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 15 showing 281 ~ 300 out of 16,813 results
Snippet view Table view Download Top 1000 Results
Click the to add this resource to a Collection

https://www.facebase.org/content/ocdm

To satisfy the need for standardized terminologies several ontologies, we are developing the Ontology of Craniofacial Development and Malformation. When complete, this ontology will describe several realms of anatomy and development relevant to FaceBase, including: * Human craniofacial anatomy, including developmental progressions * Craniofacial malformations * Mouse craniofacial anatomy * Mappings between mouse and human anatomy These ontologies are currently undergoing active development. As a result, these files should be considered very preliminary. They may not work correctly, and contents will almost certainly undergo significant change. Five (sub) ontologies in this zip archive correspond to the categories described above. * OCDM - Ontology of Craniofacial Development and Malformation: currently imports the CHO, CMO, and the CHMMO. * CHO - Craniofacial Human Ontoloogy: normal adult human craniofacial anatomy derived from the FMA. * CMO - Craniofacial Mouse Ontology: normal adult mouse craniofacial anatomy * CHMMO - Craniofacial Human-Mouse Mapping Ontology: mappings of classes in the * CHO to related (homologous) structures in the CMO. CFMO - Craniofacial Malformation Ontology: abnormal human anatomy, includes the CHO All ontologies are in Protege Frames format (requires Protege 3.x). Ontologies refer to other ontologies via the Protege include mechanism. The CHMMO includes the CHO and the CMO. The OCDM (which is the umbrella ontology) includes all of the rest. Future releases will include translations to the OWL language.

Proper citation: OCDM - Ontology of Craniofacial Development and Malformation (RRID:SCR_005999) Copy   


http://www.umich.edu/~neurosci/

The Graduate Program at the University of Michigan was constituted in 1971, making it the longest-standing neuroscience graduate program in the United States. We are a collegial and interactive group of 75 students and 115 faculty that perform research across the breadth of the neuroscience field. Neuroscience graduate students on this campus form a cohesive group, which promotes interactions among the faculty, making the Graduate Program the nexus of the neuroscience community. Graduates receive a Ph.D. in Neuroscience, which provides tremendous flexibility in choosing one's career path. There are more than 100 alumni of our Program, and these graduates work in academic research, industrial research and development, academic medicine and biotechnology. Our program captures the excitement and interaction intrinsic to the field of neuroscience. Students can seek admission to the Neuroscience Program by three different routes direct application to the Neuroscience Program, application via the Program in Biomedical Sciences and application via the Medical Scientist Training Program.

Proper citation: University of Michigan Department of Neuroscience Graduate Program (RRID:SCR_006002) Copy   


  • RRID:SCR_006005

    This resource has 10+ mentions.

http://bioinformatics.charite.de/voronoia/

Voronoia is a program suite to analyse and visualize the atomic packing of protein structures. It is based on the Voronoi Cell method and can be used to estimate the quality of a protein structure, e.g. by comparing the packing density of buried atoms to a reference data set or by highlighting protein regions with large packing defects. Voronoia is also targeted to detect locations of putative internal water or binding sites for ligands. Accordingly, Voronoia is beneficial for a broad range of protein structure approaches. It is applicable as a standalone version coming with a user friendly GUI or, alternatively, as a Pymol Plugin. Finally, Voronoia is also available as an easy to use webtool to process user defined PDB-files or to asses precalculated packing files from DOPP, the regularly updated Dictionary of Packing in Proteins.

Proper citation: Voronoia (RRID:SCR_006005) Copy   


  • RRID:SCR_006000

    This resource has 10+ mentions.

http://cran.r-project.org/web/packages/MetaQC/

Software for quality control and diagnosis for microarray meta-analysis. Quantitative quality control measures include: (1) internal homogeneity of co-expression structure among studies (internal quality control; IQC); (2) external consistency of co-expression structure correlating with pathway database (external quality control; EQC); (3) accuracy of differentially expressed gene detection (accuracy quality control; AQCg) or pathway identification (AQCp); (4) consistency of differential expression ranking in genes (consistency quality control; CQCg) or pathways (CQCp). For each quality control index, the p-values from statistical hypothesis testing are minus log transformed and PCA biplots were applied to assist visualization and decision. Results generate systematic suggestions to exclude problematic studies in microarray meta-analysis and potentially can be extended to GWAS or other types of genomic meta-analysis. The identified problematic studies can be scrutinized to identify technical and biological causes (e.g. sample size, platform, tissue collection, preprocessing etc) of their bad quality or irreproducibility for final inclusion / exclusion decision.

