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http://redfly.ccr.buffalo.edu

Curated collection of known Drosophila transcriptional cis-regulatory modules (CRMs) and transcription factor binding sites (TFBSs). Includes experimentally verified fly regulatory elements along with their DNA sequence, associated genes, and expression patterns they direct. Submission of experimentally verified cis-regulatory elements that are not included in REDfly database are welcome.

Proper citation: REDfly Regulatory Element Database for Drosophilia (RRID:SCR_006790) Copy   

•   Source: SciCrunch Registry

http://compbio.dfci.harvard.edu/tgi/

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 19,2019.The goal of The Gene Index Project is to use the available Expressed Sequence Transcript (EST) and gene sequences, along with the reference genomes wherever available, to provide an inventory of likely genes and their variants and to annotate these with information regarding the functional roles played by these genes and their products. The promise of genome projects has been a complete catalog of genes in a wide range of organisms. While genome projects have been successful in providing reference genome sequences, the problem of finding genes and their variants in genomic sequence remains an ongoing challenge. TGI has created an inventory that contains genes and their variants together with description. In addition, this resource is attempting to use these catalogs to find links between genes and pathways in different species and to provide lists of features within completed genomes that can aid in the understanding of how gene expression is regulated. DATABASES *Eukaryotic Gene Orthologues (formerly known as TOGA - TIGR Orthologous Gene Alignment): Eukaryotic Gene Orthologues (EGO) at DFGI are generated by pair-wise comparison between the Tentative Consensus (TC) sequences that comprise the Dana Farber Gene Indices from individual organisms. The reciprocal pairs of the best match were clustered into individual groups and multiple sequence alignments were displayed for each group. *GeneChip Oncology Database (GCOD):Cancer gene expression database is a collection of publicly available microarray expression data on Affymetrix GeneChip Arrays related to human cancers. Currently only datasets with available raw data (Affymetrix .CEL files) are processed. All processed datasets were subjected to extensive manual curation, uniform processing and consistent quality control. You can browse the experiments in our collection, perform statistical analysis, and download processed data; or to search gene expression profiles using Entrez gene symbol, Unigene ID, or Affymetrix probeset ID. *Gene Indices: As of July 1, 2008, there are 111 publicly available gene indices. They are separated into 4 categories for better organization and easier access. Animal: 41, Plant: 45, Protist: 15, Fungal: 10 *Genomic Maps: Human, mouse, rat, chicken, drosophila melanogaster, zebrafish, mosquito, caenorhabditis elegans, Arabidopsis thaliana, rice, yeast, fission yeast Dana-Farber Cancer Institute (DFCI) Gene Indices Software Tools: *TGI Clustering tools (TGICL): a software system for fast clustering of large EST datasets. *GICL: this package contains the scripts and all the necessary pre-compiled binaries for 32bit Linux systems. *clview: an assembly file viewer. *SeqClean:a script for automated trimming and validation of ESTs or other DNA sequences by screening for various contaminants, low quality and low-complexity sequences. *cdbfasta/cdbyank: fast indexing/retrieval of fasta records from flat file databases. *DAS/XML Genomic Viewer The Genomic viewer borrows modules from http://www.biodas.org (lstein (at) cshl.org) & http://webreference.com.

