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http://www.maizegdb.org

Collection of data related to crop plant and model organism Zea mays. Used to synthesize, display, and provide access to maize genomics and genetics data, prioritizing mutant and phenotype data and tools, structural and genetic map sets, and gene models and to provide support services to the community of maize researchers. Data stored at MaizeGDB was inherited from the MaizeDB and ZmDB projects. Sequence data are from GenBank. Data are searchable by phenotype, traits, Pests, Gel Pattern, and Mutant Images.

Proper citation: MaizeGDB (RRID:SCR_006600) Copy   

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https://www.phenx.org/Default.aspx?tabid=56

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on 05 01 2025. PhenX is a project to prioritize Phenotype and eXposure measures for Genome-wide Association Studies (GWAS). Leaders of the scientific community will assess and prioritize a broad range of domains relevant to genomics research and public health. The PhenX Steering Committee (SC), chaired by Dr. Jonathan Haines, provides leadership in the selection of domains and domain experts. Members of the SC include outstanding scientists from the research community and liaisons from the Institutes and Centers of the National Institutes of Health. Consensus measures for GWAS will have a direct impact on biomedical research and ultimately on public health. During the course of this project, up to 20 research domains will be examined, with up to 15 measures being recommended for use in future GWAS and other large-scale genomic research efforts. The goal is to maximize the benefits of future research by having comparable measures so that studies can be integrated. Each selected domain will be reviewed by a Working Group (WG) of scientists who are experts in the research area. A systematic review of the literature will guide the WGs selection of up to 15 high priority measures with standardized approaches for measurement. Selection criteria for the measures include factors such as validity, reproducibility, cost, feasibility, and burden to both investigators and participants. The scientific community will be asked to provide input on proposed measures. Consensus development is a key component of the project.

Proper citation: Consensus Measures for Phenotype and Exposure (RRID:SCR_006688) Copy   

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http://sourceforge.net/projects/gasic/

A method to correct read alignment results for the ambiguities imposed by similarities of genomes.

Proper citation: GASiC (RRID:SCR_006765) Copy   

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http://pre.ensembl.org/index.html

Database of genomes that are in the process of being annotated are provided as an early access site for users. Genomes are here when the initial BLAST analysis on a new assembly has been done but the gene build has not been completed. Owing to the preliminary nature of the data, Pre-Ensembl provides views of the assembly, BLAST against the assembly and download of portions of the assembly - and little else. A number of ready-made tools for processing your data are also available. In general a full Ensembl release takes months depending on how complex the data are and the time constraints of people in the team. Occasionally a more complete gene build will be released on this site, but without any comparative genomics, variation or other additional data. Many other species with fully annotated genomic data, more website features and documentation are available at www.ensembl.org

Proper citation: Pre Ensembl (RRID:SCR_006766) Copy   

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http://159.149.160.51/cscan/

Data resource that includes a large collection of genome-wide ChIP-Seq experiments performed on transcription factors (TFs), histone modifications, RNA polymerases and others. Enriched peak regions from the ChIP-Seq experiments are crossed with the genomic coordinates of a set of input genes, to identify which of the experiments present a statistically significant number of peaks within the input genes' loci. The input can be a cluster of co-expressed genes, or any other set of genes sharing a common regulatory profile. Users can thus single out which TFs are likely to be common regulators of the genes, and their respective correlations. Also, by examining results on promoter activation, transcription, histone modifications, polymerase binding and so on, users can investigate the effect of the TFs (activation or repression of transcription) as well as of the cell or tissue specificity of the genes' regulation and expression.

Proper citation: Cscan (RRID:SCR_006756) Copy   

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http://genome.ucsc.edu/ENCODE

Encyclopedia of DNA elements consisting of list of functional elements in human genome, including elements that act at protein and RNA levels, and regulatory elements that control cells and circumstances in which gene is active. Enables scientific and medical communities to interpret role of human genome in biology and disease. Provides identification of common cell types to facilitate integrative analysis and new experimental technologies based on high-throughput sequencing. Genome Browser containing ENCODE and Epigenomics Roadmap data. Data are available for entire human genome.

