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http://swissregulon.unibas.ch/fcgi/sr/swissregulon

A database of genome-wide annotations of regulatory sites. The predictions are based on Bayesian probabilistic analysis of a combination of input information including: * Experimentally determined binding sites reported in the literature. * Known sequence-specificities of transcription factors. * ChIP-chip and ChIP-seq data. * Alignments of orthologous non-coding regions. Predictions were made using the PhyloGibbs, MotEvo, IRUS and ISMARA algorithms developed in their group, depending on the data available for each organism. Annotations can be viewed in a Gbrowse genome browser and can also be downloaded in flat file format.

Proper citation: SwissRegulon (RRID:SCR_005333) Copy   

•   Source: SciCrunch Registry

http://ssd.rbvi.ucsf.edu/

The SSD has been developed to address the need for resources and tools for understanding large sets of superpositions in order to understand evolutionary relationships and to make predictions of function. We have therefore created the Structure Superposition Database (SSD) for accessing, viewing and understanding large sets of structure superposition data. It contains the results of pairwise, all-by-all superpositions of a representative set of 115 (beta/alpha) barrel structures (TIM barrels). The initial implementation of the SSD contains the results of pairwise, all-by-all superpositions of a representative set of 115 (/alpha)8 barrel structures (TIM barrels). Future plans call for extending the database to include representative structure superpositions for many additional folds. The SSD can be browsed with a user interface module developed as an extension to Chimera, an extensible molecular modeling program. Features of the user interface module facilitate viewing multiple superpositions together.

Proper citation: Structure Superposition Database (RRID:SCR_005236) Copy   

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http://transpogene.tau.ac.il/

A publicly available database of Transposed elements (TEs) which are located within protein-coding genes of 7 organisms: human, mouse, chicken, zebrafish, fruilt fly, nematode and sea squirt. Using TranspoGene the user can learn about the many aspects of the effect these TEs have on their hosting genes, such as: exonization events (including alternative splicing-related data), insertion of TEs into introns, exons, and promoters, specific location of the TE over the gene, evolutionary divergence of the TE from its consensus sequence and involvement in diseases. TranspoGene database is quickly searchable through its website, enables many kinds of searches and is available for download. TranspoGene contains information regarding specific type and family of the TEs, genomic and mRNA location, sequence, supporting transcript accession and alignment to the TE consensus sequence. The database also contains host gene specific data: gene name, genomic location, Swiss-Prot and RefSeq accessions, diseases associated with the gene and splicing pattern. The TranspoGene and microTranspoGene databases can be used by researchers interested in the effect of TE insertion on the eukaryotic transcriptome.

Proper citation: TranspoGene (RRID:SCR_005634) Copy   

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http://plantta.jcvi.org/

The TIGR database is a collection of plant transcript sequences. Transcript assemblies are searchable using BLAST and accession number. The construction of plant transcript assemblies (TAs) is similar to the TIGR gene indices. The sequences that are used to build the plant TAs are expressed transcripts collected from dbEST (ESTs) and the NCBI GenBank nucleotide database (full length and partial cDNAs). "Virtual" transcript sequences derived from whole genome annotation projects are not included. All plant species for which more than 1,000 ESTs or cDNA sequences are available are included in this project. TAs are clustered and assembled using the TGICL tool (Pertea et al., 2003), Megablast (Zhang et al., 2000) and the CAP3 assembler (Huang and Madan, 1999). TGICL is a wrapper script which invokes Megablast and CAP3. Sequences are initially clustered based on an all-against-all comparisons using Megablast. The initial clusters are assembled to generate consensus sequences using CAP3. Assembly criteria include a 50 bp minimum match, 95% minimum identity in the overlap region and 20 bp maximum unmatched overhangs. Any EST/cDNA sequences that are not assembled into TAs are included as singletons. All singletons retain their GenBank accession numbers as identifiers. Plant TA identifiers are of the form TAnumber_taxonID, where number is a unique numerical identifier of the transcript assembly and taxonID represents the NCBI taxon id. In order to provide annotation for the TAs, each TA/singleton was aligned to the UniProt Uniref database. For release 1 TAs, a masked version of the Uniref90 database was used. For release 2 and onwards, a masked version of the UniRef100 database is used. Alignments were required to have at least 20% identity and 20% coverage. The annotation for the protein with the best alignment to each TA or singleton was used as the annotation for that sequence. Additionally, the relative orientation of each TA/singleton to the best matching protein sequence was used to determine the orientation of each TA/singleton. Some sequences did not have alignments to the protein database that met our quality criteria, and those sequences have neither annotation nor orientation assignments. The release number for the plant TAs refers to the release version for a particular species. For the initial build, all TA sets are of version 1. Subsequent TA updates for new releases will be carried out when the percentage increase of the EST and cDNA counts exceeds 10% of the previous release and when the increase contains more than 1,000 new sequences. New releases will also include additional plant species with more than 1,000 EST or cDNA sequences that have become publicly available.