Proper citation: MetaQC (RRID:SCR_006000) Copy   


http://mialab.mrn.org/index.html

MIALAB, headed by Dr. Vince Calhoun, focuses on developing and optimizing methods and software for quantitative analysis of structure and function in medical images with particular focus on the study of psychiatric illness. We work with many types of data, including functional magnetic resonance imaging (fMRI), diffusion tensor imaging (DTI), electroencephalography (EEG), structural imaging and genetic data. Much of our time is spent working on new methods for flexible analysis of brain imaging data. The use of data driven approaches is very useful for extracting potentially unpredictable patterns within these data. However such methods can be further improved by incorporating additional prior information as constraints, in order to benefit from what we know. To this end, we draw heavily from the areas of image processing, adaptive signal processing, estimation theory, neural networks, statistical signal processing, and pattern recognition.

Proper citation: MIALAB - Medical Image Analysis Lab (RRID:SCR_006089) Copy   


http://bishopw.loni.ucla.edu/AIR5/

A tool for automated registration of 3D (and 2D) images within and across subjects and within and sometimes across imaging modalities. The AIR library can easily incorporate automated image registration into site specific programs adapted to your particular needs.

Proper citation: Automated Image Registration (RRID:SCR_005944) Copy   


  • RRID:SCR_005942

    This resource has 10+ mentions.

http://bio-bigdata.hrbmu.edu.cn/diseasemeth/

Human disease methylation database. DiseaseMeth version 2.0 is focused on aberrant methylomes of human diseases. Used for understanding of DNA methylation driven human diseases.

Proper citation: DiseaseMeth (RRID:SCR_005942) Copy   


http://distild.jensenlab.org/

The DistiLD database aims to increase the usage of existing genome-wide association studies (GWAS) results by making it easy to query and visualize disease-associated SNPs and genes in their chromosomal context. The database performs three important tasks: # published GWAS are collected from several sources and linked to standardized, international disease codes ICD10 codes) # data from the International HapMap Project are analyzed to define linkage disequilibrium (LD) blocks onto which SNPs and genes are mapped # the web interface makes it easy to query and visualize disease-associated SNPs and genes within LD blocks. Users can query the database by diseases, SNPs or genes. No matter which of the three query modes was used, an intermediate page will be shown listing all the studies that matched the search with a link to the corresponding publication. The user can select either all studies related to a certain disease or one specific study for which to view the related LD blocks. The DistiLD resource integrates information on: * Associations between Single Nucleotide Polymorphisms (SNPs) and diseases from genome-wide association studies (GWAS) * Links between SNPs and genes based on linkage disequilibrium (LD) data from HapMap For convenience, we provide the complete datasets as two (zipped) tab-delimited files. The first file contains GWAS results mapped to LD blocks. The second file contains all SNPs and genes assigned to each LD block.

Proper citation: DistiLD - Diseases and Traits in LD (RRID:SCR_005943) Copy   


http://www.nematodes.org/NeglectedGenomes/ARTHROPODA/

As part of our effort in PhyloGenomics, we have developed the PartiGene ARTHROPODA Database. In these databases, we have analyzed the EST datasets for sixty different arthropod species. To aid searching we have split the interface between four class-based views: Chelicerata, Hexapoda, Crustacea, Myriapoda. Amongst other analyses, we have included Alfried Vogler's lab's PartiGene analysis of ~30 different arthropod species ESTs. A separate access point for that dataset is also available.