Proper citation: ENCODE (RRID:SCR_006793) Copy   

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http://www.1000genomes.org/

International collaboration producing an extensive public catalog of human genetic variation, including SNPs and structural variants, and their haplotype contexts, in an effort to provide a foundation for investigating the relationship between genotype and phenotype. The genomes of about 2500 unidentified people from about 25 populations around the world were sequenced using next-generation sequencing technologies. Redundant sequencing on various platforms and by different groups of scientists of the same samples can be compared. The results of the study are freely and publicly accessible to researchers worldwide. The consortium identified the following populations whose DNA will be sequenced: Yoruba in Ibadan, Nigeria; Japanese in Tokyo; Chinese in Beijing; Utah residents with ancestry from northern and western Europe; Luhya in Webuye, Kenya; Maasai in Kinyawa, Kenya; Toscani in Italy; Gujarati Indians in Houston; Chinese in metropolitan Denver; people of Mexican ancestry in Los Angeles; and people of African ancestry in the southwestern United States. The goal Project is to find most genetic variants that have frequencies of at least 1% in the populations studied. Sequencing is still too expensive to deeply sequence the many samples being studied for this project. However, any particular region of the genome generally contains a limited number of haplotypes. Data can be combined across many samples to allow efficient detection of most of the variants in a region. The Project currently plans to sequence each sample to about 4X coverage; at this depth sequencing cannot provide the complete genotype of each sample, but should allow the detection of most variants with frequencies as low as 1%. Combining the data from 2500 samples should allow highly accurate estimation (imputation) of the variants and genotypes for each sample that were not seen directly by the light sequencing. All samples from the 1000 genomes are available as lymphoblastoid cell lines (LCLs) and LCL derived DNA from the Coriell Cell Repository as part of the NHGRI Catalog. The sequence and alignment data generated by the 1000genomes project is made available as quickly as possible via their mirrored ftp sites. ftp://ftp.1000genomes.ebi.ac.uk ftp://ftp-trace.ncbi.nlm.nih.gov/1000genomes

Proper citation: 1000 Genomes: A Deep Catalog of Human Genetic Variation (RRID:SCR_006828) Copy   

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http://www.funnet.info/

Functional Analysis of Transcriptional Networks (FunNet) is designed as an integrative tool for analyzing gene co-expression networks built from microarray expression data. The analytical model implemented in this tool involves two abstraction layers: transcriptional (i.e. gene expression profiles) and functional (i.e. biological themes indicating the roles of the analyzed transcripts). A functional analysis technique, which relies on Gene Ontology and KEGG annotations, is applied to extract a list of relevant biological themes from microarray gene expression data. Afterwards multiple-instance representations are built to relate relevant biological themes to their annotated transcripts. An original non-linear dynamical model is used to quantify the contextual proximity of relevant genomic themes based on their patterns of propagation in the gene co-expression network (i.e. capturing the similarity of the expression profiles of the transcriptional instances of annotating themes). In the end an unsupervised multiple-instance spectral clustering procedure is used to explore the modular architecture of the co-expression network by grouping together biological themes demonstrating a significant relationship in the co-expression network. Functional and transcriptional representations of the co-expression network are provided, together with detailed information on the contextual centrality of related transcripts and genomic themes. FunNet is provided both as a web-based tool and as a standalone R package. The standalone R implementation can be run on any operating system for which an R environment implementation is available (Windows, Mac OS, various flavors of Linux and Unix) and can be downloaded from the FunNet website, or from the worldwide mirrors of CRAN. Both implementations of the FunNet tool are provided freely under the GNU General Public License 2.0. Platform: Online tool, Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: FunNet - Transcriptional Networks Analysis (RRID:SCR_006968) Copy   

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http://humancyc.org/

The HumanCyc database describes human metabolic pathways and the human genome. By presenting metabolic pathways as an organizing framework for the human genome, HumanCyc provides the user with an extended dimension for functional analysis of Homo sapiens at the genomic level. A computational pathway analysis of the human genome assigned human enzymes to predicted metabolic pathways. Pathway assignments place genes in their larger biological context, and are a necessary step toward quantitative modeling of metabolism. HumanCyc contains the complete genome sequence of Homo sapiens, as presented in Build 31. Data on the human genome from Ensembl, LocusLink and GenBank were carefully merged to create a minimally redundant human gene set to serve as an input to SRI''s PathoLogic software, which generated the database and predicted Homo sapiens metabolic pathways from functional information contained in the genome''s annotation. SRI did not re-annotate the genome, but worked with the gene function assignments in Ensembl, LocusLink, and GenBank. The resulting pathway/genome database (PGDB) includes information on 28,783 genes, their products and the metabolic reactions and pathways they catalyze. Also included are many links to other databases and publications. The Pathway Tools software/database bundle includes HumanCyc and the Pathway Tools software suite and is available under license. This form of HumanCyc is faster and more powerful than the Web version.

