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http://www.cbs.dtu.dk/ws/ws.php?entry=BLASTatlas

The BLASTatlas is a tool that is useful for mapping and visualizing whole genome homology of genes and proteins within a reference strain compared to other strains or species of one or more prokaryotic organisms using either blastp, blastn, tblastn, or blastx. DNA structural information is also included in the atlas to visualize the DNA chromosomal context of regions. Additional information can be added to these plots. The tool is SOAP compliant and WSDL (web services description language) files are available with programming examples available in Perl. The resolution is per-residue or per nucleotide depending on the regime of the blast search: For each annotation in the reference genome, the best hit in the database genome is found using one of the above algorithms. Each matching or mismatching residue/nucleotide of the best hit (based on BLAST score) is then mapped back to the genome sequence, using the coordinates provided in the annotations. By providing an interoperable method to carry out whole genome visualization of homology, this service offers bioinformaticians as well as biologists an easy-to-adopt workflow that can be directly called from the programming language of the user, hence enabling automation of repeated tasks. This tool can be relevant in many pangenomic as well as in metagenomic studies, by giving a quick overview of clusters of insertion sites, genomic islands and overall homology between a reference sequence and a data set.

Proper citation: BLASTatlas - Mapping of whole genome homology (RRID:SCR_005891) Copy   

•   Source: SciCrunch Registry

http://great.stanford.edu/public/html/splash.php

Data analysis service that predicts functions of cis-regulatory regions identified by localized measurements of DNA binding events across an entire genome. Whereas previous methods took into account only binding proximal to genes, GREAT is able to properly incorporate distal binding sites and control for false positives using a binomial test over the input genomic regions. GREAT incorporates annotations from 20 ontologies and is available as a web application. The utility of GREAT extends to data generated for transcription-associated factors, open chromatin, localized epigenomic markers and similar functional data sets, and comparative genomics sets. Platform: Online tool

Proper citation: GREAT: Genomic Regions Enrichment of Annotations Tool (RRID:SCR_005807) Copy   

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http://www.hormone.org/

A portal for hormone-related health information for the public, physicians, allied health professionals and the media. It serves as a resource for the public by promoting the prevention, treatment and cure of hormone-related conditions through outreach and education. It provides free educational materials, public forums, physician referral service, and media education campaigns. It offers a library of educational materials and programs covering a wide range of endocrine topics, including adrenal disorders, breast cancer, diabetes, osteoporosis, stress, thyroid disease and cancer.

Proper citation: Hormone Health Network (RRID:SCR_005765) Copy   

•   Source: SciCrunch Registry

https://www.google.com/docs/about/

Authoring tool to create, share, and collaborate on the web with documents, spreadsheets, presentations, and more in real time. All your changes are saved automatically in Drive.

Proper citation: Google Docs (RRID:SCR_005886) Copy   

•   Source: SciCrunch Registry

http://manuals.bioinformatics.ucr.edu/home/R_BioCondManual#GOHyperGAll

To test a sample population of genes for overrepresentation of GO terms, the R/BioC function GOHyperGAll computes for all GO nodes a hypergeometric distribution test and returns the corresponding p-values. A subsequent filter function performs a GO Slim analysis using default or custom GO Slim categories. Basic knowledge about R and BioConductor is required for using this tool. Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible, THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: GOHyperGAll (RRID:SCR_005766) Copy   

•   Source: SciCrunch Registry

https://gene-atlas.brainminds.jp/

Database of gene expression in the marmoset brain.Comparative anatomy of marmoset and mouse cortex from genomic expression. Atlas comparing brain of neonatal marmoset with mouse using in situ hybridization.

Proper citation: Expression Atlas of the Marmoset (RRID:SCR_005760) Copy   

•   Source: SciCrunch Registry

http://www.cancer.fi/syoparekisteri/en/

The Finnish Cancer Registry maintains a nation-wide database on all cancer cases in Finland going back to 1953. It is also an internationally active institute for statistical and epidemiological cancer research. The Mass Screening Registry is a department of the Finnish Cancer Registry, and is responsible of planning and evaluating national cancer screening programs in Finland. The site contains information on cancer research and up to date statistics on the prevalence of different types of cancer in Finland, the Nordic countries and on a global level. The web pages include information for participants in cancer screening and for professionals involved in organizing such screening.

