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http://www.yandell-lab.org/software/mwas.html

The MAKER Web Annotation Service (MWAS) is an easily configurable web-accessible genome annotation pipeline. It''''s purpose is to allow research groups with small to intermediate amounts of eukaryotic and prokaryotic genome sequence (i.e. BAC clones, small whole genomes, preliminary sequencing data, etc.) to independently annotate and analyze their data and produce output that can be loaded into a genome database. MWAS is build on the stand alone genome annotation pipeline MAKER, and users who wish to annotate larger datasets and whole genomes are free to download MAKER for use on their own systems. MWAS identifies repeats, aligns ESTs and proteins to a genome, produces ab-initio gene predictions and automatically synthesizes these data into gene annotations having evidence-based quality values. MWAS can also automatically train popular gene prediction algorithms for use on new genomes for which pre-existing information is limited. MAKER is a member of the Generic Model Organism Database (GMOD) project and output produced by this site can be directly used with other GMOD tools. Annotations can be directly viewed online by the user via GBrowse, JBrowse, and Apollo, or they can be downloaded for local analysis and integration into a genome database. MWAS also supplies summary statistics on sequence features via the Sequence Ontology tool SOBA. MWAS should prove especially useful for emerging model organism genome projects with minimal bioinformatics expertise and computer resources, since a user can produce final genome annotations without having to install and configure any software locally.

Proper citation: MAKER Web Annotation Service (RRID:SCR_005318) Copy   

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http://microbesonline.org/

MicrobesOnline is designed specifically to facilitate comparative studies on prokaryotic genomes. It is an entry point for operon, regulons, cis-regulatory and network predictions based on comparative analysis of genomes. The portal includes over 1000 complete genomes of bacteria, archaea and fungi and thousands of expression microarrays from diverse organisms ranging from model organisms such as Escherichia coli and Saccharomyces cerevisiae to environmental microbes such as Desulfovibrio vulgaris and Shewanella oneidensis. To assist in annotating genes and in reconstructing their evolutionary history, MicrobesOnline includes a comparative genome browser based on phylogenetic trees for every gene family as well as a species tree. To identify co-regulated genes, MicrobesOnline can search for genes based on their expression profile, and provides tools for identifying regulatory motifs and seeing if they are conserved. MicrobesOnline also includes fast phylogenetic profile searches, comparative views of metabolic pathways, operon predictions, a workbench for sequence analysis and integration with RegTransBase and other microbial genome resources. The next update of MicrobesOnline will contain significant new functionality, including comparative analysis of metagenomic sequence data. Programmatic access to the database, along with source code and documentation, is available at http://microbesonline.org/programmers.html.

Proper citation: MicrobesOnline (RRID:SCR_005507) Copy   

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http://www.GeneWeaver.org

Freely accessible phenotype-centered database with integrated analysis and visualization tools. It combines diverse data sets from multiple species and experiment types, and allows data sharing across collaborative groups or to public users. It was conceived of as a tool for the integration of biological functions based on the molecular processes that subserved them. From these data, an empirically derived ontology may one day be inferred. Users have found the system valuable for a wide range of applications in the arena of functional genomic data integration.

Proper citation: Gene Weaver (RRID:SCR_003009) Copy   

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http://ww2.sanbi.ac.za/Dbases.html

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 23, 2016. The STACKdb is knowledgebase generated by processing EST and mRNA sequences obtained from GenBank through a pipeline consisting of masking, clustering, alignment and variation analysis steps. The STACK project aims to generate a comprehensive representation of the sequence of each of the expressed genes in the human genome by extensive processing of gene fragments to make accurate alignments, highlight diversity and provide a carefully joined set of consensus sequences for each gene. The STACK project is comprised of the STACKdb human gene index, a database of virtual human transcripts, as well as stackPACK, the tools used to create the database. STACKdb is organized into 15 tissue-based categories and one disease category. STACK is a tool for detection and visualization of expressed transcript variation in the context of developmental and pathological states. The data system organizes and reconstructs human transcripts from available public data in the context of expression state. The expression state of a transcript can include developmental state, pathological association, site of expression and isoform of expressed transcript. STACK consensus transcripts are reconstructed from clusters that capture and reflect the growing evidence of transcript diversity. The comprehensive capture of transcript variants is achieved by the use of a novel clustering approach that is tolerant of sub-sequence diversity and does not rely on pairwise alignment. This is in contrast with other gene indexing projects. STACK is generated at least four times a year and represents the exhaustive processing of all publicly available human EST data extracted from GenBank. This processed information can be explored through 15 tissue-specific categories, a disease-related category and a whole-body index