Proper citation: HumanCyc: Encyclopedia of Homo sapiens Genes and Metabolism (RRID:SCR_007050) Copy   

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http://tritrypdb.org/tritrypdb/

An integrated genomic and functional genomic database providing access to genome-scale datasets for kinetoplastid parasites, and supporting a variety of complex queries driven by research and development needs. Currently, TriTrypDB integrates datasets from Leishmania braziliensis, L. infantum, L. major, L. tarentolae, Trypanosoma brucei and T. cruzi. Users may examine individual genes or chromosomal spans in their genomic context, including syntenic alignments with other kinetoplastid organisms. Data within TriTrypDB can be interrogated utilizing a sophisticated search strategy system that enables a user to construct complex queries combining multiple data types. All search strategies are stored, allowing future access and integrated searches. ''''User Comments'''' may be added to any gene page, enhancing available annotation; such comments become immediately searchable via the text search, and are forwarded to curators for incorporation into the reference annotation when appropriate. TriTrypDB provides programmatic access to its searches, via REST Web Services. The result of a web service request is a list of records (genes, ESTs, etc) in either XML or JSON format. REST services can be executed in a browser by typing a specific URL. TriTrypDB and its continued development are possible through the collaborative efforts between EuPathDB, GeneDB and colleagues at the Seattle Biomedical Research Institute (SBRI).

Proper citation: TriTrypDB (RRID:SCR_007043) Copy   

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http://yetfasco.ccbr.utoronto.ca/

Collection of all available transcription factor (TF) specificities for the yeast Saccharomyces cerevisiae in Position Frequency Matrix (PFM) or Position Weight Matrix (PWM) formats. The specificities are evaluated for quality using several metrics. With this website, you can scan sequences with the motifs to find where potential binding sites lie, inspect precomputed genome-wide binding sites, find which TFs have similar motifs to one you have found, and download the collection of motifs. Submissions are welcome.

Proper citation: YeTFaSCo (RRID:SCR_006893) Copy   

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http://rgd.mcw.edu/rgdCuration/?module=portal&func=show&name=nuro

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 12,2023. Portal that provides researchers with easy access to data on rat genes, QTLs, strain models, biological processes and pathways related to neurological diseases. This resource also includes dynamic data analysis tools.

Proper citation: Rat Genome Database: Neurological Disease Portal (RRID:SCR_008685) Copy   

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http://www.tutegenomics.com/

A robust, secure, medical-grade, web application that lives in the cloud and has the ability to analyze and annotate entire human genomes in a rapid and cost-effective way.

Proper citation: Tute Genomics (RRID:SCR_008672) Copy   

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http://roadmapepigenomics.org/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 11, 2022. Project for human epigenomic data from experimental pipelines built around next-generation sequencing technologies to map DNA methylation, histone modifications, chromatin accessibility and small RNA transcripts in stem cells and primary ex vivo tissues selected to represent normal counterparts of tissues and organ systems frequently involved in human disease. Consortium expects to deliver collection of normal epigenomes that will provide framework or reference for comparison and integration within broad array of future studies. Consortium is also committed to development, standardization and dissemination of protocols, reagents and analytical tools to enable research community to utilize, integrate and expand upon this body of data.

Proper citation: Roadmap Epigenomics Project (RRID:SCR_008924) Copy   

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http://research-pub.gene.com/gmap/

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 29, 2016. A software program for mapping and aligning cDNA sequences to a genome. The program maps and aligns a single sequence with minimal startup time and memory requirements, and provides fast batch processing of large sequence sets. The program generates accurate gene structures, even in the presence of substantial polymorphisms and sequence errors, without using probabilistic splice site models. Methodology underlying the program includes a minimal sampling strategy for genomic mapping, oligomer chaining for approximate alignment, sandwich DP for splice site detection, and microexon identification with statistical significance testing.