Proper citation: Gene Index Project (RRID:SCR_002148) Copy   

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http://www.aspgd.org/

Database of genetic and molecular biological information about the filamentous fungi of the genus Aspergillus including information about genes and proteins of Aspergillus nidulans and Aspergillus fumigatus; descriptions and classifications of their biological roles, molecular functions, and subcellular localizations; gene, protein, and chromosome sequence information; tools for analysis and comparison of sequences; and links to literature information; as well as a multispecies comparative genomics browser tool (Sybil) for exploration of orthology and synteny across multiple sequenced Sgenus species. Also available are Gene Ontology (GO) and community resources. Based on the Candida Genome Database, the Aspergillus Genome Database is a resource for genomic sequence data and gene and protein information for Aspergilli. Among its many species, the genus contains an excellent model organism (A. nidulans, or its teleomorph Emericella nidulans), an important pathogen of the immunocompromised (A. fumigatus), an agriculturally important toxin producer (A. flavus), and two species used in industrial processes (A. niger and A. oryzae). Search options allow you to: *Search AspGD database using keywords. *Find chromosomal features that match specific properties or annotations. *Find AspGD web pages using keywords located on the page. *Find information on one gene from many databases. *Search for keywords related to a phenotype (e.g., conidiation), an allele (such as veA1), or an experimental condition (e.g., light). Analysis and Tools allow you to: *Find similarities between a sequence of interest and Aspergillus DNA or protein sequences. *Display and analyze an Aspergillus sequence (or other sequence) in many ways. *Navigate the chromosomes set. View nucleotide and protein sequence. *Find short DNA/protein sequence matches in Aspergillus. *Design sequencing and PCR primers for Aspergillus or other input sequences. *Display the restriction map for a Aspergillus or other input sequence. *Find similarities between a sequence of interest and fungal nucleotide or protein sequences. AspGD welcomes data submissions.

Proper citation: ASPGD (RRID:SCR_002047) Copy   

•   Source: SciCrunch Registry

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

Database of high-throughput genome sequences from large-scale genome sequencing centers, including unfinished and finished sequences. It was created to accommodate a growing need to make unfinished genomic sequence data rapidly available to the scientific community in a coordinated effort among the International Nucleotide Sequence databases, DDBJ, EMBL, and GenBank. Sequences are prepared for submission by using NCBI's software tools Sequin or tbl2asn. Each center has an FTP directory into which new or updated sequence files are placed. Sequence data in this division are available for BLAST homology searches against either the htgs database or the month database, which includes all new submissions for the prior month. Unfinished HTG sequences containing contigs greater than 2 kb are assigned an accession number and deposited in the HTG division. A typical HTG record might consist of all the first-pass sequence data generated from a single cosmid, BAC, YAC, or P1 clone, which together make up more than 2 kb and contain one or more gaps. A single accession number is assigned to this collection of sequences, and each record includes a clear indication of the status (phase 1 or 2) plus a prominent warning that the sequence data are unfinished and may contain errors. The accession number does not change as sequence records are updated; only the most recent version of a HTG record remains in GenBank.

Proper citation: High Throughput Genomic Sequences Division (RRID:SCR_002150) Copy   

•   Source: SciCrunch Registry

http://www.doe-mbi.ucla.edu/

The UCLA-DOE Institute for Genomics and Proteomics carries out research in bioenergy, structural biology, genomics and proteomics, consistent with the research mission of the United States Department of Energy. Major interests of the 12 Principal Investigators and 9 Associate Members include systems approaches to organisms, structural biology, bioinformatics, and bioenergetic systems. The Institute sponsors 5 Core Technology Centers, for X-ray and NMR structural determination, bioinformatics and computation, protein expression and purification, and biochemical instrumentation. Services offered by this Institute: - Databases: * DIP (The Database of Interacting Proteins): The DIPTM database catalogs experimentally determined interactions between proteins. It combines information from a variety of sources to create a single, consistent set of protein-protein interactions. * ProLinks Database of Functional Linkages: The Prolinks database is a collection of inference methods used to predict functional linkages between proteins. These methods include the Phylogenetic Profile method which uses the presence and absence of proteins across multiple genomes to detect functional linkages; the Gene Cluster method, which uses genome proximity to predict functional linkage; Rosetta Stone, which uses a gene fusion event in a second organism to infer functional relatedness; and the Gene Neighbor method, which uses both gene proximity and phylogenetic distribution to infer linkage. - Data-to-Structure Servers: * SAVEs Structure Verification Server * Merohedral Twinning Test Server * SER Surface Entropy Reduction Server * VERIFY3D Structure Verification Server * ERRAT Structure Verification Server - Structure-to-Function Servers: * ProKnow Protein Functionator * Hot Patch Functional Site Locator

Proper citation: University of California at Los Angeles - Department of Energy Institute for Genomics and Proteomics (RRID:SCR_001921) Copy   

•   Source: SciCrunch Registry

http://mips.gsf.de/genre/proj/yeast/index.jsp

The MIPS Comprehensive Yeast Genome Database (CYGD) aims to present information on the molecular structure and functional network of the entirely sequenced, well-studied model eukaryote, the budding yeast Saccharomyces cerevisiae. In addition, the data of various projects on related yeasts are used for comparative analysis.

