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http://wannovar.usc.edu/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 6,2023. Web interface to the ANNOVAR software, a tool to annotate functional consequences of genetic variation from high-throughput sequencing data, to help biologists without bioinformatics skills to easily submit a list of mutations (even whole-genome variants calls) to the web server, select the desired annotation categories, and receive functional annotation back by emails. Given a list of single nucleotide variants (SNVs) and insertions / deletions in VCF or ANNOVAR input format, wANNOVAR annotates their functional effects on genes (such as amino acid changes for non-synonymous SNPs), calculate their predicted functional importance scores (such as SIFT and PolyPhen scores), retrieve allele frequencies in public databases (such as the 1000 Genomes Project and NHLBI-ESP 6500 exomes), and implement a variants reduction protocol to identify a subset of potentially deleterious variants., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: wANNOVAR (RRID:SCR_000565) Copy   

•   Source: SciCrunch Registry

http://sites.huji.ac.il/malaria/

Data set of metabolic pathways for the malaria parasite based on the present knowledge of parasite biochemistry and on pathways known to occur in other unicellular eukaryotes. This site extracted the pertinent information from the universal sites and presented them in an educative and informative format. The site also includes, cell-cell interactions (cytoadherence and rosetting), invasion of the erythrocyte by the parasite and transport functions. It also contains an artistic impression of the ultrastructural morphology of the interaerythrocytic cycle stages and some details about the morphology of mitochondria and the apicoplast. Most pathways are relevant to the erythrocytic phase of the parasite cycle. All maps were checked for the presence of enzyme-coding genes as they are officially annotated in the Plasmodium genome (http://plasmodb.org/). The site is constructed in a hierarchical pattern that permits logical deepening: * Grouped pathways of major chemical components or biological process ** Specific pathways or specific process *** Chemical structures of substrates and products or process **** Names of enzymes and their genes or components of process Each map is linked to other maps thus enabling to verify the origin of a substrate or the fate of a product. Clicking on the EC number that appears next to each enzyme, connects the site to BRENDA, SWISSPROT ExPASy ENZYME, PlasmoDB and to IUBMB reaction scheme. Clicking of the name of a metabolite, connects the site to KEGG thus providing its chemical structure and formula. Next to each enzyme there is a pie that depicts the stage-dependent transcription of the enzyme''s coding gene. The pie is constructed as a clock of the 48 hours of the parasite cycle, where red signifies over-transcription and green, under-transcription. Clicking on the pie links to the DeRisi/UCSF transcriptome database.

Proper citation: Malaria Parasite Metabolic Pathways (RRID:SCR_007072) Copy   

•   Source: SciCrunch Registry

https://www.integromics.com/omicsoffice-for-ngs/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 18,2025. Software for secondary and tertiary analysis of Next Generation Sequencing (NGS) data.

Proper citation: OmicsOffice for NGS SeqSolve (RRID:SCR_001222) Copy   

•   Source: SciCrunch Registry

http://mus.well.ox.ac.uk/mouse/INBREDS/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 19,2025. Data set of genotypes available for 480 strains and 13370 successful SNP assays that are mapped to build34 of the mouse genome, including 107 SNPs that are mapped to random unanchored sequence 13374 SNPs are mapped onto Build 33 of the mouse genome. You can access the data relative to Build 33 or Build 34.

Proper citation: Wellcome-CTC Mouse Strain SNP Genotype Set (RRID:SCR_003216) Copy   

•   Source: SciCrunch Registry

http://www.broad.mit.edu/node/549

Genomic data set on Type 2 Diabetes in African-Americans derived via admixture mapping, a method for genome-wide association analysis based on admixture-generated linkage disequilibrium. This collaborative group has identified 1,478 African Americans with Type 2 Diabetes (T2D) from the Jackson Heart Study and Multiethnic Cohort Study, as well as 498 controls from the Jackson Heart Study who are normoglycemic despite high body mass index and older age. All samples were genotyped (using the Illumina BeadLab platform) for 1,291 polymorphic markers chosen to be extremely different in frequency between west Africans and European Americans. Evidence for association to diabetes at each marker as reported by the ANCESTRYMAP software are reported in the downloadable table. They calculate that this study has statistical power to detect loci where African or European ancestry on average confers multiplicative increased risk of 1.35-fold or more. The fact that they did not detect a statistically significant signal of association in the scan suggests that any genetic risk factors for T2D do not confer different risks due to ancestry that differ by this factor. The genome scan results are publicly available (Excel file) prior to publication so that researchers interested in the genetics of T2D can use the results of the scan to prioritize follow-up of any regions of interest.