Proper citation: TIGR Plant Transcript Assembly database (RRID:SCR_005470) Copy   

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http://oger.tu-bs.de/strepto_db

A database for comparative genomics of group A and group B streptococci. It is based on OGeR (Open Genome Resource for comparative analysis of prokaryotic genomes) and includes all sequenced GAS and GBS strains and serovars available as EMBL genome review or NCBI GenBank files. Strepto-DB identifies the homologous proteins deduced from the genomes of interest. It allows for the elucidation of the GAS and GBS core- and pan-genomes via genome-wide comparisons. Moreover, an intergenic region analysis tool provides alignments and predictions for transcription factor binding sites in the non-coding sequences. An interactive genome browser visualizes functional annotations. Strepto-DB (http://oger.tu-bs.de/strepto_db) was created by the use of OGeR, the Open Genome Resource for comparative analysis of prokaryotic genomes. OGeR is a newly developed open source database and tool platform for the web-based storage, distribution, visualization and comparison of prokaryotic genome data. The system automatically creates the dedicated relational database and web interface and imports an arbitrary number of genomes derived from standardized genome files.

Proper citation: Strepto-DB (RRID:SCR_005196) Copy   

•   Source: SciCrunch Registry

http://tabit.ucsd.edu/sdec/

A next-generation web-based application that aims to provide an integrated solution for both visualization and analysis of deep-sequencing data, along with simple access to public datasets.

Proper citation: Systems Transcriptional Activity Reconstruction (RRID:SCR_005622) Copy   

•   Source: SciCrunch Registry

http://www.youtube.com/user/sfnvideo

The Society for Neuroscience (SfN) is a nonprofit membership organization of scientists and physicians who study the brain and nervous system. SFNVideo - YouTube are videos uploaded to YouTube by the Society for Neuroscience (SfN). Since inception in 1969, the Society has grown from 500 members to more than 41,000. Today, SfN is the world''s largest organization of scientists and physicians devoted to advancing understanding of the brain and nervous system.

Proper citation: sfnvideo - YouTube (RRID:SCR_005463) Copy   

•   Source: SciCrunch Registry

http://www.gene-regulation.com/pub/databases.html#transfac

Manually curated database of eukaryotic transcription factors, their genomic binding sites and DNA binding profiles. Used to predict potential transcription factor binding sites.

Proper citation: TRANSFAC (RRID:SCR_005620) Copy   

•   Source: SciCrunch Registry

http://www.tigr.org/tdb/e2k1/plant.repeats

It assists in the compilation and identification of repeat sequences in plant genomes. All of the repetitive sequences in the database are coded for the convenience of future analyses. In plants, ploidy levels and repetitive sequences contribute significantly to genome size. A number of different repetitive sequences have been reported in the plant genome and these can be classified into super-classes, classes, and subclasses based on structure and sequence composition. The transposable element (TEs) super-class includes retrotransposons, transposons, and miniature inverted-repeat transposable elements (MITEs). Other repetitive sequences are associated the centromere and telomere. Another super-class of repetitive sequences are rDNAs which encode the structural RNA components of ribosomes.

Proper citation: Plant Repeat Databases (RRID:SCR_005460) Copy   

•   Source: SciCrunch Registry

https://www.youtube.com/user/iniusc

Videos uploaded to YouTube by the Laboratory of Neuro Imaging (LONI). The Laboratory of Neuro Imaging at UCLA strives to improve our understanding of the brain in health and disease. LONI is a leader in the development of advanced computational algorithms and scientific approaches for the comprehensive and quantitative mapping of brain structure and function.