Proper citation: Sequence Tag Alignment and Consensus Knowledgebase Database (RRID:SCR_002156) Copy   

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http://www.projects.roslin.ac.uk/sheepmap/front.html

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 23, 2016. The project aims to apply genome mapping research to sheep, utilizing previous research in sheep (in other countries) and in other species (in the UK and abroad) to the benefit of the UK sheep industry. The project itself uses existing breeding structures, knowledge of the sheep genome and experimental resources. It has three main aims: i) To use the Suffolk, Texel and Charollais Sire Referencing Schemes to detect and verify quantitative trait loci (QTLs) for growth and carcass composition traits ii) To investigate candidate genes and/or chromosomal regions for associations with production traits. iii) To investigate approaches for optimizing future genotyping strategies within the sire referencing schemes for practical and cost effective application of marker-assisted selection By using commercial breeding populations for the research, immediate application of beneficial results is possible. Potential benefits include increased genetic progress through marker assisted selection which utilizes the genotype information, correction of possible parentage errors (ultimately leading to additional genetic progress) and opportunities for using marker information for product certification. The project will benefit the UK sheep industry by the use of Marker Assisted Selection (MAS) utilizing QTL or gene variants identified in the project. Additional benefits may arise from parentage verification and correction of errors e.g. misallocation of lamb to ewe. In the longer term, opportunities may exist to use markers for quality control, tracing products to their source. The major advantage of the design of this project is that the results are immediately applicable to the breeding schemes within which the QTLs and/or genes are detected. The time lag in the application of the results that is often seen with experimental populations is minimized. The project requires close involvement with the Sire Reference Schemes, in return for their assistance the results have immediate benefit to animals within these groups.

Proper citation: UK Sheep Genome Mapping Project (RRID:SCR_002272) Copy   

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http://soybase.org

Professionally curated repository for genetics, genomics and related data resources for soybean that contains the most current genetic, physical and genomic sequence maps integrated with qualitative and quantitative traits. SoyBase includes annotated Williams 82 genomic sequence and associated data mining tools. The genetic and sequence views of the soybean chromosomes and the extensive data on traits and phenotypes are extensively interlinked. This allows entry to the database using almost any kind of available information, such as genetic map symbols, soybean gene names or phenotypic traits. The repository maintains controlled vocabularies for soybean growth, development, and traits that are linked to more general plant ontologies. Contributions to SoyBase or the Breeder''s Toolbox are welcome.

Proper citation: SoyBase (RRID:SCR_005096) Copy   

•   Source: SciCrunch Registry

http://www.patricbrc.org/portal/portal/patric/Home

A Bioinformatics Resource Center bacterial bioinformatics database and analysis resource that provides researchers with an online resource that stores and integrates a variety of data types (e.g. genomics, transcriptomics, protein-protein interactions (PPIs), three-dimensional protein structures and sequence typing data) and associated metadata. Datatypes are summarized for individual genomes and across taxonomic levels. All genomes, currently more than 10 000, are consistently annotated using RAST, the Rapid Annotations using Subsystems Technology. Summaries of different data types are also provided for individual genes, where comparisons of different annotations are available, and also include available transcriptomic data. PATRIC provides a variety of ways for researchers to find data of interest and a private workspace where they can store both genomic and gene associations, and their own private data. Both private and public data can be analyzed together using a suite of tools to perform comparative genomic or transcriptomic analysis. PATRIC also includes integrated information related to disease and PPIs. The PATRIC project includes three primary collaborators: the University of Chicago, the University of Manchester, and New City Media. The University of Chicago is providing genome annotations and a PATRIC end-user genome annotation service using their Rapid Annotation using Subsystem Technology (RAST) system. The National Centre for Text Mining (NaCTeM) at the University of Manchester is providing literature-based text mining capability and service. New City Media is providing assistance in website interface development. An FTP server and download tool are available.