Proper citation: Finnish Cancer Registry (RRID:SCR_005881) Copy   

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http://www.scytek.com/

An Antibody supplier

Proper citation: ScyTek Laboratories (RRID:SCR_005919) Copy   

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http://www.vectorbase.org

Bioinformatics Resource Center for invertebrate vectors. Provides web-based resources to scientific community conducting basic and applied research on organisms considered potential agents of biowarfare or bioterrorism or causing emerging or re-emerging diseases.

Proper citation: VectorBase (RRID:SCR_005917) Copy   

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http://snp-magma.sourceforge.net

Software that utilizes a multiobjective evolutionary algorithm for genetic mapping. It is based on a the ECJ evolutionary software package written by Sean Luke and includes the Strength Pareto Evoluationary Algorithm Version 2 changes for multiobjective analysis. The code runs on any platform with Java Version 2. A genetic mapping project, typically implemented during a search for genes responsible for a disease, requires the acquisition of a set of data from each of a large number of individuals. This data set includes the values of multiple genetic markers. These genetic markers occur at discrete positions along the genome, which is a collection of one or more linear chromosomes. Typing the value of a marker in an individual carries a cost; one seeks to minimize the number of markers typed without excessively jeopardizing the probability of detecting an association between a marker and a disease phenotype. MAGMA is a project which employ''s a multiobjective evolutionary algorithm to solve this problem.

Proper citation: MAGMA (RRID:SCR_005757) Copy   

•   Source: SciCrunch Registry

https://adaptivedisclosure.wordpress.com/aida/

A generic set of components that can perform a variety of tasks, such as learn new pattern recognition models, perform specialized search on resource collections, and store knowledge in a repository. W3C standards are used to make data accessible and manageable with semantic web technologies such as OWL, RDF(S), and SKOS. The AIDA Toolkit is directed at groups of knowledge workers that cooperatively search, annotate, interpret, and enrich large collections of heterogeneous documents from diverse locations. The server offers services for: text indexing and statistics, metadata storage and querying, thesaurus reasoning, annotation, text retrieval, spelling correction, synonym detection, and model learning.

Proper citation: AIDA Toolkit (RRID:SCR_005914) Copy   

•   Source: SciCrunch Registry

http://icahn.mssm.edu/

Icahn School of Medicine at Mount Sinai, formerly Mount Sinai School of Medicine, is graduate medical school in Manhattan, New York City. Leader in medical and scientific training and education, biomedical research and patient care.

Proper citation: Icahn School of Medicine at Mount Sinai; New York; USA (RRID:SCR_005793) Copy   

•   Source: SciCrunch Registry

http://www.ebi.ac.uk/Tools/pfa/iprscan/

Software package for functional analysis of sequences by classifying them into families and predicting presence of domains and sites. Scans sequences against InterPro's signatures. Characterizes nucleotide or protein function by matching it with models from several different databases. Used in large scale analysis of whole proteomes, genomes and metagenomes. Available as Web based version and standalone Perl version and SOAP Web Service.

Proper citation: InterProScan (RRID:SCR_005829) Copy   

•   Source: SciCrunch Registry

http://www.ebi.ac.uk/webservices/whatizit/info.jsf

A text processing system that allows you to do textmining tasks on text. It is great at identifying molecular biology terms and linking them to publicly available databases. Whatizit is also a Medline abstracts retrieval/search engine. Instead of providing the text by Copy&Paste, you can launch a Medline search. The abstracts that match your search criteria are retrieved and processed by a pipeline of your choice. Whatizit is also available as 1) a webservice and as 2) a streamed servlet. The webservice allows you to enrich content within your website in a similar way as in the wikipedia. The streamed servlet allows you to process large amounts of text.