Proper citation: CYGD - Comprehensive Yeast Genome Database (RRID:SCR_002289) Copy   

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http://microbes.ucsc.edu/cgi-bin/hgGateway?db=neisMeni_MC58_1

Portal contains detailed information for Neisseria meningitidis MC58. Information include DNA molecule summary, primary annotation summary, and taxonomy. It is a tool that allows the researcher to access all of the bacterial genome sequences completed to date. Users may access information on all of the bacterial genomes or any subset of them. Information in the website about its DNA molecule includes: total number of DNA molecules, total size of all DNA molecules, number of primary annotation coding bases, and number of G + C bases. Its primary annotation summary include: total genes, protein coding genes, tRNA genes, and rRNA genes. Sponsors: The CMR was previously funded by two grants, one from the U.S. Department of Energy (DOE) and one from the National Science Foundation (NSF). It is currently partially funded by a Microbial Sequence Center (MSC) grant from the National Institute of Allergy and Infectious Diseases (NIAID)

Proper citation: Neisseria meningitidis MC58 Genome Page (RRID:SCR_002200) Copy   

•   Source: SciCrunch Registry

http://insulatordb.uthsc.edu/

A comprehensive collection of experimentally determined and computationally predicted CCCTC-binding factor (CTCF) binding sites (CTCFBS) from the literature. The database is designed to facilitate the studies on insulators and their roles in demarcating functional genomic domains. The CTCFBS Prediction Tool allows users to scan sequences for the single best match to CTCF position weight matrices. Currently (March 2014), the database contains almost 15 million experimentally determined CTCF binding sites across several species. CTCF binding sites were collected from published papers containing CTCF binding sites identified using ChIPSeq or similar methods, data from the ENCODE project, and a set of approximately 100 manually curated binding sites identified by low-throughput experiments. Users can browse insulator sequence features, function annotations, genomic contexts including histone methylation profiles, flanking gene expression patterns and orthologous regions in other mammalian genomes. Users can also retrieve data by text search, sequence search and genomic range search.

Proper citation: CTCFBSDB (RRID:SCR_002279) Copy   

•   Source: SciCrunch Registry

http://www.ark-genomics.org/

Portal for studies of genome structure and genetic variation, gene expression and gene function. Provides services including DNA sequencing of model and non-model genomes using both Next Generation and Sanger sequencing , Gene expression analysis using both microarrays and Next Generation Sequencing, High throughput genotyping of SNP and copy number variants, Data collection and analysis supported in-house high performance computing facilities and expertise, Extensive EST clone collections for a number of animal species, all of commercially available microarray tools from Affymetrix, Illumina, Agilent and Nimblegen, Parentage testing using microsatellites and smaller SNP panels. ARK-Genomics has developed network of researchers whom they support through each stage of their genomics research, from grant application, experimental design and technology selection, performing wet laboratory protocols, through to analysis of data often in conjunction with commercial partners.

Proper citation: ARK-Genomics: Centre for Functional Genomics (RRID:SCR_002214) Copy   

•   Source: SciCrunch Registry

http://www.ddbj.nig.ac.jp

Maintains and provides archival, retrieval and analytical resources for biological information. Central DDBJ resource consists of public, open-access nucleotide sequence databases including raw sequence reads, assembly information and functional annotation. Database content is exchanged with EBI and NCBI within the framework of the International Nucleotide Sequence Database Collaboration (INSDC). In 2011, DDBJ launched two new resources: DDBJ Omics Archive and BioProject. DOR is archival database of functional genomics data generated by microarray and highly parallel new generation sequencers. Data are exchanged between the ArrayExpress at EBI and DOR in the common MAGE-TAB format. BioProject provides organizational framework to access metadata about research projects and data from projects that are deposited into different databases.