Proper citation: Pathosystems Resource Integration Center (RRID:SCR_004154) Copy   

•   Source: SciCrunch Registry

http://smd.stanford.edu/cgi-bin/source/sourceSearch

SOURCE compiles information from several publicly accessible databases, including UniGene, dbEST, UniProt Knowledgebase, GeneMap99, RHdb, GeneCards and LocusLink. GO terms associated with LocusLink entries appear in SOURCE. The mission of SOURCE is to provide a unique scientific resource that pools publicly available data commonly sought after for any clone, GenBank accession number, or gene. SOURCE is specifically designed to facilitate the analysis of large sets of data that biologists can now produce using genome-scale experimental approaches Platform: Online tool

Proper citation: SOURCE (RRID:SCR_005799) Copy   

•   Source: SciCrunch Registry

http://cmr.jcvi.org/tigr-scripts/CMR/CmrHomePage.cgi

Database of all of the publicly available, complete prokaryotic genomes. In addition to having all of the organisms on a single website, common data types across all genomes in the CMR make searches more meaningful, and cross genome analysis highlight differences and similarities between the genomes. CMR offers a wide variety of tools and resources, all of which are available off of our menu bar at the top of each page. Below is an explanation and link for each of these menu options. * Genome Tools: Find organism lists as well as summary information and analyses for selected genomes. * Searches: Search CMR for genes, genomes, sequence regions, and evidence. * Comparative Tools: Compare multiple genomes based on a variety of criteria, including sequence homology and gene attributes. SNP data is also found under this menu. * Lists: Select and download gene, evidence, and genomic element lists. * Downloads: Download gene sequences or attributes for CMR organisms, or go to our FTP site. * Carts: Select genome preferences from our Genome Cart or download your Gene Cart genes. The Omniome is the relational database underlying the CMR and it holds all of the annotation for each of the CMR genomes, including DNA sequences, proteins, RNA genes and many other types of features. Associated with each of these DNA features in the Omniome are the feature coordinates, nucleotide and protein sequences (where appropriate), and the DNA molecule and organism with which the feature is associated. Also available are evidence types associated with annotation such as HMMs, BLAST, InterPro, COG, and Prosite, as well as individual gene attributes. In addition, the database stores identifiers from other centers such as GenBank and SwissProt, as well as manually curated information on each genome or each DNA molecule including website links. Also stored in the Omniome are precomputed homology data, called All vs All searches, used throughout the CMR for comparative analysis.

Proper citation: JCVI CMR (RRID:SCR_005398) Copy   

•   Source: SciCrunch Registry

http://vmd.vbi.vt.edu/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 15, 2013. Database covering a range of plant pathogenic oomycetes, fungi and bacteria primarily those under study at Virginia Bioinformatics Institute. The data comes from different sources and has genomes of 3 oomycetes pathogens: Phytophthora sojae, Phytophthora ramorum and Hyaloperonospora arabidopsidis. The genome sequences (95 MB for P.sojae and 65 MB for P.ramorum) were annotated with approximately 19,000 and approximately 16,000 gene models, respectively. Two different statistical methods were used to validate these gene models, Fickett''''s and a log-likelihood method. Functional annotation of the gene models is based on results from BlastX and InterProScan screens. From the InterProScan results, putative functions to 17,694 genes in P.sojae and 14,700 genes in P.ramorum could be assigned. An easy-to-use genome browser was created to view the genome sequence data, which opens to detailed annotation pages for each gene model. A community annotation interface is available for registered community members to add or edit annotations. There are approximately 1600 gene models for P.sojae and approximately 700 models for P.ramorum that have already been manually curated. A toolkit is provided as an additional resource for users to perform a variety of sequence analysis jobs.

Proper citation: VMD (RRID:SCR_004905) Copy   

•   Source: SciCrunch Registry

http://www.plexdb.org/index.php

PLEXdb (Plant Expression Database) is a unified gene expression resource for plants and plant pathogens. PLEXdb is a genotype to phenotype, hypothesis building information warehouse, leveraging highly parallel expression data with seamless portals to related genetic, physical, and pathway data. The integrated tools of PLEXdb allow investigators to use commonalities in plant biology for a comparative approach to functional genomics through use of large-scale expression profiling data sets.