Proper citation: PartiGene ARTHROPODA Database (RRID:SCR_006071) Copy   


  • RRID:SCR_006073

    This resource has 1+ mentions.

http://newt-omics.mpi-bn.mpg.de/index.php

Newt-omics is a database, which enables researchers to locate, retrieve and store data sets dedicated to the molecular characterization of newts. Newt-omics is a transcript-centered database, based on an Expressed Sequence Tag (EST) data set from the newt, covering ~50,000 Sanger sequenced transcripts and a set of high-density microarray data, generated from regenerating hearts. Newt-omics also contains a large set of peptides identified by mass spectrometry, which was used to validate 13,810 ESTs as true protein coding. Newt-omics is open to implement additional high-throughput data sets without changing the database structure. Via a user-friendly interface Newt-omics allows access to a huge set of molecular data without the need for prior bioinformatical expertise. The newt Notopthalmus viridescens is the master of regeneration. This organism is known for more than 200 years for its exceptional regenerative capabilities. Newts can completely replace lost appendages like limb and tail, lens and retina and parts of the central nervous system. Moreover, after cardiac injury newts can rebuild the functional myocardium with no scar formation. To date only very limited information from public databases is available. Newt-Omics aims to provide a comprehensive platform of expressed genes during tissue regeneration, including extensive annotations, expression data and experimentally verified peptide sequences with yet no homology to other publicly available gene sequences. The goal is to obtain a detailed understanding of the molecular processes underlying tissue regeneration in the newt, that may lead to the development of approaches, efficiently stimulating regenerative pathways in mammalians. * Number of contigs: 26594 * Number of est in contigs: 48537 * Number of transcripts with verified peptide: 5291 * Number of peptides: 15169

Proper citation: Newtomics (RRID:SCR_006073) Copy   


  • RRID:SCR_006070

    This resource has 10+ mentions.

http://www.nematodes.org/nembase4/

NEMBASE is a comprehensive Nematode Transcriptome Database including 63 nematode species, over 600,000 ESTs and over 250,000 proteins. Nematode parasites are of major importance in human health and agriculture, and free-living species deliver essential ecosystem services. The genomics revolution has resulted in the production of many datasets of expressed sequence tags (ESTs) from a phylogenetically wide range of nematode species, but these are not easily compared. NEMBASE4 presents a single portal into extensively functionally annotated, EST-derived transcriptomes from over 60 species of nematodes, including plant and animal parasites and free-living taxa. Using the PartiGene suite of tools, we have assembled the publicly available ESTs for each species into a high-quality set of putative transcripts. These transcripts have been translated to produce a protein sequence resource and each is annotated with functional information derived from comparison with well-studied nematode species such as Caenorhabditis elegans and other non-nematode resources. By cross-comparing the sequences within NEMBASE4, we have also generated a protein family assignment for each translation. The data are presented in an openly accessible, interactive database. An example of the utility of NEMBASE4 is that it can examine the uniqueness of the transcriptomes of major clades of parasitic nematodes, identifying lineage-restricted genes that may underpin particular parasitic phenotypes, possible viral pathogens of nematodes, and nematode-unique protein families that may be developed as drug targets.

Proper citation: NEMBASE (RRID:SCR_006070) Copy   


  • RRID:SCR_005939

    This resource has 1+ mentions.

http://www.wf4ever-project.org/

Project to addresses challenges associated with the preservation of scientific experiments in data-intensive science, including: * The definition of models to describe, in a standard way, scientific experiments by means of workflow-centric Research Objects, which comprise scientific workflows, the provenance of their executions, interconnections between workflows and related resources (e.g., datasets, publications, etc.), and social aspects related to such scientific experiments. * The collection of best practices for the creation and management of Research Objects. * The analysis and management of decay in scientific workflows. To address these challenges they are creating an architecture and tooling for the access, manipulation, sharing, reuse and evolution of Research Objects in a range of disciplines. This will result into the next generation RO-enabled myExperiment.

