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We present a database of repetitive DNA elements, called Dfam (http://dfam.janelia.org). Many genomes contain a large fraction of repetitive DNA, much of which is made up of remnants of transposable elements (TEs). Accurate annotation of TEs enables research into their biology and can shed light on the evolutionary processes that shape genomes. Identification and masking of TEs can also greatly simplify many downstream genome annotation and sequence analysis tasks. The commonly used TE annotation tools RepeatMasker and Censor depend on sequence homology search tools such as cross_match and BLAST variants, as well as Repbase, a collection of known TE families each represented by a single consensus sequence. Dfam contains entries corresponding to all Repbase TE entries for which instances have been found in the human genome. Each Dfam entry is represented by a profile hidden Markov model, built from alignments generated using RepeatMasker and Repbase. When used in conjunction with the hidden Markov model search tool nhmmer, Dfam produces a 2.9% increase in coverage over consensus sequence search methods on a large human benchmark, while maintaining low false discovery rates, and coverage of the full human genome is 54.5%. The website provides a collection of tools and data views to support improved TE curation and annotation efforts. Dfam is also available for download in flat file format or in the form of MySQL table dumps.

We present the Database of Disordered Protein Prediction (D2P2), available at http://d2p2.pro (including website source code). A battery of disorder predictors and their variants, VL-XT, VSL2b, PrDOS, PV2, Espritz and IUPred, were run on all protein sequences from 1765 complete proteomes (to be updated as more genomes are completed). Integrated with these results are all of the predicted (mostly structured) SCOP domains using the SUPERFAMILY predictor. These disorder/structure annotations together enable comparison of the disorder predictors with each other and examination of the overlap between disordered predictions and SCOP domains on a large scale. D2P2 will increase our understanding of the interplay between disorder and structure, the genomic distribution of disorder, and its evolutionary history. The parsed data are made available in a unified format for download as flat files or SQL tables either by genome, by predictor, or for the complete set. An interactive website provides a graphical view of each protein annotated with the SCOP domains and disordered regions from all predictors overlaid (or shown as a consensus). There are statistics and tools for browsing and comparing genomes and their disorder within the context of their position on the tree of life. © The Author(s) 2012. Published by Oxford University Press.

FlyFactorSurvey (http://pgfe.umassmed.edu/TFDBS/) is a database of DNA binding specificities for Drosophila transcription factors (TFs) primarily determined using the bacterial one-hybrid system. The database provides community access to over 400 recognition motifs and position weight matrices for over 200 TFs, including many unpublished motifs. Search tools and flat file downloads are provided to retrieve binding site information (as sequences, matrices and sequence logos) for individual TFs, groups of TFs or for all TFs with characterized binding specificities. Linked analysis tools allow users to identify motifs within our database that share similarity to a query matrix or to view the distribution of occurrences of an individual motif throughout the Drosophila genome. Together, this database and its associated tools provide computational and experimental biologists with resources to predict interactions between Drosophila TFs and target cis-regulatory sequences.

3D-footprint is a living database, updated and curated on a weekly basis, which provides estimates of binding specificity for all protein–DNA complexes available at the Protein Data Bank. The web interface allows the user to: (i) browse DNA-binding proteins by keyword; (ii) find proteins that recognize a similar DNA motif and (iii) BLAST similar DNA-binding proteins, highlighting interface residues in the resulting alignments. Each complex in the database is dissected to draw interface graphs and footprint logos, and two complementary algorithms are employed to characterize binding specificity. Moreover, oligonucleotide sequences extracted from literature abstracts are reported in order to show the range of variant sites bound by each protein and other related proteins. Benchmark experiments, including comparisons with expert-curated databases RegulonDB and TRANSFAC, support the quality of structure-based estimates of specificity. The relevant content of the database is available for download as flat files and it is also possible to use the 3D-footprint pipeline to analyze protein coordinates input by the user. 3D-footprint is available at http://floresta.eead.csic.es/3dfootprint with demo buttons and a comprehensive tutorial that illustrates the main uses of this resource., Consejo Superior de Investigaciones Científicas [grant number 200720I038]. Funding to pay the Open Access publication charges for this article was provided by [grant A06] from Gobierno de Aragón to the research group of J.M. Lasa in 2009.