Proper citation: Laboratory of Neuro Imaging - YouTube (RRID:SCR_005462) Copy   

•   Source: SciCrunch Registry

http://www.hematology.org/Publications/Videos/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on August 18, 2016. ASH's video library includes a number of films produced on various topics, including ASH''s history and award winners, Society programs such as the Clinical Research Training Institute, and a trailer and clips from the hematology documentary Blood Detectives, which aired on Discovery Health. These videos were created for educational purposes, and we encourage members of the hematology community to share them with others.

Proper citation: ASH Video Library (RRID:SCR_005777) Copy   

•   Source: SciCrunch Registry

http://microrna.osu.edu/.UCbase4

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 16, 2013. UCbase & miRfunc is a database of (i) human, mouse and rat microRNAs and (ii) Ultraconserved elements providing information about function, expression and correlation between these classes of non-coding RNAs and the disorders related to their aberrant expression. The genomics interface allows the user to explore where whole-genome collections of miRNAs and UCRs are located with respect to annotation sets such as band, disorders and known genes. The Blast interface provides a web tool for matching miRNAs/UCRs elements against any given sequence and providing specific functional information on the results. 481 Ultraconserved sequences (UCRs) longer than 200 bases were discovered in the genomes of human, mouse and rat. These are DNA sequences showing 100 percent identity among the human, mouse and rat genomes. UCRs are frequently located at genomic regions involved in cancer, differentially expressed in human leukemias and carcinomas and in some instances regulated by microRNAs (miRNAs), the most extensively studied category of non-coding RNAs (ncRNAs). Here we present the first database which links UCRs and miRNAs with the related human disorders and genomic properties.

Proper citation: UCbase & miRfunc: Ultraconserved Sequences and miRNA Funciton Database (RRID:SCR_005771) Copy   

•   Source: SciCrunch Registry

http://bigg.ucsd.edu/

A knowledgebase of Biochemically, Genetically and Genomically structured genome-scale metabolic network reconstructions. BiGG integrates several published genome-scale metabolic networks into one resource with standard nomenclature which allows components to be compared across different organisms. BiGG can be used to browse model content, visualize metabolic pathway maps, and export SBML files of the models for further analysis by external software packages. Users may follow links from BiGG to several external databases to obtain additional information on genes, proteins, reactions, metabolites and citations of interest.

Proper citation: BiGG Database (RRID:SCR_005809) Copy   

•   Source: SciCrunch Registry

http://the_brain.bwh.harvard.edu/uniprobe/

Database that hosts experimental data from universal protein binding microarray (PBM) experiments (Berger et al., 2006) and their accompanying statistical analyses from prokaryotic and eukaryotic organisms, malarial parasites, yeast, worms, mouse, and human. It provides a centralized resource for accessing comprehensive data on the preferences of proteins for all possible sequence variants ("words") of length k ("k-mers"), as well as position weight matrix (PWM) and graphical sequence logo representations of the k-mer data. The database's web tools include a text-based search, a function for assessing motif similarity between user-entered data and database PWMs, and a function for locating putative binding sites along user-entered nucleotide sequences.

Proper citation: UniPROBE (RRID:SCR_005803) Copy   

•   Source: SciCrunch Registry

http://edwardslab.bmcb.georgetown.edu/downloads/

The Peptide Sequence Database contains putative peptide sequences from human, mouse, rat, and zebrafish. Compressed to eliminate redundancy, these are about 40 fold smaller than a brute force enumeration. Current and old releases are available for download. Each species'' peptide sequence database comprises peptide sequence data from releveant species specific UniGene and IPI clusters, plus all sequences from their consituent EST, mRNA and protein sequence databases, namely RefSeq proteins and mRNAs, UniProt''s SwissProt and TrEMBL, GenBank mRNA, ESTs, and high-throughput cDNAs, HInv-DB, VEGA, EMBL, IPI protein sequences, plus the enumeration of all combinations of UniProt sequence variants, Met loss PTM, and signal peptide cleavages. The README file contains some information about the non amino-acid symbols O (digest site corresponding to a protein N- or C-terminus) and J (no digest sequence join) used in these peptide sequence databases and information about how to configure various search engines to use them. Some search engines handle (very) long sequences badly and in some cases must be patched to use these peptide sequence databases. All search engines supported by the PepArML meta-search engine can (or can be patched to) successfully search these peptide sequence databases.

