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At least 973 records · Page 54Linked to original sources
PubMed2003

COmplete GENome Tracking (COGENT): a flexible data environment for computational genomics.

SUMMARY: We present a database of fully sequenced and published genomes to facilitate the re-distribution of data and ensure reproducibility of results in the field of computational genomics. For its design we have implemented an extremely simple yet powerful schema to allow linking of genome sequence data to other resources. AVAILABILITY: http://maine.ebi.ac.uk:8000/services/cogent/

Computational Biology↗
PubMed2004

The otter annotation system.

With the completion of the human genome sequence and genome sequence available for other vertebrate genomes, the task of manual annotation at the large genome scale has become a priority. Possibly even more important, is the requirement to curate and improve this annotation in the light of future data. For this to be possible, there is a need for tools to access and manage the annotation. Ensembl provides an excellent means for storing gene structures, genome features, and sequence, but it does not support the extra textual data necessary for manual annotation. We have extended Ensembl to create the Otter manual annotation system. This comprises a relational database schema for storing the manual annotation data, an application-programming interface (API) to access it, an extensible markup language (XML) format to allow transfer of the data, and a server to allow multiuser/multimachine access to the data. We have also written a data-adaptor plugin for the Apollo Browser/Editor to enable it to utilize an Otter server. The otter database is currently used by the Vertebrate Genome Annotation (VEGA) site (http://vega.sanger.ac.uk), which provides access to manually curated human chromosomes. Support is also being developed for using the AceDB annotation editor, FMap, via a perl wrapper called Lace. The Human and Vertebrate Annotation (HAVANA) group annotators at the Sanger center are using this to annotate human chromosomes 1 and 20.

Computational Biology↗
PubMed2001

RAMEDIS- rare metabolic diseases publishing tool for genotype-phenotype correlation.

To gain further knowledge about rare genetic diseases, a world wide method for data collection via the Internet has been established. This new approach will improve collecting valuable data from single case reports. RAMEDIS saves standardised patient data which will be usable for statistics, longitudinal examinations and co-operative studies in future time. Embedded in the scene of the German Human Genome Project, RAMEDIS directly will enable phenotype-genotype correlation's. Technically RAMEDIS is based on the Oracle database management system with some additional tools. Since November 2000 first case reports are committed online. Beside the better characterisation of clinical heterogeneity of rare diseases, there may be a great benefit for the treatment of these patients in whom prospective studies are otherwise expensive and difficult to perform. Quality of clinical diagnostic process and therapy will increase.

Computational Biology↗
PubMed2002

ScanProsite: a reference implementation of a PROSITE scanning tool.

Many different software tools are available publicly to scan the PROSITE database of protein families. However, none of them, to our knowledge, wholly implements the PROSITE syntax, or satisfies all the rules for scanning a pattern against a sequence. We hereby propose a strict definition of how a PROSITE pattern is to be scanned against a sequence, and provide a reference implementation of a tool to scan PROSITE patterns, rules and profiles against protein sequences.

Computational Biology↗
PubMed2004

3D-GENOMICS: a database to compare structural and functional annotations of proteins between sequenced genomes.

The 3D-GENOMICS database (http://www.sbg.bio. ic.ac.uk/3dgenomics/) provides structural annotations for proteins from sequenced genomes. In August 2003 the database included data for 93 proteomes. The annotations stored in the database include homologous sequences from various sequence databases, domains from SCOP and Pfam, patterns from Prosite and other predicted sequence features such as transmembrane regions and coiled coils. In addition to annotations at the sequence level, several precomputed cross- proteome comparative analyses are available based on SCOP domain superfamily composition. Annotations are available to the user via a web interface to the database. Multiple points of entry are available so that a user is able to: (i) directly access annotations for a single protein sequence via keywords or accession codes, (ii) examine a sequence of interest chosen from a summary of annotations for a particular proteome, or (iii) access precomputed frequency-based cross-proteome comparative analyses.

Amino Acid Sequence↗
PubMed2004

Pathbase: a database of mutant mouse pathology.