Proper citation: PLEXdb - Plant Expression Database (RRID:SCR_006963) Copy   

•   Source: SciCrunch Registry

http://rarediseases.info.nih.gov/GARD/Default.aspx

Genetic and Rare Diseases Information Center (GARD) is a collaborative effort of two agencies of the National Institutes of Health, The Office of Rare Diseases Research (ORDR) and the National Human Genome Research Institute (NHGRI) to help people find useful information about genetic conditions and rare diseases. GARD provides timely access to experienced information specialists who can furnish current and accurate information about genetic and rare diseases. So far, GARD has responded to 27,635 inquiries on about 7,147 rare and genetic diseases. Requests come not only from patients and their families, but also from physicians, nurses and other health-care professionals. GARD also has proved useful to genetic counselors, occupational and physical therapists, social workers, and teachers who work with people with a genetic or rare disease. Even scientists who are studying a genetic or rare disease and who need information for their research have contacted GARD, as have people who are taking part in a clinical study. Community leaders looking to help people find resources for those with genetic or rare diseases and advocacy groups who want up-to-date disease information for their members have contacted GARD. And members of the media who are writing stories about genetic or rare diseases have found the information GARD has on hand useful, accurate and complete. GARD has information on: :- What is known about a genetic or rare disease. :- What research studies are being conducted. :- What genetic testing and genetic services are available. :- Which advocacy groups to contact for a specific genetic or rare disease. :- What has been written recently about a genetic or rare disease in medical journals. GARD information specialists get their information from: :- NIH resources. :- Medical textbooks. :- Journal articles. :- Web sites. :- Advocacy groups, and their literature and services. :- Medical databases.

Proper citation: Genetic and Rare Diseases Information Center (RRID:SCR_008695) Copy   

•   Source: SciCrunch Registry

http://www.novocraft.com/products/novoalign/

Software tool designed for mapping short reads onto a reference genome generated from Illumina, Ion Torrent, and 454 NGS platforms. Its features include paired end alignment, methylation status analysis, automatic base quality calibration, and in built adapter trimming and base quality trimming.

Proper citation: NovoAlign (RRID:SCR_014818) Copy   

•   Source: SciCrunch Registry

http://www.roslin.ed.ac.uk/alan-archibald/porcine-genome-sequencing-project/

Map of identifyied genes controlling traits of economic and welfare significance in the pig. The project objectives were to produce a genetic map with markers spaced at approximately 20 centiMorgan intervals over at least 90% of the pig genome; to produce a physical map with at least one distal and one proximal landmark locus mapped on each porcine chromosome arm and also genetically mapped; to develop a flow karyotype for the pig based on FACS sorted chromosomes; to develop PCR based techniques to enable rapid genotyping for polymorphic markers; to evaluate synteny conservation between pigs, man, mice and cattle; to develop and evaluate the statistical techniques required to analyze data from QTL mapping experiments and to plan and initiate the mapping of QTLs in the pig; to map loci affecting traits of economic and biological significance in the pig; and to develop the molecular tools to allow the future identification and cloning of mapped loci. Animal breeders currently assume that economically important traits such as growth, carcass composition and reproductive performance are controlled by an infinite number of genes each of infinitessimal effect. Although this model is known to be unrealistic, it has successfully underpinned the genetic improvement of livestock, including pigs, over recent decades. A map of the pig genome would allow the development of more realistic models of the genetic control of economic traits and the ultimately the identification of the major trait genes. This would allow the development of more efficient marker assisted selection which may be of particular value for traits such as disease resistance and meat quality.

Proper citation: Pig Genome Mapping (RRID:SCR_012884) Copy   

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http://www.aniseed.cnrs.fr/

Database of ascidian embryonic development at the level of the genome (cis-regulatory sequences, gene expression, protein annotation), of the cell (morphology, fate, induction, lineage) or of the whole embryo (anatomy, morphogenesis). Currently, four organism models are described in Aniseed: Ciona intestinalis, Ciona savignyi, Halocynthia roretzi and Phallusia mammillata.
This version supports four sets of Ciona intestinalis transcript models: JGI v1.0, KyotoGrail 2005, KH and ENSEMBL, all functionally annotated, and grouped into Aniseedv3.0 gene models. Users can explore their expression profiles during normal or manipulated development, access validated cis-regulatory regions, get the molecular tools used to assay gene function, or all articles related to the function, or regulation of a given gene. Known transcriptional regulators and targets are listed for each gene, as are the gene regulatory networks acting in individual anatomical territories.
ANISEED is a community tool, and the direct involvement of external contributors is important to optimize the quality of the submitted data. Virtual embryo: The 3D Virtual embryo is available to download in the download section of the website.

