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 67 showing 1321 ~ 1340 out of 2,279 results
Snippet view Table view Download Top 1000 Results
Click the to add this resource to a Collection
  • RRID:SCR_005439

    This resource has 50+ mentions.

http://epigenome.usc.edu/publicationdata/bissnp2011/

A software package based on the Genome Analysis Toolkit (GATK) map-reduce framework for genotyping and accurate DNA methylation calling in bisulfite treated massively parallel sequencing (Bisulfite-seq, NOMe-seq, RRBS and any other bisulfite treated sequencing) with Illumina directional library protocol. It contains the following key features: * Call and summarize methylation of any cytosine context provided (CpG, CHH, CHG, GCH et.al.); * Work for single end and paired-end data; * Accurtae variant detection. Enable base quality recalibration and indel calling in bisulfite sequencing; * Based on Java map-reduce framework, allow multi-thread computing. Cross-platform; * Allow multiple output format, detailed VCF files, CpG haplotype reads file for mono-allelic methylation analysis, simplified bedGraph, wig and bed format for visualization in UCSC genome broswer and IGV browser. BisSNP uses bayesian inference with locus specific methylation probabilities and bisulfite conversion rate of different cytosine context(not only CpG, CHH, CHG in Bisulfite-seq, but also GCH et.al. in other bisulfite treated sequencing) to determine genotypes and methylation levels simultaneously., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Bis-SNP (RRID:SCR_005439) Copy   


  • RRID:SCR_005473

    This resource has 10+ mentions.

http://code.google.com/p/distmap/

A user-friendly software pipeline designed to map short reads in a MapReduce framework on a local Hadoop cluster. It is designed to be easily implemented by researchers who do not have expert knowledge of bioinformatics. As it does not have any dependencies, it provides full flexibility and control to the user. The user can use any version of a compatible mapper and any reference genome assembly. There is no need to maintain the mapper, reference or DistMap source code on each of the slaves (nodes) in the Hadoop cluster, making maintenance extremely easy.

Proper citation: DistMap (RRID:SCR_005473) Copy   


  • RRID:SCR_005504

    This resource has 100+ mentions.

http://www.well.ox.ac.uk/project-stampy

A software package for the mapping of short reads from illumina sequencing machines onto a reference genome. It''s recommended for most workflows, including those for genomic resequencing, RNA-Seq and Chip-seq. Stampy excels in the mapping of reads containing that contain sequence variation relative to the reference, in particular for those containing insertions or deletions. It can map reads from a highly divergent species to a reference genome for instance. Stampy achieves high sensitivity and speed by using a fast hashing algorithm and a detailed statistical model. Stampy has the following features: * Maps single, paired-end and mate pair Illumina reads to a reference genome * Fast: about 20 Gbase per hour in hybrid mode (using BWA) * Low memory footprint: 2.7 Gb shared memory for a 3Gbase genome * High sensitivity for indels and divergent reads, up to 10-15% * Low mapping bias for reads with SNPs * Well calibrated mapping quality scores * Input: Fastq and Fasta; gzipped or plain * Output: SAM, Maq''s map file * Optionally calculates per-base alignment posteriors * Optionally processes part of the input * Handles reads of up to 4500 bases

Proper citation: Stampy (RRID:SCR_005504) Copy   


http://snap.cs.berkeley.edu/

A sequence aligner software program that is 10-100x faster and simultaneously more accurate than existing tools like BWA, Bowtie2 and SOAP2. It runs on commodity x86 processors, and supports a rich error model that lets it cheaply match reads with more differences from the reference than other tools. This gives SNAP up to 2x lower error rates than existing tools and lets it match larger mutations that they may miss. SNAP also natively reads BAM, FASTQ, or gzipped FASTQ, and natively writes SAM or BAM, with built-in sorting, duplicate marking, and BAM indexing.

Proper citation: Scalable Nucleotide Alignment Program (RRID:SCR_005501) Copy   


  • RRID:SCR_018146

    This resource has 1+ mentions.

https://laniakea-elixir-it.github.io/

Software tool for automatic deployment of virtual Galaxy environments for life science. Can be deployed over common cloud architectures supported both by public and private e-infrastructures. User interacts with Laniakea based service through simple front end that allows general setup of Galaxy instance, then Laniakea takes care of automatic deployment of virtual hardware and software components. User gains access with full administrative privileges to private, production grade, fully customized, Galaxy virtual instance, and to underlying virtual machine.