Proper citation: Workflow4Ever (RRID:SCR_005939) Copy   


  • RRID:SCR_005971

    This resource has 10+ mentions.

http://vbrc.org/index.asp

One of eight Bioinformatics Resource Centers nationwide providing comprehensive web-based genomics resources including a relational database and web application supporting data storage, annotation, analysis, and information exchange to support scientific research directed at viruses belonging to the Arenaviridae, Bunyaviridae, Filoviridae, Flaviviridae, Paramyxoviridae, Poxviridae, and Togaviridae families. These centers serve the scientific community and conduct basic and applied research on microorganisms selected from the NIH/NIAID Category A, B, and C priority pathogens that are regarded as possible bioterrorist threats or as emerging or re-emerging infectious diseases. The VBRC provides a variety of analytical and visualization tools to aid in the understanding of the available data, including tools for genome annotation, comparative analysis, whole genome alignments, and phylogenetic analysis. Each data release contains the complete genomic sequences for all viral pathogens and related strains that are available for species in the above-named families. In addition to sequence data, the VBRC provides a curation for each virus species, resulting in a searchable, comprehensive mini-review of gene function relating genotype to biological phenotype, with special emphasis on pathogenesis.

Proper citation: VBRC (RRID:SCR_005971) Copy   


  • RRID:SCR_006017

    This resource has 1+ mentions.

http://hfv.lanl.gov/content/index

The Hemorrhagic Fever Viruses (HFV) sequence database collects and stores sequence data and provides a user-friendly search interface and a large number of sequence analysis tools, following the model of the highly regarded and widely used Los Alamos HIV database. The database uses an algorithm that aligns each sequence to a species-wide reference sequence. The NCBI RefSeq database is used for this; if a reference sequence is not available, a Blast search finds the best candidate. Using this method, sequences in each genus can be retrieved pre-aligned. Hemorrhagic fever viruses (HFVs) are a diverse set of over 80 viral species, found in 10 different genera comprising five different families: arena-, bunya-, flavi-, filo- and togaviridae. All these viruses are highly variable and evolve rapidly, making them elusive targets for the immune system and for vaccine and drug design. About 55,000 HFV sequences exist in the public domain today. A central website that provides annotated sequences and analysis tools will be helpful to HFV researchers worldwide.

Proper citation: HFV Database (RRID:SCR_006017) Copy   


  • RRID:SCR_005963

    This resource has 10+ mentions.

http://sourceforge.net/projects/bless-ec/

Software tool for Bloom-filter-based error correction for next-generation sequencing (NGS) reads. The algorithm produces accurate correction results with much less memory.

Proper citation: BLESS (RRID:SCR_005963) Copy   


  • RRID:SCR_006013

    This resource has 100+ mentions.

http://fungidb.org/fungidb/

FungiDB is a database for functional and evolutionary comparison of fungal genomes. FungiDB is a functional genomic resource for pan-fungal genomes that was developed in partnership with the Eukaryotic Pathogen Bioinformatic resource center (http://EuPathDB.org). FungiDB uses the same infrastructure and user interface as EuPathDB, which allows for sophisticated and integrated searches to be performed using an intuitive graphical system. The current release of FungiDB contains genome sequence and annotation from 18 species spanning several fungal classes, including the Ascomycota classes, Eurotiomycetes, Sordariomycetes, Saccharomycetes and the Basidiomycota orders, Pucciniomycetes and Tremellomycetes, and the basal "Zygomycete" lineage Mucormycotina. Additionally, FungiDB contains cell cycle microarray data, hyphal growth RNA-sequence data and yeast two hybrid interaction data. The underlying genomic sequence and annotation combined with functional data, additional data from the FungiDB standard analysis pipeline and the ability to leverage orthology provides a powerful resource for in silico experimentation.

Proper citation: FungiDB (RRID:SCR_006013) Copy   


  • RRID:SCR_006015

    This resource has 10+ mentions.

http://jjwanglab.org:8080/gwasdb/

Combines collections of genetic variants (GVs) from GWAS and their comprehensive functional annotations, as well as disease classifications. Used to maximize utilility of GWAS data to gain biological insights through integrative, multi-dimensional functional annotation portal. In addition to all GVs annotated in NHGRI GWAS Catalog, we manually curate GVs that are marginally significant (P value < 10-3) by looking into supplementary materials of each original publication and provide extensive functional annotations for these GVs. GVs are manually classified by diseases according to Disease Ontology Lite and HPO (Human Phenotype Ontology) for easy access. Database can also conduct gene based pathway enrichment and PPI network association analysis for those diseases with sufficient variants. SOAP services are available. You may Download GWASdb SNP. (This file contains all of the significant SNP in GWASdb. In the pvalue column, 0 means this P-value is not reported in the study but it is significant SNP. In the source column, GWAS:A represents the original data in GWAS catalog, while GWAS:B is our curation data which P-value < 10-3)

