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https://www.biovendor.cz/

An Antibody supplier

Proper citation: BioVendor Laboratory Medicine (RRID:SCR_005143) Copy   

•   Source: SciCrunch Registry
  

http://birdgenenames.org/cgnc/

International group of researchers interested in providing standardized gene nomenclature for chicken genes. A Chicken Gene Annotation Tool is available from CGNC-UK which assigns chicken nomenclature based on predicted orthology to human genes. The CGNC-US database includes CGNC-UK information and adds manually biocurated from biocurators and interested contributors. A Human Chicken Ortholog Predictions Search is available. Both resources are part of a united CGNC effort and nomenclature data is shared and co-ordinated between these two resources. They strongly encourage researchers with domain knowledge to participate in this nomenclature effort by requesting a login and providing gene nomenclature for their genes of interest. Please contact them for further information or assistance. The AGNC works in conjunction with public resources such as NCBI and Ensembl and in consultation with existing nomenclature committees, including the Chicken Gene Nomenclature Committee (CGNC). The Avian and Chicken nomenclature efforts are co-ordinated and chicken data is shared between these two groups.

Proper citation: Chicken Gene Nomenclature Consortium (RRID:SCR_004966) Copy   

•   Source: SciCrunch Registry
  

https://code.google.com/p/methylkit/

An R package for DNA methylation analysis and annotation from high-throughput bisulfite sequencing., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: methylKit (RRID:SCR_005177) Copy   

•   Source: SciCrunch Registry
  

http://www.biovision.com/

An Antibody supplier, THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: BioVision (RRID:SCR_005057) Copy   

•   Source: SciCrunch Registry
  

http://sourceforge.net/projects/gesnd/

A software package and a pipeline for identifying causal mutations for rare congenital diseases by next-generation sequencing. Features * one-stop solution for identifying causal mutations of rare genetic diseases * detect wide-spctrum variants, including medium and large sized indels, and tandem repeats * annotate and filter variants * prioritize candidate variants

Proper citation: GESND (RRID:SCR_005179) Copy   

•   Source: SciCrunch Registry
  

http://www.keralauniversity.ac.in/

University of Kerala, formerly the University of Travancore, is an affiliating university located in Thiruvananthapuram, capital of the state of Kerala, India.

Proper citation: University of Kerala; Kerala; India (RRID:SCR_005059) Copy   

•   Source: SciCrunch Registry
  

http://www.well.ox.ac.uk/~kgaulton/chaos.shtml

A Perl-based system for annotation of variants identified in high-throughput sequencing experiments. Functionality includes annotation of variants with information relating to population genetics, known transcripts, positional records, and sequence motif-based prediction. In addition, annotated variants can be summarized and extracted to facilitate downstream analysis. There is also basic support for gene-based biological annotation, and eventually will include tools for variant and genotype analysis and visualization.

Proper citation: CHAoS (RRID:SCR_005174) Copy   

•   Source: SciCrunch Registry
  

http://anntools.sourceforge.net/

Software tool for annotating single nucleotide substitutions (SNP/SNV), small insertions/deletions (indels), and copy number variations (CNV) calls generated from sequencing and microarray data. Only human genome build 37/hg19 can be annotated at this time.

Proper citation: AnnTools (RRID:SCR_005170) Copy   

•   Source: SciCrunch Registry
  

http://www.uni-konstanz.de/en/welcome/

University in the city of Konstanz in Baden-Württemberg, Germany. Its main campus was opened on the Gießberg in 1972 after being founded in 1966.

Proper citation: University of Konstanz; Baden-Wurttemberg; Germany (RRID:SCR_005171) Copy   

•   Source: SciCrunch Registry
  

http://www.usuhs.mil/pha/

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 18,2021.Research in the Department of Pharmacology addresses fundamental questions relevant to understanding the actions of drugs, hormones, neurotransmitters, and growth factors at the molecular and cellular level, as well as their effects on the whole organism. Current areas of focus, employing a wide variety of approaches and model systems, are neuropharmacology and mechanisms of signal transduction. Seminars, Journal Clubs and Interest Groups create a stimulating, supportive and collegial environment in which intra and interdepartmental collaborations flourish. Postdoctoral fellows and graduate students from the interdisciplinary Molecular and Cell Biology and Neuroscience training programs enrich this environment, and faculty are actively encouraged to participate all aspects of graduate education. In addition to modern, well-equipped laboratories within the Department, the Biomedical Instrumentation Center provides core facilities for imaging, flow cytometry, proteomics and protein and DNA sequencing. Other University resources, as well as our proximity to the National Institutes of Health, provide easy access to additional state-of the-art technologies that enhance the research programs of our faculty.