Proper citation: Laniakea (RRID:SCR_018146) Copy   


  • RRID:SCR_007026

    This resource has 100+ mentions.

http://scansite.mit.edu/

Scansite searches for motifs within proteins that are likely to be phosphorylated by specific protein kinases or bind to domains such as SH2 domains, 14-3-3 domains or PDZ domains. The Motifscanner program utilizes an entropy approach that assesses the probability of a site matching the motif using the selectivity values and sums the logs of the probability values for each amino acid in the candidate sequence. The program then indicates the percentile ranking of the candidate motif in respect to all potential motifs in proteins of a protein database. When available, percentile scores of some confirmed phosphorylation sites for the kinase of interests or confirmed binding sites of the domain of interest are provided for comparison with the scores of the candidate motifs.

Proper citation: Scansite (RRID:SCR_007026) Copy   


http://www.iiserpune.ac.in/~coee/histome/

Database of human histone variants, sites of their post-translational modifications and various histone modifying enzymes. The database covers 5 types of histones, 8 types of their post-translational modifications and 13 classes of modifying enzymes. Many data fields are hyperlinked to other databases (e.g. UnprotKB/Swiss-Prot, HGNC, OMIM, Unigene etc.). Additionally, this database also provides sequences of promoter regions (-700 TSS +300) for all gene entries. These sequences were extracted from the UCSC genome browser. Sites of post-translational modifications of histones were manually searched from PubMed listed literature. Current version contains information for about ~50 histone proteins and ~150 histone modifying enzymes. HIstome is a combined effort of researchers from two institutions, Advanced Center for Treatment, Research and Education in Cancer (ACTREC), Navi Mumbai and Center of Excellence in Epigenetics (CoEE), Indian Institute of Science Education and Research (IISER), Pune.

Proper citation: HIstome: The Histone Infobase (RRID:SCR_006972) Copy   


http://microkit.biocuckoo.org/

MiCroKit database is the first integrative resource to pin point most of identified components and related scientific information of midbody, centrosome and kinetochore. In this work, we have collected all proteins identified to be localized on kinetochore, centrosome, and/or midbody from two fungi (S. cerevisiae and S. pombe) and five animals, including C. elegans, D. melanogaster, X. laevis, M. musculus and H. sapiens. From the related literature of PubMed, numerous proteins have been manually curated to be localized on at least one of the sub-cellular localizations of kinetochore, centrosome and midbody. And to promise the quality of data, based on the rationale of Seeing is believing (Bloom K et al., 2005), these proteins have been unambiguously observed under fluorescent microscope as directly supportive evidences. Then an integrated and searchable database MiCroKit - Midbody, Centrosome and Kinetochore has been established. The version 1.0 of MiCroKit database was set up on Nov. 2nd, 2005, containing 1,065 unique proteins. The MiCroKit version 2.0 was released on Jun. 5th, 2006, with 1,120 entries. Currently, the MiCroKit 3.0 database was updated on July 9, 2009, containing 1,489 unique protein entries. The online service of MiCroKit 3.0 was implemented in PHP + MySQL + JavaScript. And the local packages of MiCroKit 3.0 were developed in JAVA 1.5 (J2SE). The database will be updated routinely as new microkit proteins are reported.

Proper citation: Midbody, Centrosome and Kinetochore (RRID:SCR_007052) Copy   


  • RRID:SCR_006917

    This resource has 1000+ mentions.

http://www.biocarta.com/

BioCarta Pathways allows users to observe how genes interact in dynamic graphical models. Online maps available within this resource depict molecular relationships from areas of active research. In an open source approach, this community-fed forum constantly integrates emerging proteomic information from the scientific community. It also catalogs and summarizes important resources providing information for over 120,000 genes from multiple species. Find both classical pathways as well as current suggestions for new pathways.