Proper citation: GMAP (RRID:SCR_008992) Copy   

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https://www.mtocdb.org/?next=/browse/results/

A database of over 300 Electron Microscopy (EM) images of centrioles and centriole related structures from almost 60 species, described by a controlled vocabulary allowing detailed description of the observed structures. This knowledge is supplemented by a manually curated list of proteins known to be involved in centriole assembly, their (putative) orthologs, and localization information. mtocDB aims to characterize the naturally occurring morphological variation observed in centrioles and centriole associated structure alongside molecular information on the proteins involved in their assembly. Examining these in an evolutionary context will allow the cell biology community to infer meaningful relationships between cellular assembly mechanisms and the structures they form. This community resource for cell biologists interested in the the evolution of centrioles and centriole related structures aims to bridge the gap between structural morphology and molecular function by examining naturally occurring structural variation in a phylogenomic context. Centrioles are cylindrical microtubule arrays required for stability and duplication of the centrosome in animal cells, and for the assembly of cilia and flagella in many eukaryotes. The presence of centrioles throughout most eukaryotic branches suggests that this structure was present in the last eukaryotic common ancestor. Although centrioles show a typically well conserved structure, they can perform several functions and display a diversity of accessory structures. However, this diversity is not properly classified beyond model organisms, and the information contained in decades of electronic microscopy of other organisms remains untapped.

Proper citation: mtocDB (RRID:SCR_008933) Copy   

•   Source: SciCrunch Registry

http://gwas.biosciencedbc.jp/cgi-bin/hvdb/hv_top.cgi

A repository database to achieve continuous and intensive management of GWAS data and variation data identified by next generation sequencing (NGS) and data-sharing among researchers. In this database, variations including short/long insertions / deletions and structural variations related to disease susceptibility, virus resistance, and drug response are registered along with statistical genetic results and simple clinical characteristics to clarify the locus specific characteristics. Currently this database contains information extracted from scientific papers and next generation sequencing results and other small scale experimental results of several research laboratories. Mutation data submission is greatly appreciated.

Proper citation: Human Variation DB (RRID:SCR_009014) Copy   

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http://hadvwg.gmu.edu/

The Human Adenovirus Type Classification coordinates the naming of candidate new types, prior to manuscript submission for peer review. This resource contains a method of submitting candidate HAdV, criteria for a new HAdV type, and a Serotyping tool, which displays all potential types corresponding to the query serotype entered by a user. The criteria are based on discussions at the International Adenovirus Meeting (Dobog��k, Hungary; 26-30 April, 2009) and the NIH Human Adenovirus Working Group Workshop (Bethesda, MD. USA; 3 February 2011), which are summarized in a Letter to the Editor.

Proper citation: Human Adenovirus Type Classification (RRID:SCR_005753) Copy   

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http://www.clipz.unibas.ch/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 20,2019.Database and analysis environment for experimentally determined binding sites of RNA-binding proteins. It supports the automatic functional annotation of short reads resulting primarily from crosslinking and immunoprecipitation experiments (CLIP) performed with RNA-binding proteins in order to identify the binding sites of these proteins. The functional annotation could be also applied to short reads resulting from other types of experiments such as mRNA-Seq, Digital Gene Expression, small RNA cloning, etc. The platform enables visualization and mining of individual data sets as well as analysis involving multiple experimental data sets. The platform can support collaborative projects involving multiple users and groups of users as well as public and private datasets.

Proper citation: CLIPZ (RRID:SCR_005755) Copy   

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http://www.nematodes.org/nematodegenomes/index.php/Main_Page

A collaborative wiki that collates information on completed, ongoing and planned genome and transcriptome sequencing projects on species from phylum Nematoda. The intention is to encourage genome sequencing across the diversity of the phylum Nematoda. Wiki includes: * Published complete nematode genomes: A dynamically generated table of all species for which the genome is published. * Nematode species with genomes in progress: A dynamically generated table of all species for which a genome project is underway. Users may add species to the list * Proposed nematode genome projects: To propose a species for genome sequencing, edit its species page, and set the genome project status to proposed. * BLAST server: Search a number of the nematode-genomes-in-progress with genes of your choice. Currently there are 12 draft genomes available... * Genomes with Data available: Genomes with data available for download. Users may add more data URLs to strain pages or update the URLs.

Proper citation: 959 Nematode Genomes (RRID:SCR_006068) Copy   

•   Source: SciCrunch Registry