Proper citation: Whatizit (RRID:SCR_005824) Copy   

•   Source: SciCrunch Registry

http://www.ibridgenetwork.org/wustl/splinter

Software that detects and quantifies short IN/DELs as well as single nucleotide substitutions in pooled-DNA samples.

Proper citation: SPLINTER (RRID:SCR_005826) Copy   

•   Source: SciCrunch Registry

http://umbbd.msi.umn.edu/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on August 27, 2014. Database containing information on microbial biocatalytic reactions and biodegradation pathways for primarily xenobiotic, chemical compounds. Its goal is to provide information on microbial enzyme-catalyzed reactions that are important for biotechnology. The reactions covered are studied for basic understanding of nature, biocatalysis leading to specialty chemical manufacture, and biodegradation of environmental pollutants. Individual reactions and metabolic pathways are presented with information on the starting and intermediate chemical compounds, the organisms that transform the compounds, the enzymes, and the genes. The present database has been successfully used to teach enzymology and use of biochemical Internet information resources to advanced undergraduate and graduate students, and is being expanded primarily with the help of such students. In addition to reactions and pathways, this database also contains Biochemical Periodic Tables and a Pathway Prediction System. * Search the UM-BBD for compound, enzyme, microorganism, pathway, or BT rule name; chemical formula; chemical structure; CAS Registry Number; or EC code. * Go to Pathways and Metapathways in the UM-BBD * Lists of 203 pathways; 1400 reactions; 1296 compounds; 916 enzymes; 510 microorganism entries; 245 biotransformation rules; 50 organic functional groups; 76 reactions of naphthalene 1,2-dioxygenase; 109 reactions of toluene dioxygenase; Graphical UM-BBD Overview; and Other Graphics (Metapathway and Pathway Maps and Reaction Mechanisms).

Proper citation: UM-BBD (RRID:SCR_005787) Copy   

•   Source: SciCrunch Registry

Ratings or validation data are available for this resource

http://genome.ucsc.edu/

Portal to interactively visualize genomic data. Provides reference sequences and working draft assemblies for collection of genomes and access to ENCODE and Neanderthal projects. Includes collection of vertebrate and model organism assemblies and annotations, along with suite of tools for viewing, analyzing and downloading data.

Proper citation: UCSC Genome Browser (RRID:SCR_005780) Copy   

•   Source: SciCrunch Registry

http://www.patternlabforproteomics.org/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented July 5, 2018. Gene Ontology Explorer (GOEx) combines data from protein fold changes with GO over-representation statistics to help draw conclusions in proteomic experiments. It is tightly integrated within the PatternLab for Proteomics project and, thus, lies within a complete computational environment that provides parsers and pattern recognition tools designed for spectral counting. GOEx offers three independent methods to query data: an interactive directed acyclic graph, a specialist mode where key words can be searched, and an automatic search. A recent hack included in GOEx is to load the sparse matrix index file directly into GOEx, instead of going through the report generation using the AC/T-fold methods. This makes it easy for GOEx to analyze any list of proteins as long as the list follows the index file format (described in manuscript) . Please note that if using this alternative strategy, there will be no protein fold information. Platform: Windows compatible

Proper citation: GOEx - Gene Ontology Explorer (RRID:SCR_005779) Copy   

•   Source: SciCrunch Registry

https://www.applichem.com/home/

An Antibody supplier

Proper citation: AppliChem (RRID:SCR_005814) Copy   

•   Source: SciCrunch Registry

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

OWLTools (aka OWL2LS - OWL2 Life Sciences) is a java API for accessing ontologies in either OBO or OWL. OWLTools provides a bio-ontologies friendly wrapper on top of the Manchester OWL API. It provides many features, including: * convenience methods for OBO-like properties such as synonyms, textual definitions, obsoletion, replaced_by * simple graph-like operations over ontologies * visualization using the QuickGO graphs libraries Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: OWLTools (RRID:SCR_005732) Copy   

•   Source: SciCrunch Registry