Proper citation: Uniformed Services University of the Health Sciences, Department of Pharmacology (RRID:SCR_005051) Copy   

•   Source: SciCrunch Registry
  

http://www.cebitec.uni-bielefeld.de/index.php/2-uncategorised/47-carma?highlight=WyJjYXJtYSJd

A software pipeline for characterizing the taxonomic composition and genetic diversity of short-read metagenomes. The software was originally designed for the analysis of environmental metagenomes obtained by the ultra-fast 454 pyrosequencing system.

Proper citation: CARMA (RRID:SCR_004999) Copy   

•   Source: SciCrunch Registry
  

http://smithlab.usc.edu/methpipe/

A computational pipeline for analyzing bisulfite sequencing data.

Proper citation: MethPipe (RRID:SCR_005168) Copy   

•   Source: SciCrunch Registry
  

http://www.labspaces.net/index.php

LabSpaces.net is a social network for the scientific community designed to spread scientific news, maintain and create friendships, and harbor collaboration through the internet. The site serves as a web profile for researchers and labs, and is also a community for active communication in the sciences. Current Features LabSpaces offers a wide range of features that will attract and engage researchers. Some of these features include: A Science News feed updated daily with ~40 news articles, UserProfiles, Friends, A Messaging system, Groups, Lab Profiles with Lab members, Lab Picture albums, Collaboration Profiles, Science Discussion Forum, Publication Database, Protocol Database, and free Blogs upon request.

Proper citation: LabSpaces (RRID:SCR_005169) Copy   

•   Source: SciCrunch Registry
  

http://neurowiki.alleninstitute.org/index.php/Main_Page

THIS RESOURCE IS NO LONGER IN SERVICE, documented September 6, 2016. The Allen Institute Neurowiki is a joint project between Vulcan Inc. and the Allen Institute to build a Semantic Wiki mapping genetic instances. It is a finished prototype testing the import pipelines and display componenets for combining 5 major RDF datasets from 4 different sources. Current planning includes mapping complete datasets, curating a better ontology, and creating multiple ontology management for a user class. Biological Linked Data Map: * Open, public online access * Data from multiple RDF data stores * Complete import pipeline using LDIF framework * Outlines of each imported instance embedding inline wiki properties and providing views of imported properties from original RDF datasets * Charting tools that ''''pivot'''' SPARQL queries providing several views of each query * Navigation and composition tools for accessing and mining the data Where did we get the data? * KEGG: Kyoto Encyclopedia of Genes and Genomes: KEGG GENES is a collection of gene catalogs for all complete genomes generated from publicly available resources, mostly NCBI RefSeq * Diseasome: The Diseasome website is a disease / disorder relationships explorer and a sample of an innovative map-oriented scientific work. Built by a team of researchers and engineers, it uses the Human Disease Network dataset. * DrugBank: The DrugBank database is a unique bioinformatics and cheminformatics resource that combines detailed drug data with comprehensive drug target information. * Sider: Sider contains information on marketed medicines and their recorded adverse drug reactions. The information is extracted from public documents and package inserts. Every piece of content on every instance page is generated by Semantic Result Formatters interpreting SPARQL results.

Proper citation: Allen Institute Neurowiki (RRID:SCR_005042) Copy   

•   Source: SciCrunch Registry
  

http://sourceforge.net/projects/asoovir/

A set of Ruby modules to annotate consequence terms, defined by the Sequence Ontology, of variants (SNP/SNVs, INDELs, SVs, CNAs) using Ensembl gene sets. Prior to annotation of variants an Ensembl gene set and reference coding sequences are loaded into memory from a database file, which can be downloaded or generated by the user from reference files. This allows rapid annotation of variants, making it suitable for annotation of whole genome scale calls. Annotation is performed on a transcript level basis, identifying associated sequence ontology terms for affected and nearby transcripts. Default output can be obtained on a gene basis, summarising the consequences for each gene affected, or on a transcript level basis. Output information is also readily customisable using user-generated scripts.

Proper citation: ASOoViR (RRID:SCR_005161) Copy   

•   Source: SciCrunch Registry
  

http://smd.princeton.edu/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on December 17, 2021. Database to store, annotate, view, analyze and share microarray data. It provides registered users access to their own data, provides users access to public data, and tools with which to analyze those data, to any public user anywhere in the world. The GenePattern software package has been incorporated directly into SMD, providing access to many new analysis tools, as well as a plug-in architecture that allows users to directly integrate and share additional tools through SMD. This extension is available with the SMD source code that is fully and freely available to others under an Open Source license, enabling other groups to create a local installation of SMD with an enriched data analysis capability. SMD search options allow the user to Search By Experiments, Search By Datasets, or Search By Gene Names. Web services are provided using common standards, such as Simple Object Access Protocol (SOAP). This enables both local and remote researchers to connect to an installation of the database and retrieve data using pre-defined methods, without needing to resort to use of a web browser.

Proper citation: SMD (RRID:SCR_004987) Copy   

•   Source: SciCrunch Registry
  

http://mitcr.milaboratory.com/

An open source software package aimed at extraction of information on repertoire of T-cell clones from Next Generation Sequencing (NGS) data. It is designed with the knowledge of the critical challenges arising in everyday processing of immunological data.