Proper citation: GWASdb (RRID:SCR_006015) Copy   


  • RRID:SCR_006011

    This resource has 100+ mentions.

http://equilibrator.weizmann.ac.il/

Web interface designed for thermodynamic analysis of biochemical systems. eQuilibrator enables free-text search for biochemical compounds and reactions and provides thermodynamic estimates for both in a variety of conditions. It can provide estimates for compounds in the KEGG database, and individual compounds and enzymes can be searched for by their common names (water, glucosamine, hexokinase). Reactions can be entered in a free-text format that eQuilibrator parses automatically. eQuilibrator also allows manipulation of the conditions of a reaction - pH, ionic strength, and reactant and product concentrations.

Proper citation: eQuilibrator (RRID:SCR_006011) Copy   


http://www.ddcf.org/

The mission of the Doris Duke Charitable Foundation is to improve the quality of people''s lives through grants supporting the performing arts, environmental conservation, medical research and the prevention of child abuse, and through preservation of the cultural and environmental legacy of Doris Duke''s properties. Established in 1996, the foundation supports four national grant-making programs. It also supports three properties that were owned by Doris Duke in Hillsborough, New Jersey; Honolulu, Hawaii; and Newport, Rhode Island. The foundation is headquartered in New York and is governed by a board of 12 Trustees. DDCF''s activities are guided by the will of Doris Duke, who endowed the foundation with financial assets that totaled approximately $1.6 billion as of December 31, 2010. The foundation regularly evaluates and modifies its allocation of resources from the endowment to support the programs and properties and to respond to fluctuations in portfolio returns. The foundation awarded its first grants in 1997. As of December 31, 2011, the foundation has awarded grants totaling more than $1 billion. DDCF awards grants in four core program areas: * The Arts Program supports performing artists with the creation and public performance of their work. * The Environment Program supports efforts that enable communities to protect and manage wildlife habitat and create efficient built environments. * The Medical Research Program seeks to contribute to the prevention and cure of disease by supporting clinical research. * The Child Abuse Prevention Program seeks to protect children from abuse and neglect in order to promote their healthy development. In the fall of 2007, DDCF also launched the African Health Initiative, with the goal of strengthening health systems in sub-Saharan Africa. The Building Bridges Program, which seeks to increase public understanding of Islamic cultures through media and the arts, is funded through the Doris Duke Foundation for Islamic Art and is headquartered in DDCF''s offices in New York. The Properties In her will, Doris Duke requested that several operating foundations manage the properties listed below. She also expressed her wishes that the properties be opened for public visitation and used for educational programs. The operating foundations receive funding from the Doris Duke Charitable Foundation. * The Duke Farms Foundation manages a 2,700-acre property in Hillsborough, New Jersey, which is known as Duke Farms and has a mission of environmental stewardship. * The Doris Duke Foundation for Islamic Art manages Doris Duke''s home in Honolulu, Hawaii, which is known as Shangri La and serves as a center for the study of Islamic art and cultures. * The Newport Restoration Foundation preserves historic houses in Newport, Rhode Island, and operates Doris Duke''s home in Newport known as Rough Point, which is also a public museum.

Proper citation: Doris Duke Charitable Foundation (RRID:SCR_006012) Copy   


http://freesurfer.net/fswiki/HippocampalSubfieldSegmentation

A software package for automatic segmentation of hippocampal subfields in magnetic resonance imges. Given a pair of T1-weighted and T2-weighted images (the latter acquired using a protocol tuned for hippocampus imaging), ASHS will automatically label main subfields of the hippocampus, and some extra-hippocampal structures, using multi-atlas segmentation. The main method is described in the Yushkevich et al. 2011 Neuroimage paper (http://tinyurl.com/cffrp3p). * execution requires: Advanced Normalization Tools, FSL

Proper citation: Segmentation of Hippocampus Subfields (RRID:SCR_005996) 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