Proper citation: Ascidian Network for InSitu Expression and Embryological Data (RRID:SCR_013030) Copy   

•   Source: SciCrunch Registry

http://ccg.vital-it.ch/snp2tfbs

Collection of text files providing specific annotations for human single nucleotide polymorphisms (SNPs), namely whether they are predicted to abolish, create or change the affinity of one or several transcription factor (TF) binding sites. Used to investigate the molecular mechanisms underlying regulatory variation in the human genome. SNP2TFBS is also accessible over a web interface, enabling users to view the information provided for an individual SNP, to extract SNPs based on various search criteria, to annotate uploaded sets of SNPs or to display statistics about the frequencies of binding sites affected by selected SNPs.

Proper citation: SNP2TFBS (RRID:SCR_016885) Copy   

•   Source: SciCrunch Registry

http://home.cc.umanitoba.ca/~frist/Bit/

BIT Core at University of Manitoba, Manitoba, Canada, provides bioinformatics services, resources and collaborations. Support for Genome assembly and annotation, Microarray and Transcriptomics, Systems Biology and Pathway analysis, Databases, Data pipelines, Bioinformatics software, Custom software and programming, Project Wikis, Lab group computer management.

Proper citation: University of Manitoba Department of Plant Science Bio Information Technologies Lab Core Facility (RRID:SCR_017177) Copy   

•   Source: SciCrunch Registry

http://www.cbil.upenn.edu/cgi-bin/tess/tess

TESS is a web tool for predicting transcription factor binding sites in DNA sequences. It can identify binding sites using site or consensus strings and positional weight matrices from the TRANSFAC, JASPAR, IMD, and our CBIL-GibbsMat database. You can use TESS to search a few of your own sequences or for user-defined CRMs genome-wide near genes throughout genomes of interest. Search for CRMs Genome-wide: TESS now has the ability to search whole genomes for user defined CRMs. Try a search in the AnGEL CRM Searches section of the navigation bar.. You can search for combinations of consensus site sequences and/or PWMs from TRANSFAC or JASPAR. Search DNA for Binding Sites: TESS also lets you search through your own sequence for TFBS. You can include your own site or consensus strings and/or weight matrices in the search. Use the Combined Search under ''Site Searches'' in the menu or use the box for a quick search. TESS assigns a TESS job number to all sequence search jobs. The job results are stored on our server for a period of time specified in the search submit form. During this time you may recall the search results using the form on this page. TESS can also email results to you as a tab-delimited file suitable for loading into a spreadsheet program. Query for Transcription Factor Info: TESS also has data browsing and querying capabilities to help you learn about the factors that were predicted to bind to your sequence. Use the Query TRANSFAC or Query Matrices links above or use the search interface provided from the home page.

Proper citation: TESS: Transcription Element Search System (RRID:SCR_010739) Copy   

•   Source: SciCrunch Registry

http://jjwanglab.org/snvrap

The web portal provides comprehensive local database of human genome variants with a user-friendly web page that provides a one-stop annotating and funtonal prediction service which is both convenient and up-to-date. A query can be accepted as either a dbSNP Id or a chromosomal location and our system will instantly provide all the annotation information in an interactive LD panel. The system can also simultaneously prioritize this variant based on additive effect mode by corresponding annotation information and evaluate the variant effect that is then displayed in a prioritization tree. Furthermore, cohort sequencing continuously produces lots of un-annotated variants such as rare variants or de novo variants, and our system can even fit this data by accepting genomic coordinates (hg19) to offer maximal annotations. Main Functions Over 40 up-to-date annotation items for human single nucleotide variations; Functional prediction for different types of variants; Dynamic LD panel for both HapMap and 1000 Genomes Project populations; Prioritization score and tree viewer based on variant functional model.

Proper citation: SNVrap (RRID:SCR_010512) Copy   

•   Source: SciCrunch Registry

http://www.jiffynet.org/

Web based instant protein network modeler for newly sequenced species. Web server designed to instantly construct genome scale protein networks using protein sequence data. Provides network visualization, analysis pages and solution for instant network modeling of newly sequenced species.

Proper citation: JiffyNet (RRID:SCR_011954) Copy   

•   Source: SciCrunch Registry