Proper citation: A Whole Genome Admixture Scan for Type 2 Diabetes in African Americans (RRID:SCR_006984) Copy   

•   Source: SciCrunch Registry

http://eyebrowse.cit.nih.gov/

EyeBrowse displays expressed sequence tag (EST) cDNA clones from eye tissues (derived from NEIBank and other sources) aligned with current versions of the human, rhesus, mouse, rat, dog, cow, chicken, or zebrafish genomes, including reference sequences for known genes. This gives a simplified view of gene expression activity from different parts of the eye across the genome. The data can be interrogated in several ways. Specific gene names can be entered into the search window. Alternatively, regions of the genome can be displayed. For example, entering two STS markers separated by a semicolon (e.g. RH18061;RH80175) allows the display of the entire chromosomal region associated with the mapping of a specific disease locus. ESTs for each tissue can then be displayed to help in the selection of candidate genes. In addition, sequences can be entered into a BLAT search and rapidly aligned on the genome, again showing eye derived ESTs for the same region. EyeBrowse includes a custom track display SAGE data for human eye tissues derived from the EyeSAGE project. The track shows the normalized sum of SAGE tag counts from all published eye-related SAGE datasets centered on the position of each identifiable Unigene cluster. This indicates relative activity of each gene locus in eye. Clicking on the vertical count bar for a particular location will bring up a display listing gene details and linking to specific SAGE counts for each eye SAGE library and comparisons with normalized sums for neural and non-neural tissues. To view or alter settings for the EyeSAGE track on EyeBrowse, click on the vertical gray bar at the left of the display. Other custom tracks display known eye disease genes and mapped intervals for candidate loci for retinal disease, cataract, myopia and cornea disease. These link back to further information at NEIBank. For mouse, there is custom track data for ChIP-on-Chip of RNA-Polymerase-II during photoreceptor maturation.

Proper citation: EyeBrowse (RRID:SCR_008000) Copy   

•   Source: SciCrunch Registry

http://www.hgvs.org/dblist/dblist.html

A list of various databases freely available to the public, including several mutation and variation resources, such as education resources for teachers students provided by the Human Genome Variation Society. Databases listed include: * Locus Specific Mutation Databases * Disease Centered Central Mutation Databases * Central Mutation and SNP Databases * National and Ethnic Mutation Databases * Mitochondrial Mutation Databases * Chromosomal Variation Databases * Other Mutation Databases ( i.e. your round holes don''''t fit our square pegs) * Clinical and Patient Aspects Databases * Non Human Mutation Databases * Artificial Mutations Only * Other Related Databases * Education Resources for Teachers and Students

Proper citation: Human Genome Variation Society: Databases and Other Tools (RRID:SCR_006876) Copy   

•   Source: SciCrunch Registry

http://rulai.cshl.edu/SCPD/

A promoter database of Saccharomyces cerevisiae. Users can explore the promoter regions of ~6000 genes and ORFs in yeast genome, annotate putative regulatory sites of all genes and ORFs, locate intergenic regions, and retrieve sequence of the promoter region. In regards to regulatory elements and transcription factors, users can provide information on transcriptionally related genes, browse matrix and consensus sequences, view the correlation between elements, observe binding affinity and expression, and look at genomewise distribution. SCPD also provides some simple but useful tools for promoter sequence analysis. Gene, consensus and matrix records may be submitted.

