627

    This resource has 1000+ mentions.

http://zhanglab.ccmb.med.umich.edu/I-TASSER/

Web server as integrated platform for automated protein structure and function prediction. Used for protein 3D structure prediction. Resource for automated protein structure prediction and structure-based function annotation.

Proper citation: I-TASSER (RRID:SCR_014627) Copy   


  • RRID:SCR_014827

    This resource has 50+ mentions.

http://nmrbox.org

Computing platform for biomolecular NMR available to not-for-profit or government users. It consists of a virtual machine (VM) provisioned with dozens of widely-used NMR software packages, and is available as a cloud-based Platform-as-a-Service (PaaS) or as a downloadable VM for local execution.

Proper citation: NMRbox (RRID:SCR_014827) Copy   


  • RRID:SCR_015699

    This resource has 1+ mentions.

http://www.genepattern-notebook.org/

Interactive analysis notebook environment that streamlines genomics research by interleaving text, multimedia, and executable code into unified, sharable, reproducible “research narratives.” It integrates the dynamic capabilities of notebook systems with an investigator-focused, simple interface that provides access to hundreds of genomic tools without the need to write code.

Proper citation: GenePattern Notebook (RRID:SCR_015699) Copy   


  • RRID:SCR_015530

    This resource has 10000+ mentions.

http://ccb.jhu.edu/software/hisat2/index.shtml

Graph-based alignment of next generation sequencing reads to a population of genomes.

Proper citation: HISAT2 (RRID:SCR_015530) Copy   


  • RRID:SCR_002388

    This resource has 100+ mentions.

http://www.genenetwork.org/

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   


  • RRID:SCR_002681

    This resource has 10+ mentions.

https://simtk.org/home/contrack

An algorithm for identifying pathways that are known to exist between two regions within DTI data of anisotropic tissue, e.g., muscle, brain, spinal cord. The ConTrack algorithms use knowledge of DTI scanning physics and apriori information about tissue architecture to identify the location of connections between two regions within the DTI data. Assuming a course of connection or pathway between these two regions is known to exist within the measured tissue, ConTrack can be used to estimate properties of these connections in-vivo.

Proper citation: ConTrack (RRID:SCR_002681) Copy   


  • RRID:SCR_002689

    This resource has 1000+ mentions.

http://www.pharmgkb.org/

Database and central repository for genetic, genomic, molecular and cellular phenotype data and clinical information about people who have participated in pharmacogenomics research studies. The data includes, but is not limited to, clinical and basic pharmacokinetic and pharmacogenomic research in the cardiovascular, pulmonary, cancer, pathways, metabolic and transporter domains. PharmGKB welcomes submissions of primary data from all research into genes and genetic variation and their effects on drug and disease phenotypes. PharmGKB collects, encodes, and disseminates knowledge about the impact of human genetic variations on drug response. They curate primary genotype and phenotype data, annotate gene variants and gene-drug-disease relationships via literature review, and summarize important PGx genes and drug pathways. PharmGKB is part of the NIH Pharmacogenomics Research Network (PGRN), a nationwide collaborative research consortium. Its aim is to aid researchers in understanding how genetic variation among individuals contributes to differences in reactions to drugs. A selected subset of data from PharmGKB is accessible via a SOAP interface. Downloaded data is available for individual research purposes only. Drugs with pharmacogenomic information in the context of FDA-approved drug labels are cataloged and drugs with mounting pharmacogenomic evidence are listed.

Proper citation: PharmGKB (RRID:SCR_002689) Copy   


  • RRID:SCR_002792

    This resource has 1+ mentions.

http://diseasome.eu

A disease / disorder relationships explorer and a sample of a map-oriented scientific work. It uses the Human Disease Network dataset and allows intuitive knowledge discovery by mapping its complexity. The Human Disease Network (official) dataset, a poster of the data and related book (Biology - The digital era, ISBN: 978-2-271-06779-1) are available. This kind of data has a network-like organization, and relations between elements are at least as important as the elements themselves. More data could be integrated to this prototype and could eventually bring closer phenotype and genotype. Results should be visual, but also printable. Creating posters can enhance collaborative work. It facilitates discussion and sharing of ideas about the data. This website initiative is an invitation to think about the benefits of networks exploration but above all it tries to outline future designs of scientific information systems.