Proper citation: MiTCR (RRID:SCR_004989) Copy   

•   Source: SciCrunch Registry
  

http://science.nasa.gov/earth-science/earth-science-data/

The Earth Observing System Data and Information System (EOSDIS) is a major core capability within NASA''s Earth Science Data Systems Program. EOSDIS ingests, processes, archives and distributes data from a large number of Earth observing satellites. EOSDIS consists of a set of processing facilities and Earth Science Data Centers distributed across the United States and serves hundreds of thousands of users around the world, providing hundreds of millions of data files each year covering many Earth science disciplines. In order to serve the needs of a broad and diverse community of users, NASA''s Earth Science Data Systems Program is comprised of both Core and Community data system elements. Core data system elements reflect NASA''s responsibility for managing Earth science satellite mission data characterized by the continuity of research, access, and usability. The core comprises all the hardware, software, physical infrastructure, and intellectual capital NASA recognizes as necessary for performing its tasks in Earth science data system management. Community data system elements are those pieces or capabilities developed and deployed largely outside of NASA core elements and are characterized by their evolvability and innovation. Successful applicable elements can be infused into the core, thereby creating a vibrant and flexible, continuously evolving infrastructure. NASA''s Earth Science program was established to use the advanced technology of NASA to understand and protect our home planet by using our view from space to study the Earth system and improve prediction of Earth system change. To meet this challenge, NASA promotes the full and open sharing of all data with the research and applications communities, private industry, academia, and the general public. NASA was the first agency in the US, and the first space agency in the world, to couple policy and adequate system functionality to provide full and open access in a timely manner - that is, with no period of exclusive access to mission scientists - and at no cost. NASA made this decision after listening to the user community, and with the background of the then newly-formed US Global Change Research Program, and the International Earth Observing System partnerships. Other US agencies and international space agencies have since adopted similar open-access policies and practices. Since the adoption of the Earth Science Data Policy adoption in 1991, NASA''s Earth Science Division has developed policy implementation, practices, and nomenclature that mission science teams use to comply with policy tenets. Data System Standards NASA''s Earth Science Data Systems Groups anticipate that effective adoption of standards will play an increasingly vital role in the success of future science data systems. The Earth Science Data Systems Standards Process Group (SPG), a board composed of Earth Science Data Systems stakeholders, directs the process for both identification of appropriate standards and subsequent adoption for use by the Earth Science Data Systems stakeholders.

Proper citation: NASA: Earth Science Data (RRID:SCR_005078) Copy   

•   Source: SciCrunch Registry
  

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

Software that characterizes coexisting subpopulations (SPs) in a tumor using copy number and allele frequencies derived from exome- or whole genome sequencing input data. The model amplifies the statistical power to detect coexisting genotypes, by fully exploiting run-specific tradeoffs between depth of coverage and breadth of coverage. ExPANdS predicts the number of clonal expansions, the size of the resulting SPs in the tumor bulk, the mutations specific to each SP and tumor purity. The main function runExPANdS provides the complete functionality needed to predict coexisting SPs from single nucleotide variations (SNVs) and associated copy numbers. The robustness of the subpopulation predictions by ExPANdS increases with the number of mutations provided. It is recommended that at least 200 mutations are used as an input to obtain stable results.

Proper citation: ExPANdS (RRID:SCR_005199) Copy   

•   Source: SciCrunch Registry
  

http://iaspub.epa.gov/sor_internet/registry/datastds/home/overview/home.do

EPA data standards are a means to promote the efficient sharing of environmental information among US EPA, states, Tribes, local governments, the private sector, and other information trading partners. EPA''s Data Standards are managed by the Data Standards Branch (DSB) within the Office of Environmental Information (OEI). DSB works closely with Federal agencies, states, tribes, and other information trading partners to develop data standards. By its nature the program is a part of EPA''s Enterprise-wide Data Architecture and EPA''s Quality Systems. The use of data standards across EPA''s multiple program offices provides consistently defined and formatted data elements and sets of data values which provide the public access to more meaningful data. The benefits of EPA''s data standards are those as are applicable to any standard: * They are developed by subject matter experts coming to common consensus on how to solve business problems so represents the best solution * They are harder to develop than non-standards, but are more economical in the long term because you can use the same code or presentation and publishing mechanisms to provide access to information * They enable transparency and understanding use of standards promotes common, clear meanings for data that is often reused * They enable access - the same well understood terms, codes, and data structures can be used for data retrieval * They encourage and enable reuse of data and software for multiple purposes * Mappings to standards allow comparisons even when data isn''t standardized solves the environmental interest problem between programs and states * They provide consistent results during data retrieval Standards also promote quality EPA''s goal is high quality information delivered in an efficient way to the people who need it.

Proper citation: EPA Data Standards (RRID:SCR_005077) Copy   

•   Source: SciCrunch Registry