Proper citation: SCPD - Saccharomyces cerevisiae promoter database (RRID:SCR_004412) Copy   

•   Source: SciCrunch Registry

http://sequenceontology.org/

A collaborative ontology for the definition of sequence features used in biological sequence annotation. SO was initially developed by the Gene Ontology Consortium. Contributors to SO include the GMOD community, model organism database groups such as WormBase, FlyBase, Mouse Genome Informatics group, and institutes such as the Sanger Institute and the EBI. Input to SO is welcomed from the sequence annotation community. The OBO revision is available here: http://sourceforge.net/p/song/svn/HEAD/tree/ SO includes different kinds of features which can be located on the sequence. Biological features are those which are defined by their disposition to be involved in a biological process. Biomaterial features are those which are intended for use in an experiment such as aptamer and PCR_product. There are also experimental features which are the result of an experiment. SO also provides a rich set of attributes to describe these features such as polycistronic and maternally imprinted. The Sequence Ontologies use the OBO flat file format specification version 1.2, developed by the Gene Ontology Consortium. The ontology is also available in OWL from Open Biomedical Ontologies. This is updated nightly and may be slightly out of sync with the current obo file. An OWL version of the ontology is also available. The resolvable URI for the current version of SO is http://purl.obolibrary.org/obo/so.owl.

Proper citation: SO (RRID:SCR_004374) Copy   

•   Source: SciCrunch Registry

http://bix.ucsd.edu/projects/singlecell/

Software package for short read data from single cells that improves assembly through use of progressively increasing coverage cutoff. Used for single cell Illumina sequences, allows variable coverage datasets to be utilized with assembly of E. coli and S. aureus single cell reads. Assembles single cell genome of uncultivated SAR324 clade of Deltaproteobacteria.

Proper citation: Velvet-SC (RRID:SCR_004377) Copy   

•   Source: SciCrunch Registry

http://www.arabidopsis.org

Database of genetic and molecular biology data for the model higher plant Arabidopsis thaliana. Data available includes the complete genome sequence along with gene structure, gene product information, metabolism, gene expression, DNA and seed stocks, genome maps, genetic and physical markers, publications, and information about the Arabidopsis research community. Gene product function data is updated every two weeks from the latest published research literature and community data submissions. Gene structures are updated 1-2 times per year using computational and manual methods as well as community submissions of new and updated genes. TAIR also provides extensive linkouts from data pages to other Arabidopsis resources. The data can be searched, viewed and analyzed. Datasets can also be downloaded. Pages on news, job postings, conference announcements, Arabidopsis lab protocols, and useful links are provided.

Proper citation: TAIR (RRID:SCR_004618) Copy   

•   Source: SciCrunch Registry

http://www.genedb.org/Homepage/Lmajor

Database of the most recent sequence updates and annotations for the L. major genome. New annotations are constantly being added to keep up with published manuscripts and feedback from the Trypanosomatid research community. You may search by Protein Length, Molecular Mass, Gene Type, Date, Location, Protein Targeting, Transmembrane Helices, Product, GO, EC, Pfam ID, Curation and Comments, and Dbxrefs. BLAST and other tools are available. Leishmania species cause a spectrum of human diseases in tropical and subtropical regions of the world. We have sequenced the 36 chromosomes of the 32.8-megabase haploid genome of Leishmania major (Friedlin strain) and predict 911 RNA genes, 39 pseudogenes, and 8272 protein-coding genes, of which 36% can be ascribed a putative function. These include genes involved in host-pathogen interactions, such as proteolytic enzymes, and extensive machinery for synthesis of complex surface glycoconjugates. The Pathogen Genomics group at the Wellcome Trust Sanger Institute played a major role in sequencing the genome of Leishmania major (see Ivens et al.) Details of the centres involved and which chromosomes they sequenced, are given. The sequence data were obtained by adopting several parallel approaches, including complete cosmid sequencing, whole chromosome shotguns and/or BAC sequencing/skimming. The Leishmania parasite is an intracellular pathogen of the immune system targeting macrophages and dendritic cells. The disease Leishmaniasis affects the populations of 88 counties worldwide with symptoms ranging from disfiguring cutaneous and muco-cutaneous lesions that can cause widespread destruction of mucous membranes to visceral disease affecting the haemopoetic organs. In collaboration with GeneDB, the EuPathDB genomic sequence data and annotations are regularly deposited on TriTrypDB where they can be integrated with other datasets and queried using customized queries.