Proper citation: Peptide Sequence Database (RRID:SCR_005764) Copy   

•   Source: SciCrunch Registry

http://h-invitational.jp/varygene/

It consists of a Genome Browser, an LD Search System, and the VaryGene 2 system. The Generic Genome Browser is a combination of database and interactive Web page for manipulating and displaying annotations on genomes, while LDSearchSystem is a search system for linkage disequilibrium (LD) bins. VaryGene 2 is a system to search, display, and download our research results on human polymorphism based on publicly available data and annotations of transcripts presented by H-InvDB. VaryGene 2 provides information about single nucleotide polymorphisms (SNPs), deletion-insertion polymorphisms (DIPs), short tandem repeats (STRs), single amino acid repeats (SARs), structural variation (or copy number variations: CNVs), and their relations to the genome, transcripts, and functional domains. Users can search by polymorphisms, transcripts, STRs/SARs, and CNVs.

Proper citation: VarySysDB (RRID:SCR_005880) Copy   

•   Source: SciCrunch Registry

http://indel.bioinfo.sdu.edu.cn/gridsphere/gridsphere

THIS RESOURCE IS NO LONGER IN SERVCE, documented September 2, 2016. Indel Flanking Region Database is an online resource for indels and the flanking regions of proteins in SCOP superfamilies, including amino acid sequences, lengths, locations, secondary structure constitutions, hydrophilicity / hydrophobicity, domain information, 3D structures and so on. It aims at providing a comprehensive dataset for analyzing the qualities of amino acid insertion/deletions(indels), substitutions and the relationship between them. The indels were obtained through the pairwise alignment of homologous structures in SCOP superfamilies. The IndelFR database contains 2,925,017 indels with flanking regions extracted from 373,402 structural alignment pairs of 12,573 non-redundant domains from 1053 superfamilies. IndelFR has already been used for molecular evolution studies and may help to promote future functional studies of indels and their flanking regions.

Proper citation: IndelFR - Indel Flanking Region Database (RRID:SCR_006050) Copy   

•   Source: SciCrunch Registry

http://www.utrome.org

This database is intended as a comprehensive resource for UTR (Untranslated Region) biology in C. elegans. The database provides detailed information on UTR structures for all protein-coding mRNAs, and includes annotations extracted from other databases (such as WormBase and PicTar) as well as new annotations generated as part of the NYU UTRome project (including preliminary characterization of UTR clones, USTs (UTR sequence tags), curated sequences, and computational and experimental analysis of functional elements). Examples of functional elements within UTRs include predicted and validated microRNA (miRNA) binding sites (responsible for post-transcriptional gene regulation), putative consensus signals for polyA addition, and predicted secondary structures (which may influence the biological activity of UTRs). The UTRome project is part of the ModEncode Consortium, an NIH initiative to characterize at a genomic scale functional sequence elements encoded in the worm (C. elegans) and fly (D. melanogaster) genomes. UTRs are important portions of mRNAs required for post-transcriptional regulation by interacting with proteins or non-coding RNAs (e.g. microRNAs). To study the role of UTRs we are building a UTR database for C. elegans.

Proper citation: UTRome.org (RRID:SCR_005878) Copy   

•   Source: SciCrunch Registry

http://roar.eprints.org/

Listing of institutional repositories for depositing preprints of published materials with the aim of promoting the development of open access by providing timely information about the growth and status of repositories throughout the world. Open access to research maximizes research access and thereby also research impact, making research more productive and effective. Repository Types: * Research Institutional or Departmental * Research Multi-institution Repository * Research Cross-Institutional * e-Journal/Publication * e-Theses * Database/A&I Index * Research Data * Open and Linked Data * Learning and Teaching Objects * Demonstration * Web Observatory * Other Repository Software: * ARNO * Bepress * CDS Invenio * ContentDM by OCLC * DIGIBIB * DigiTool * DiVA * DoKS * DSpace * EDOC * EPrints * Equella * ETD-db * Fedora ** Fez * Greenstone * HAL * i-Tor * IntraLibrary * Keystone DLS * MiTOS * MyCoRe * Open Journal System * Open Repository * OPUS (Open Publications System) * Other softwares (various) * PMB Services * SBCAT * SciX * SobekCM * WIKINDX * Zentity

Proper citation: ROAR (RRID:SCR_005951) Copy   

•   Source: SciCrunch Registry

http://www.youtube.com/user/NIGMS/

YouTube videos provided by the National Institute of General Medical Sciences (NIGMS).

Proper citation: NIGMS - YouTube (RRID:SCR_005678) Copy   

•   Source: SciCrunch Registry