Proper citation: DNA DataBank of Japan (DDBJ) (RRID:SCR_002359) Copy   

•   Source: SciCrunch Registry

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

Database that organizes information on genomes including sequences, maps, chromosomes, assemblies, and annotations in six major organism groups: Archaea, Bacteria, Eukaryotes, Viruses, Viroids, and Plasmids. Genomes of over 1,200 organisms can be found in this database, representing both completely sequenced organisms and those for which sequencing is in progress. Users can browse by organism, and view genome maps and protein clusters. Links to other prokaryotic and archaeal genome projects, as well as BLAST tools and access to the rest of the NCBI online resources are available.

Proper citation: NCBI Genome (RRID:SCR_002474) Copy   

•   Source: SciCrunch Registry

https://cghub.ucsc.edu/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on March 17, 2022. A secure repository for storing, cataloging, and accessing cancer genome sequences, alignments, and mutation information from the Cancer Genome Atlas (TCGA) consortium and related projects. CGHub gives scientific researchers the statistical power of large cancer genome datasets to attack the molecular complexity of cancer.

Proper citation: Cancer Genomics Hub (RRID:SCR_002657) Copy   

•   Source: SciCrunch Registry

http://deweylab.biostat.wisc.edu/rsem/

Software package for quantifying gene and isoform abundances from single end or paired end RNA Seq data. Accurate transcript quantification from RNA Seq data with or without reference genome. Used for accurate quantification of gene and isoform expression from RNA-Seq data.

Proper citation: RSEM (RRID:SCR_000262) Copy   

•   Source: SciCrunch Registry

http://gst.tennessee.edu/

Graduate School of Genome Science and Technology (GST) is a Life Science graduate program founded on two premises. First, whole-genome sequences and related large-scale datasets have transformed how we perform biological research, a trend that is gathering momentum and is anticipated to frame the way the biology research is accomplished for many years to come. Second, advances in technology, whether at the level of instrumentation, computation, or wet lab reagents, have long been a powerful driving force in biology. The GST program is home to faculty mentors from many walks of life. The virulence factors of pathogenic fungi and the engineering of photosynthetic reaction complexes for bioenergy harvesting are just two examples from the cornucopia of research projects being pursued in GST.

Proper citation: University of Tennessee Genome Science and Technology Graduate Program (RRID:SCR_000038) Copy   

•   Source: SciCrunch Registry

https://sourceforge.net/projects/popbam/

A tool to perform evolutionary or population-based analyses of next-generation sequencing data. POPBAM takes a BAM file as its input and can compute many widely used evolutionary genetics measures in sliding windows across a genome.

Proper citation: POPBAM (RRID:SCR_000464) Copy   

•   Source: SciCrunch Registry

http://bejerano.stanford.edu/phenotree/

Web server to search for genes involved in given phenotypic difference between mammalian species. The mouse-referenced multiple alignment data files used to perform the forward genomics screen is also available. The webserver implements one strategy of a Forward Genomics approach aiming at matching phenotype to genotype. Forward genomics matches a given pattern of phenotypic differences between species to genomic differences using a genome-wide screen. In the implementation, the divergence of the coding region of genes in mammals is measured. Given an ancestral phenotypic trait that is lost in independent mammalian lineages, it is shown that searching for genes that are more diverged in all trait-loss species can discover genes that are involved in the given phenotype.