Proper citation: GeneDB Lmajor (RRID:SCR_004613) Copy   

•   Source: SciCrunch Registry

http://blast.ncbi.nlm.nih.gov/Blast.cgi

Web search tool to find regions of similarity between biological sequences. Program compares nucleotide or protein sequences to sequence databases and calculates statistical significance. Used for identifying homologous sequences.

Proper citation: NCBI BLAST (RRID:SCR_004870) Copy   

•   Source: SciCrunch Registry

http://www.ncbi.nlm.nih.gov/nucest

Nucleotide database as collection of sequences from several sources, including GenBank, RefSeq, TPA and PDB. Genome, gene and transcript sequence data provide the foundation for biomedical research and discovery.

Proper citation: Nucleotide database (RRID:SCR_004630) Copy   

•   Source: SciCrunch Registry

http://www.pantherdb.org/

System that classifies genes by their functions, using published scientific experimental evidence and evolutionary relationships to predict function even in absence of direct experimental evidence. Orthologs view is curated orthology relationships between genes for human, mouse, rat, fish, worm, and fly., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: PANTHER (RRID:SCR_004869) Copy   

•   Source: SciCrunch Registry

https://datashare.ed.ac.uk/handle/10283/3844

Genome transcriptome atlas by RNA in situ hybridization on sagittal sections of developing mouse at embryonic day 14.5. Consists of searchable database of annotated images that can be interactively viewed. Anatomy based expression profiles for coding genes and microRNAs, tissue specific genes. Expression data generated by using human and murine tissue arrays.

Proper citation: Eurexpress (RRID:SCR_005093) Copy   

•   Source: SciCrunch Registry

http://smart.embl.de/

Software tool for identification and annotation of genetically mobile domains and analysis of domain architectures.

Proper citation: SMART (RRID:SCR_005026) Copy   

•   Source: SciCrunch Registry

http://dgv.tcag.ca/dgv/app/home

Public repository that accepts direct submissions and provides archiving, accessioning and distribution of publicly available genomic structural variants, in all species. Variants are accessioned at the study and sample level, granting stable identifiers that can be used in publications. DGVa data is integrated with other EBI resources, including comprehensive EBI search and Ensembl genome browser. Exchanges data with companion database, dbVar, at National Center for Biotechnology Information.NOTE: since 2019 DGVa doesn't accept submissions. Please send the data for submission to European Variation Archive (EVA).

Proper citation: Database of Genomic Variants Archive (DGVa) (RRID:SCR_004896) Copy   

•   Source: SciCrunch Registry

http://phast.wishartlab.com/

A web server designed to rapidly and accurately identify, annotate and graphically display prophage sequences within bacterial genomes or plasmids. It accepts either raw DNA sequence data or partially annotated GenBank formatted data and rapidly performs a number of database comparisons as well as phage cornerstone feature identification steps to locate, annotate and display prophage sequences and prophage features. Relative to other prophage identification tools, PHAST is up to 40 times faster and up to 15% more sensitive. It is also able to process and annotate both raw DNA sequence data and Genbank files, provide richly annotated tables on prophage features and prophage quality and distinguish between intact and incomplete prophage. PHAST also generates downloadable, high quality, interactive graphics that display all identified prophage components in both circular and linear genomic views. Databases available for download include Virus DB, Prophage and virus DB, Bacteria DB, and PHAST result DB. Pre-calculated genomes for viewing are also available.

Proper citation: PHAge Search Tool (RRID:SCR_005184) Copy   

•   Source: SciCrunch Registry

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

A simple and easy to use high through-put analysis tool which can provide comprehensive annotation of both novel and known single nucleotide polymorphisms (SNPs) for any organism with a draft sequence and annotation. SNPdat makes possible analyses involving non-model organisms that are not supported by the vast majority of SNP annotation tools currently available. It is especially intended for use by researchers with limited bioinformatic experience.

Proper citation: SNPdat (RRID:SCR_005187) Copy   

•   Source: SciCrunch Registry