Proper citation: BioCarta Pathways (RRID:SCR_006917) Copy   


  • RRID:SCR_006931

    This resource has 10+ mentions.

http://www.imgt.org/IMGTindex/LIGM.html

IMGT/LIGM-DB is a comprehensive database of immunoglobulin (IG) and T cell receptor (TR) nucleotide sequences from human and other vertebrate species (270). IMGT/LIGM-DB includes all germline (non-rearranged) and rearranged IG and TR genomic DNA (gDNA) and complementary DNA (cDNA) sequences published in generalist databases. IMGT/LIGM-DB allows searches from the Web interface according to biological and immunogenetic criteria through five distinct modules depending on the user interest. Users can search the catalogue by accession number, mnemonic, definition, creation date, length, or annotation level. They also have the option to search through taxonomic classification, keywords, and annotated labels. For a given entry, nine types of display are available including the IMGT flat file, the translation of the coding regions and the analysis by the IMGT/V-QUEST tool (see parent org. below). IMGT/LIGM-DB distributes expertly annotated sequences. The annotations hugely enhance the quality and the accuracy of the distributed detailed information. They include the sequence identification, the gene and allele classification, the constitutive and specific motif description, the codon and amino acid numbering, and the sequence obtaining information, according to the main concepts of IMGT-ONTOLOGY. They represent the main source of IG and TR gene and allele knowledge stored in IMGT/GENE-DB and in the IMGT reference directory., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: IMGT/LIGM-DB (RRID:SCR_006931) Copy   


http://datf.cbi.pku.edu.cn/

Database that collects all arabidopsis transcription factors (totally 1922 Loci; 2290 Gene Models) and classifies them into 64 families. It uses not only locus (gene), but also gene model (transcript, protein) and the detail information is for each gene model not for locus. It adds multiple alignment of the DNA-binding domain of each family, Neighbor-Joining phylogenetic tree of each family, the GO annotation, homolog with the Database of Rice Transcription Factors (DRTF). It also keeps old information items such as the unique cloned and sequenced information of about 1200 transcription factors, protein domains, 3D structure information with BLAST hits against PDB, predicted Nuclear Location Signals, UniGene information, as well as links to literature reference.

Proper citation: Database of Arabidopsis Transcription Factors (RRID:SCR_007101) Copy   


  • RRID:SCR_006962

    This resource has 1+ mentions.

http://www.polygenicpathways.co.uk

Database of disease genes and risk factors and of host pathogen/interactomes. Lists genes, pathways and environmental risk factors positively associated with diseases and conditions such as Alzheimer's disease, schizophrenia, multiple sclerosis, childhood obesity, anorexia nervosa, HIV-1/AIDS, and helicobacter pylori. Details of polymorphisms as well as negative/positive association data can be found via Useful links. Throughout the site are links to Entrez Gene and Pubmed.

Proper citation: Polygenic Pathways (RRID:SCR_006962) Copy   


  • RRID:SCR_006796

    This resource has 1000+ mentions.

http://www.broadinstitute.org/mammals/haploreg/haploreg.php

HaploReg is a tool for exploring annotations of the noncoding genome at variants on haplotype blocks, such as candidate regulatory SNPs at disease-associated loci. Using linkage disequilibrium (LD) information from the 1000 Genomes Project, linked SNPs and small indels can be visualized along with their predicted chromatin state in nine cell types, conservation across mammals, and their effect on regulatory motifs. HaploReg is designed for researchers developing mechanistic hypotheses of the impact of non-coding variants on clinical phenotypes and normal variation.

Proper citation: HaploReg (RRID:SCR_006796) Copy   


http://urgv.evry.inra.fr/CATdb

CATdb collects together all the information on transcriptome experiments done at URGV with CATMA micro arrays. All data in CATdb come from the URGV micro array platforms. Common procedures are used including any steps from the experiment design to the statistical analyses. Directed through a WEB interface, biologists enter the standard description of each experimental step (extraction, labelling, hybridization and scanning). Then, normalization and statistical analyses are done following a set of selected methods depending on the experimental design and array types.