Proper citation: Phenotree (RRID:SCR_003591) Copy   

•   Source: SciCrunch Registry

http://nematode.lab.nig.ac.jp/

Expression pattern map of the 100Mb genome of the nematode Caenorhabditis elegans through EST analysis and systematic whole mount in situ hybridization. NEXTDB is the database to integrate all information from their expression pattern project and to make the data available to the scientific community. Information available in the current version is as follows: * Map: Visual expression of the relationships among the cosmids, predicted genes and the cDNA clones. * Image: In situ hybridization images that are arranged by their developmental stages. * Sequence: Tag sequences of the cDNA clones are available. * Homology: Results of BLASTX search are available. Users of the data presented on our web pages should not publish the information without our permission and appropriate acknowledgment. Methods are available for: * In situ hybridization on whole mount embryos of C.elegans * Protocols for large scale in situ hybridization on C.elegans larvae

Proper citation: NEXTDB (RRID:SCR_004480) Copy   

•   Source: SciCrunch Registry

http://stemcellcommons.org/

Open source environment for sharing, processing and analyzing stem cell data bringing together stem cell data sets with tools for curation, dissemination and analysis. Standardization of the analytical approaches will enable researchers to directly compare and integrate their results with experiments and disease models in the Commons. Key features of the Stem Cell Commons * Contains stem cell related experiments * Includes microarray and Next-Generation Sequencing (NGS) data from human, mouse, rat and zebrafish * Data from multiple cell types and disease models * Carefully curated experimental metadata using controlled vocabularies * Export in the Investigation-Study-Assay tabular format (ISA-Tab) that is used by over 30 organizations worldwide * A community oriented resource with public data sets and freely available code in public code repositories such as GitHub Currently in development * Development of Refinery, a novel analysis platform that links Commons data to the Galaxy analytical engine * ChIP-seq analysis pipeline (additional pipelines in development) * Integration of experimental metadata and data files with Galaxy to guide users to choose workflows, parameters, and data sources Stem Cell Commons is based on open source software and is available for download and development.

Proper citation: Stem Cell Commons (RRID:SCR_004415) Copy   

•   Source: SciCrunch Registry

http://www.genedb.org/Homepage/Tbruceibrucei927

Database of the most recent sequence updates and annotations for the T. brucei 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. T. brucei possesses a two-unit genome, a nuclear genome and a mitochondrial (kinetoplast) genome with a total estimated size of 35Mb/haploid genome. The nuclear genome is split into three classes of chromosomes according to their size on pulsed-field gel electrophoresis, 11 pairs of megabase chromosomes (0.9-5.7 Mb), intermediate (300-900 kb) and minichromosomes (50-100 kb). The T. brucei genome contains a ~0.5Mb segmental duplication affecting chromosomes 4 and 8, which is responsible for some 75 gene duplicates unique to this species. A comparative chromosome map of the duplicons can be accessed here (PubmedID 18036214). Protozoan parasites within the species Trypanosoma brucei are the etiological agent of human sleeping sickness and Nagana in animals. Infections are limited to patches of sub-Saharan Africa where insects vectors of the Glossina genus are endemic. The most recent estimates indicate between 50,000 - 70,000 human cases currently exist, with 17 000 new cases each year (WHO Factsheet, 2006). 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 Tbrucei (RRID:SCR_004786) Copy   

•   Source: SciCrunch Registry

http://www.osc.riken.jp/english/

Omics Science Center is aiming to develop a comprehensive system called Life Science Accelerator(LSA) for the advancement of omics research. The LSA is a comprehensive system consists of biological resources, human resources, technologies, know-how, and essential administrative ability. Ultimate goal of LSA is to support and accelerate the advancement in life science research. Omics is the comprehensive study of molecules in living organisms. The complete sequencing of genomes (the complete set of genes in an organism) has enabled rapid developments in the collection and analysis of various types of comprehensive molecular data such as transcriptomes (the complete set of gene expression data) and proteomes (the complete set of intracellular proteins). Fundamental omics research aims to link these omics data to molecular networks and pathways in order to advance the understanding of biological phenomena as systems at the molecular level.

Proper citation: RIKEN Omics Science Center (RRID:SCR_008241) Copy   

•   Source: SciCrunch Registry