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 81 showing 1601 ~ 1620 out of 1,647 results
Snippet view Table view Download Top 1000 Results
Click the to add this resource to a Collection
  • RRID:SCR_019030

    This resource has 1+ mentions.

http://pyntacle.css-mendel.it/

Software Python package and command line tool for graphs analysis. Used to search for important components of graphs. Implements and provides ancillary methods for community finding, set operations between graphs, and quick data type conversion tools.

Proper citation: Pyntacle (RRID:SCR_019030) Copy   


  • RRID:SCR_018796

    This resource has 1+ mentions.

https://github.com/BackofenLab/StoatyDive

Software tool to evaluate and classify predicted peak profiles to assess binding specificity of protein to its targets. Can be used for sequencing data such as CLIP-seq or ChIP-Seq, or any other type of peak profile data.

Proper citation: StoatyDive (RRID:SCR_018796) Copy   


  • RRID:SCR_018963

    This resource has 1+ mentions.

http://www.imgt.org/StatClonotype/

Software tool to evaluate and visualize statistical significance of pairwise comparisons of IMGT clonotype (AA) diversity or expression, per variable,diversity, and joining gene of given IG or TR group, from NGS IMGT/HighV-QUEST statistical output. Antibody clonotype analysis based on NGS sequences.

Proper citation: IMGT/StatClonotype (RRID:SCR_018963) Copy   


  • RRID:SCR_019018

    This resource has 1+ mentions.

https://github.com/auranic/ClinTrajan

Software Python package for analysis of trajectories in clinical datasets.

Proper citation: ClinTrajAn (RRID:SCR_019018) Copy   


  • RRID:SCR_018927

    This resource has 500+ mentions.

https://github.com/lh3/seqtk

Software fast and lightweight tool for processing sequences in FASTA or FASTQ format.

Proper citation: Seqtk (RRID:SCR_018927) Copy   


  • RRID:SCR_018909

    This resource has 1+ mentions.

https://github.com/sandmanns/CopyDetective

Software tool for detection threshold aware CNV calling in matched whole exome sequencing data.

Proper citation: CopyDetective (RRID:SCR_018909) Copy   


  • RRID:SCR_018904

    This resource has 1+ mentions.

https://github.com/cochran4/GEMB

Software tool to introduce gene set enrichment for mathematical biology. Measures association between disease of interest and set of genes related to biological pathway. Used for defining gene contributions based on biophysical properties, by leveraging mathematical models of biology to predict effects of genetic perturbations on particular downstream function.

Proper citation: GEMB (RRID:SCR_018904) Copy   


  • RRID:SCR_018878

    This resource has 1+ mentions.

https://github.com/HicServices/DicomTypeTranslation

Open source software tool to extract metadata from DICOM files for indexing and storage in SQL database.

Proper citation: DicomTypeTranslator (RRID:SCR_018878) Copy   


  • RRID:SCR_018880

    This resource has 1+ mentions.

https://ohlerlab.mdc-berlin.de/software/RiboTaper_126/

Software tool as analysis pipeline for ribosome profiling experiments, which exploits triplet periodicity of ribosomal footprints to call translated regions. Statistical approach that identifies translated regions on basis of characteristic three nucleotide periodicity of Ribo-seq data.

Proper citation: RiboTaper (RRID:SCR_018880) Copy   


  • RRID:SCR_019277

    This resource has 10+ mentions.

https://github.com/BNadel/GEDIT

Software tool for accurate cell type quantification from gene expression data. Uses gene expression data to estimate cell type abundances. Allows user to supply custom reference matrices.

Proper citation: GEDIT (RRID:SCR_019277) Copy   


  • RRID:SCR_019193

    This resource has 50+ mentions.

https://github.com/constantAmateur/SoupX

Software R package for estimation and removal of cell free mRNA contamination in droplet based single cell RNA-seq data.

Proper citation: SoupX (RRID:SCR_019193) Copy   


  • RRID:SCR_019238

    This resource has 10+ mentions.

https://github.com/statOmics/tradeSeq

Software tool as suite of tests for identifying dynamic temporal gene regulation using single cell RNA-seq data.Trajectory based differential expression analysis for sequencing data.

Proper citation: tradeSeq (RRID:SCR_019238) Copy   


  • RRID:SCR_019213

    This resource has 500+ mentions.

http://bioinformatics.sdstate.edu/go/

Software graphical gene set enrichment tool for animals and plants. Graphical web application to gain insights from gene sets. Features include graphical visualization of enrichment results and gene characteristics, and application program interface access to KEGG and STRING for retrieval of pathway diagrams and protein-protein interaction networks.

Proper citation: ShinyGO (RRID:SCR_019213) Copy   


  • RRID:SCR_019214

    This resource has 1000+ mentions.

https://bioconductor.org/packages/biomaRt/

Software package that integrates BioMart data resources with data analysis software in Bioconductor. Can annotate range of gene or gene product identifiers including Entrez Gene and Affymetrix probe identifiers with information such as gene symbol, chromosomal coordinates, Gene Ontology and OMIM annotation. Enables retrieval of genomic sequences and single nucleotide polymorphism information, which can be used in data analysis.

Proper citation: biomaRt (RRID:SCR_019214) Copy   


  • RRID:SCR_019058

    This resource has 1+ mentions.

https://github.com/ShaokunAn/D-EE

Software tool for distributed dimensionality reduction and visualization. Distributed software for visualizing intrinsic structure of large scale single cell data written in C language. Its distributed storage and distributed computation technique allows efficiently analyze large scale single cell data at cost of constant time speedup.