Proper citation: CATdb: a Complete Arabidopsis Transcriptome database (RRID:SCR_007582) Copy   


http://www.allelefrequencies.net

The main purpose of the allelefrequencies.net website is to provide one central source, freely available to all. For the storage of allele frequencies from different polymorphic areas in the HUMAN genome. Users can contribute the results of their work into one common database, and can perform database searches on information already available. They have currently collected data in allele, haplotype and genotype format. The success of this website will depend on you to contribute your data. Sponsors: This resource is supported Royal Liverpool University. Keywords: Allele, Polymorphic, Genome, Database, Data, Haplotype, Genotype,

Proper citation: Allele Frequencies in Worldwide Populations (RRID:SCR_007259) Copy   


  • RRID:SCR_007666

    This resource has 1+ mentions.

http://fullmal.hgc.jp/

Full-Length cDNA Database is a resource for cDNA libraries of arhtropods and parasites. The arthropod species covered are Anopheles stephensi, Glossina morsitans (Tsetse fly), and Dermatophagoides farinae (House dust mite), while the parasitic species included are Plasmodium falciparum (Malaria), Toxoplasma gondii, Cryptosporidium parvum, Babesia bovis (Babesia), and Echinococcus multilocularis. A specialized database of each species is available as a link from the home page. This database has been constructed and maintained since 2001 by a Grant-in-Aid for Publication of Scientific Research Results from the Japan Society for the Promotion of Science. Anopheles stephensi, Glossina morsitans, Tsetse fly, Dermatophagoides farinae, House dust mite, Plasmodium falciparum, Malaria, Toxoplasma gondii, Cryptosporidium parvum, Babesia bovis, Babesia, Echinococcus multilocularis, cDNA, cDNA library, arthropod genome, parasite genome

Proper citation: Full-Length cDNA Database (RRID:SCR_007666) Copy   


http://cegg.unige.ch/mirortho

It contains predictions of precursor miRNA genes covering several animal genomes combining orthology and a Support Vector Machine. We provide homology extended alignments of already known miRBase families and putative miRNA families exclusively predicted by our SVM and orthology pipeline. The current release of miROrtho covers 46 animal genomes. We provide homology extended alignments of already known miRBase families and putative miRNA families exclusively predicted by our SVM and orthology pipeline.

Proper citation: miROrtho: the catalogue of animal microRNA genes (RRID:SCR_007797) Copy   


  • RRID:SCR_007815

    This resource has 10+ mentions.

http://biobases.ibch.poznan.pl/ncRNA/

It is intended to provide information on the sequences and functions of transcripts which do not code for proteins, but perform regulatory roles in the cell. Currently, the database includes over 30,000 individual sequences from 99 species of Bacteria, Archaea and Eukaryota. The primary source of sequences included in the database was the GenBank. Additional annotation information for mouse and human ncRNAs was derived from FANTOM3 database and H-inviational Integrated Database of Annotated Human Genes version 3.4, respectively. Genome mapping information was derived from tha data available at the UCSC Genome Browser site. The sequences and annotations of small cytoplasmic RNAs from bacteria, for which annotation is lacking in the genome sequences, were derived from the Rfam database. The microRNAs or snoRNAs which were available in previous editions, as well as other housekeeping (infrastructural) RNAs (e.g. rRNA, tRNA, snRNA, SRP RNA) are not included in our database to avoid redundancy with more specialized databases which emerged in recent years.

Proper citation: Noncoding RNA database (RRID:SCR_007815) Copy   


  • RRID:SCR_007733

    This resource has 500+ mentions.

http://img.jgi.doe.gov/

Datasets and tools for comparative analysis and annotation of all publicly available genomes from three domains of life in a uniquely integrated context. Plasmids that are not part of a specific microbial genome sequencing project and phage genomes are also included in order to increase its genomic context for comparative analysis. The user interface (see User Interface Map) allows navigating the microbial genome data space along its three key dimensions (genes, genomes, and functions), and groups together the main comparative analysis tools. Microbial genome data analysis in IMG usually starts with the definition of an analysis context in terms of selected genomes, functional annotations, and/or genes, followed by the individual or comparative analysis of genomes, functional annotations, or genes.

Proper citation: IMG (RRID:SCR_007733) Copy   


  • RRID:SCR_007778

    This resource has 1000+ mentions.

http://metacyc.org/

MetaCyc is a database of nonredundant, experimentally elucidated metabolic pathways. MetaCyc contains more than 1,200 pathways from more than 1,600 different organisms, and is curated from the scientific experimental literature. MetaCyc contains pathways involved in both primary and secondary metabolism, as well as associated compounds, enzymes, and genes.

Proper citation: MetaCyc (RRID:SCR_007778) 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. NIDDK Information Network Resources

    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.

  2. Navigation

    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.

  3. Logging in and Registering

    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.

  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 dkNET 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 dkNET 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