The University of California Santa Cruz (UCSC) Genome Browser Database is an up to date source for genome sequence data integrated with a large collection of related annotations. The database is optimized to support fast interactive performance with the web-based UCSC Genome Browser, a tool built on top of the database for rapid visualization and querying of the data at many levels. The annotations for a given genome are displayed in the browser as a series of tracks aligned with the genomic sequence. Sequence data and annotations may also be viewed in a text-based tabular format or downloaded as tab-delimited flat files. The Genome Browser Database, browsing tools and downloadable data files can all be found on the UCSC Genome Bioinformatics website (http://genome.ucsc.edu), which also contains links to documentation and related technical information.

Contains fulltext : 136954.pdf (Publisher’s version ) (Open Access) The Human Phenotype Ontology (HPO) project, available at http://www.human-phenotype-ontology.org, provides a structured, comprehensive and well-defined set of 10,088 classes (terms) describing human phenotypic abnormalities and 13,326 subclass relations between the HPO classes. In addition we have developed logical definitions for 46% of all HPO classes using terms from ontologies for anatomy, cell types, function, embryology, pathology and other domains. This allows interoperability with several resources, especially those containing phenotype information on model organisms such as mouse and zebrafish. Here we describe the updated HPO database, which provides annotations of 7,278 human hereditary syndromes listed in OMIM, Orphanet and DECIPHER to classes of the HPO. Various meta-attributes such as frequency, references and negations are associated with each annotation. Several large-scale projects worldwide utilize the HPO for describing phenotype information in their datasets. We have therefore generated equivalence mappings to other phenotype vocabularies such as LDDB, Orphanet, MedDRA, UMLS and phenoDB, allowing integration of existing datasets and interoperability with multiple biomedical resources. We have created various ways to access the HPO database content using flat files, a MySQL database, and Web-based tools. All data and documentation on the HPO project can be found online.

We have compiled the DNA sequence data forEscherichia coliavailable from the GenBank and EMBL data libraries and independently from the literature. We provide the most definitive version of the ECDEscherichia colidatabase now exclusively via the World Wide Web System: http://susi.bio.uni-giessen.de/usr/local/www/ html/ecdc.html . Our database encloses an assembled set of contiguous sequences. Each of these contigs compiles all available sequence information, including those derived from a variety of elder sequences. The organisation of the database allows precise physical location of each individual gene or regulatory region, even taking into consideration discrepancies in nomenclature. The WWW program allows to branch into the original EMBL and SWISSPROT datafiles. A number of links to other WWW servers is provided. A FASTA and BLAST search may be performed online. Besides the WWW format a flat file version may be obtained via ftp. The ftp version may also be obtained from the EMBL data library as part of the CD-ROM issue of the EMBL sequence database, which is released and updated every 3 months. After deletion of all detected overlaps a total of 3 588 706 individual bp has been determined up to the end of September 1996. This corresponds to a total of 77.09% of the entire E.coli chromosome consisting of approximately 4655 kb. About 479 kb (10.3%) are additionally available from Kyoto (Japan). Another 94 kb (2%) are available, but mapping has not been confirmed. Thus the total may have reached 89.4%.

FlyBase is a database of genetic and molecular data concerning Drosophila. FlyBase is maintained as a relational database (in Sybase) and is made available as html documents and flat files. The scope of FlyBase includes: genes, alleles (and phenotypes), aberrations, transposons, pointers to sequence data, clones, stock lists, Drosophila workers and bibliographic references. The Encyclopedia of Drosophila is a joint effort between FlyBase and the Berkeley Drosophila Genome Project which integrates FlyBase data with those from the BDGP.

We have compiled the DNA sequence data for E. coli available from the GENBANK and EMBL data libraries and independently from the literature. Starting with this update of our Escherichia coli database (ECD release 20) we provide major changes compared to previous issues. This update not only represents another substantial increase in sequence information, it also allows now to find the exact physical location of each individual gene or regulatory region, even regarding discrepancies in nomenclature. In order to save space this printed version does not contain the database itself anymore, but we provide several examples. The complete database is publically available in electronic form together with a self explaining application program or as a flat file. The complete compilation including a full set of genetic map data and the E. coli protein index can be obtained in machine readable form from the EMBL data library as a part of the CD-ROM issue of the EMBL sequence database, released and updated every three months. After deletion of all detected overlaps a total of 2,878,364 individual bp is found to be determined till the end of June 1994. This corresponds to a total of 60.98% of the entire E. coli chromosome consisting of about 4,720 kbp. This number may actually be higher by 9161 bp derived from other strains of E. coli.