Proper citation: D-EE (RRID:SCR_019058) Copy   


  • RRID:SCR_002981

    This resource has 50+ mentions.

http://www.emouseatlas.org

Detailed multidimensional digital multimodal atlas of C57BL/6J mouse nervous system with data and informatics pipeline that can automatically register, annotate, and visualize large scale neuroanatomical and connectivity data produced in histology, neuronal tract tracing, MR imaging, and genetic labeling. MAP2.0 interoperates with commonly used publicly available databases to bring together brain architecture, gene expression, and imaging information into single, simple interface.Resource to visualise mouse development, identify anatomical structures, determine developmental stage, and investigate gene expression in mouse embryo. eMouseAtlas portal page allows access to EMA Anatomy Atlas of Mouse Development and EMAGE database of gene expression.EMAGE is freely available, curated database of gene expression patterns generated by in situ techniques in developing mouse embryo. EMA, e-Mouse Atlas, is 3-D anatomical atlas of mouse embryo development including histology and includes EMAP ontology of anatomical structure, provides information about shape, gross anatomy and detailed histological structure of mouse, and framework into which information about gene function can be mapped.

Proper citation: eMouseAtlas (RRID:SCR_002981) Copy   


  • RRID:SCR_003176

    This resource has 1+ mentions.

https://netbio.bgu.ac.il/labwebsite/software/responsenet/

WebServer that identifies high-probability signaling and regulatory paths that connect input data sets. The input includes two weighted lists of condition-related proteins and genes, such as a set of disease-associated proteins and a set of differentially expressed disease genes, and a molecular interaction network (i.e., interactome). The output is a sparse, high-probability interactome sub-network connecting the two sets that is biased toward signaling pathways. This sub-network exposes additional proteins that are potentially involved in the studied condition and their likely modes of action. Computationally, it is formulated as a minimum-cost flow optimization problem that is solved using linear programming.

Proper citation: ResponseNet (RRID:SCR_003176) Copy   


http://www.ebi.ac.uk/intenz

IntEnz (Integrated relational Enzyme database) is a freely available resource focused on enzyme nomenclature. IntEnz is created in collaboration with the Swiss Institute of Bioinformatics (SIB). This collaboration is responsible for the production of the ENZYME resource. IntEnz contains the recommendations of the Nomenclature Committee of the International Union of Biochemistry and Molecular Biology (NC-IUBMB) on the nomenclature and classification of enzyme-catalysed reactions.

Proper citation: IntEnz- Integrated relational Enzyme database (RRID:SCR_002992) Copy   


  • RRID:SCR_004749

    This resource has 1+ mentions.

http://pilgrm.princeton.edu

PILGRM (the platform for interactive learning by genomics results mining) puts advanced supervised analysis techniques applied to enormous gene expression compendia into the hands of bench biologists. This flexible system empowers its users to answer diverse biological questions that are often outside of the scope of common databases in a data-driven manner. This capability allows domain experts to quickly and easily generate hypotheses about biological processes, tissues or diseases of interest. Specifically PILGRM helps biologists generate these hypotheses by analyzing the expression levels of known relevant genes in large compendia of microarray data. PILGRM is for the biologist with a set of proteins relevant to a disease, biological function or tissue of interest who wants to find additional players in that process. It uses a data driven method that provides added value for literature search results by mining compendia of publicly available gene expression datasets using lists of relevant and irrelevant genes (standards). PILGRM produces publication quality PDFs usable as supplementary material to describe the computational approach, standards and datasets. Each PILGRM analysis starts with an important biological question (e.g. What genes are relevant for breast cancer but not mammary tissue in general?). For PILGRM to discover relevant genes, it needs examples of both genes that you would (positive) and would not (negative) find interesting. Lists of these genes are what we call standards and in PILGRM you can build your own standards or you can use standards from common sources that we pre-load for your convenience. PILGRM lets you build your own literature-documented standards so that processes, disease, and tissues that are not well covered in databases of tissue expression, disease, or function can still be used for an analysis.

Proper citation: PILGRM (RRID:SCR_004749) Copy   


  • RRID:SCR_004953

    This resource has 10+ mentions.

http://swift.cmbi.ru.nl/gv/hssp/

HSSP (homology-derived structures of proteins) is a derived database merging structural (2-D and 3-D) and sequence information (1-D). For each protein of known 3D structure from the Protein Data Bank, the database has a file with all sequence homologues, properly aligned to the PDB protein. Homologues are very likely to have the same 3D structure as the PDB protein to which they have been aligned. As a result, the database is not only a database of sequence aligned sequence families, but it is also a database of implied secondary and tertiary structures. Likely secondary structure are carried over from the PDB protein to each homologous protein. Tertiary structure models can be built by fitting the sequence of the homologue as aligned into the 3D template of the protein of known structure. Special software is needed to construct 3D models by homology, such WHATIF by Gert Vriend or MaxSprout by Liisa Holm and Chris Sander. The command rsync can be used to obtain a local copy of the HSSP. We appreciate receiving an Email from people who do so, but there are no strings attached. Everybody can freely download the files, academia and industry alike. If your institute''s firewall doesn''t allow you to use the (preferred) rsync way of obtaining HSSP files, feel free to work with FTP. The files are in that case available from: ftp://ftp.cmbi.ru.nl//pub/molbio/data/hssp/

Proper citation: HSSP (RRID:SCR_004953) 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