Proper citation: Diseasome (RRID:SCR_002792) Copy   


http://insitu.fruitfly.org/cgi-bin/ex/insitu.pl

Database of embryonic expression patterns using a high throughput RNA in situ hybridization of the protein-coding genes identified in the Drosophila melanogaster genome with images and controlled vocabulary annotations. At the end of production pipeline gene expression patterns are documented by taking a large number of digital images of individual embryos. The quality and identity of the captured image data are verified by independently derived microarray time-course analysis of gene expression using Affymetrix GeneChip technology. Gene expression patterns are annotated with controlled vocabulary for developmental anatomy of Drosophila embryogenesis. Image, microarray and annotation data are stored in a modified version of Gene Ontology database and the entire dataset is available on the web in browsable and searchable form or MySQL dump can be downloaded. So far, they have examined expression of 7507 genes and documented them with 111184 digital photographs.

Proper citation: Patterns of Gene Expression in Drosophila Embryogenesis (RRID:SCR_002868) Copy   


  • RRID:SCR_021946

    This resource has 500+ mentions.

https://github.com/sqjin/CellChat

Software R toolkit for inference, visualization and analysis of cell-cell communication from single cell data.Quantitatively infers and analyzes intercellular communication networks from single-cell RNA-sequencing data. Predicts major signaling inputs and outputs for cells and how those cells and signals coordinate for functions using network analysis and pattern recognition approaches. Classifies signaling pathways and delineates conserved and context specific pathways across different datasets.

Proper citation: CellChat (RRID:SCR_021946) Copy   


  • RRID:SCR_023080

    This resource has 1+ mentions.

https://github.com/plaisier-lab/sygnal

Software pipeline to integrate correlative, causal and mechanistic inference approaches into unified framework that systematically infers causal flow of information from mutations to TFs and miRNAs to perturbed gene expression patterns across patients. Used to decipher transcriptional regulatory networks from multi-omic and clinical patient data. Applicable for integrating genomic and transcriptomic measurements from human cohorts.

Proper citation: SYGNAL (RRID:SCR_023080) Copy   


  • RRID:SCR_023150

    This resource has 10+ mentions.

https://github.com/virajbdeshpande/AmpliconArchitect

Software package designed to call circular DNA from short read WGS data.Used to identify one or more connected genomic regions which have simultaneous copy number amplification and elucidates architecture of amplicon.Used to reconstruct structure of focally amplified regions using whole genome sequencing and validate it extensively on multiple simulated and real datasets, across wide range of coverage and copy numbers.

Proper citation: AmpliconArchitect (RRID:SCR_023150) Copy   


  • RRID:SCR_024891

    This resource has 1+ mentions.

https://github.com/bioinform/somaticseq

Software accurate somatic mutation detection pipeline implementing stochastic boosting algorithm to produce somatic mutation calls for both single nucleotide variants and small insertions and deletions. NGS variant calling and classification.

Proper citation: SomaticSeq (RRID:SCR_024891) Copy   


https://github.com/xinhe-lab/GSFA

Software R package that performs sparse factor analysis and differential gene expression discovery simultaneously on single cell CRISPR screening data.

Proper citation: Guided Sparse Factor Analysis (RRID:SCR_025023) 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.

Can't find the RRID you're searching for? X
  1. RRID Portal Resources

    Welcome to the RRID Resources search. From here you can search through a compilation of resources used by RRID and see how data is organized within our community.

  2. Navigation

    You are currently on the Community Resources tab looking through categories and sources that RRID 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.

  3. Logging in and Registering

    If you have an account on RRID then you can log in from here to get additional features in RRID such as Collections, Saved Searches, and managing Resources.

  4. Searching

    Here is the search term that is being executed, you can type in anything you want to search for. Some tips to help searching:

    1. Use quotes around phrases you want to match exactly
    2. You can manually AND and OR terms to change how we search between words
    3. You can add "-" to terms to make sure no results return with that term in them (ex. Cerebellum -CA1)
    4. You can add "+" to terms to require they be in the data
    5. Using autocomplete specifies which branch of our semantics you with to search and can help refine your search
  5. Save Your Search

    You can save any searches you perform for quick access to later from here.

  6. Query Expansion

    We recognized your search term and included synonyms and inferred terms along side your term to help get the data you are looking for.

  7. Collections

    If you are logged into RRID you can add data records to your collections to create custom spreadsheets across multiple sources of data.

  8. Sources

    Here are the sources that were queried against in your search that you can investigate further.

  9. Categories

    Here are the categories present within RRID that you can filter your data on

  10. Subcategories

    Here are the subcategories present within this category that you can filter your data on

  11. Further Questions

    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.

X