Better characterization of binding sites in proteins and the ability to accurately predict their location and energetic properties are major challenges which, if addressed, would have many valuable practical applications. Unfortunately, reliable benchmark datasets of binding sites in proteins are still sorely lacking. Here, we present LigASite ('LIGand Attachment SITE'), a gold-standard dataset of binding sites in 550 proteins of known structures. LigASite consists exclusively of biologically relevant binding sites in proteins for which at least one apo- and one holo-structure are available. In defining the binding sites for each protein, information from all holo-structures is combined, considering in each case the quaternary structure defined by the PQS server. LigASite is built using simple criteria and is automatically updated as new structures become available in the PDB, thereby guaranteeing optimal data coverage over time. Both a redundant and a culled non-redundant version of the dataset is available at http://www.scmbb.ulb.ac.be/Users/benoit/LigASite. The website interface allows users to search the dataset by PDB identifiers, ligand identifiers, protein names or sequence, and to look for structural matches as defined by the CATH homologous superfamilies. The datasets can be downloaded from the website as Schema-validated XML files or comma-separated flat files., Journal Article, Research Support, Non-U.S. Gov't, info:eu-repo/semantics/published

PROCOGNATE is a database of protein cognate ligands for the domains in enzyme structures as described by CATH, SCOP and Pfam, and is available as an interactive website or a flat file. This article gives an overview of the database and its generation and presents a new website front end, as well as recent increased coverage in our dataset via inclusion of Pfam domains. We also describe navigation of the website and its features. The current version (1.3) of PROCOGNATE covers 4123, 4536, 5876 structures and 377, 326, 695 superfamilies/families in CATH, SCOP and Pfam, respectively. PROCOGNATE can be accessed at: http://www.ebi.ac.uk/thornton-srv/databases/procognate/

HOMSTRAD (http://www-cryst.bioc.cam.ac.uk/ homstrad/) is a collection of protein families, clustered on the basis of sequence and structural similarity. The database is unique in that the protein family sequence alignments have been specially annotated using the program, JOY, to highlight a wide range of structural features. Such data are useful for identifying key structurally conserved residues within the families. Superpositions of the structures within each family are also available and a sensitive structure-aided search engine, FUGUE, can be used to search the database for matches to a query protein sequence. Historically, HOMSTRAD families were generated using several key pieces of software, including COMPARER and MNYFIT, and held in a number of flat files and indexes. A new relational database version of HOMSTRAD, HOMSTRAD BETA (http://www-cryst.bioc.cam. ac.uk/homstradbeta/) is being developed using MySQL. This relational data structure provides more flexibility for future developments, reduces update times and makes data more easily accessible. Consequently it has been possible to add a number of new web features including a custom alignment facility. Altogether, this makes HOMSTRAD and its new BETA version, an excellent resource both for comparative modelling and for identifying distant sequence/structure similarities between proteins.

We have compiled the DNA sequence data for Escherichia coli K12 available from the GenBank and EMBL data libraries and independently from the literature. We provide the most definitive version of the ECD Escherichia coli database now exclusively via the World Wide Web System (http://susi.bio.uni-giessen.de/ecdc.html ). Our database encloses the completed genome sequence recently published by two competing groups and an assembled set of all elder sequences. The organisation of the database allows precise physical location of each individual gene or regulatory region, even taking into consideration discrepancies in nomenclature. The WWW program allows to the user to branch into the original EMBL and SWISS-PROT datafiles. A number of links to other WWW servers dealing with E. coli is provided. A FASTA and BLAST search may be performed online. Besides the WWW format a flat file version may be obtained via ftp. A number of discrepancies between the two systematic sequence determinations and/or the literature have not yet been resolved. However, our database may serve as a reference source for resolution and/or the assignment of strain difference.