Pathbase is a database that stores images of the abnormal histology associated with spontaneous and induced mutations of both embryonic and adult mice including those produced by transgenesis, targeted mutagenesis and chemical mutagenesis. Images of normal mouse histology and strain-dependent background lesions are also available. The database and the images are publicly accessible (http://www.pathbase.net) and linked by anatomical site, gene and other identifiers to relevant databases; there are also facilities for public comment and record annotation. The database is structured around a novel ontology of mouse disorders (MPATH) and provides high-resolution downloadable images of normal and diseased tissues that are searchable through orthogonal ontologies for pathology, developmental stage, anatomy and gene attributes (GO terms), together with controlled vocabularies for type of genetic manipulation or mutation, genotype and free text annotation for mouse strain and additional attributes. The database is actively curated and data records assessed by pathologists in the Pathbase Consortium before publication. The database interface is designed to have optimal browser and platform compatibility and to interact directly with other web-based mouse genetic resources.

Animals↗
PubMed2003

Identification of protein biochemical functions by similarity search using the molecular surface database eF-site.

The identification of protein biochemical functions based on their three-dimensional structures is strongly required in the post-genome-sequencing era. We have developed a new method to identify and predict protein biochemical functions using the similarity information of molecular surface geometries and electrostatic potentials on the surfaces. Our prediction system consists of a similarity search method based on a clique search algorithm and the molecular surface database eF-site (electrostatic surface of functional-site in proteins). Using this system, functional sites similar to those of phosphoenoylpyruvate carboxy kinase were detected in several mononucleotide-binding proteins, which have different folds. We also applied our method to a hypothetical protein, MJ0226 from Methanococcus jannaschii, and detected the mononucleotide binding site from the similarity to other proteins having different folds.

Algorithms↗
PubMed2006

PHOG-BLAST--a new generation tool for fast similarity search of protein families.

BACKGROUND: The need to compare protein profiles frequently arises in various protein research areas: comparison of protein families, domain searches, resolution of orthology and paralogy. The existing fast algorithms can only compare a protein sequence with a protein sequence and a profile with a sequence. Algorithms to compare profiles use dynamic programming and complex scoring functions. RESULTS: We developed a new algorithm called PHOG-BLAST for fast similarity search of profiles. This algorithm uses profile discretization to convert a profile to a finite alphabet and utilizes hashing for fast search. To determine the optimal alphabet, we analyzed columns in reliable multiple alignments and obtained column clusters in the 20-dimensional profile space by applying a special clustering procedure. We show that the clustering procedure works best if its parameters are chosen so that 20 profile clusters are obtained which can be interpreted as ancestral amino acid residues. With these clusters, only less than 2% of columns in multiple alignments are out of clusters. We tested the performance of PHOG-BLAST vs. PSI-BLAST on three well-known databases of multiple alignments: COG, PFAM and BALIBASE. On the COG database both algorithms showed the same performance, on PFAM and BALIBASE PHOG-BLAST was much superior to PSI-BLAST. PHOG-BLAST required 10-20 times less computer memory and computation time than PSI-BLAST. CONCLUSION: Since PHOG-BLAST can compare multiple alignments of protein families, it can be used in different areas of comparative proteomics and protein evolution. For example, PHOG-BLAST helped to build the PHOG database of phylogenetic orthologous groups. An essential step in building this database was comparing protein complements of different species and orthologous groups of different taxons on a personal computer in reasonable time. When it is applied to detect weak similarity between protein families, PHOG-BLAST is less precise than rigorous profile-profile comparison method, though it runs much faster and can be used as a hit pre-selecting tool.

Algorithms↗
PubMed2002

A common evolutionary origin of two elementary enzyme folds.

The (beta alpha)(8)-barrel is the most frequent and most versatile fold among enzymes [Höcker et al., Curr. Opin. Biotechnol. 12 (2001) 376-381; Wierenga, FEBS Lett. 492 (2001) 193-198]. Structural and functional evidence suggests that (beta alpha)(8)-barrels evolved from an ancestral half-barrel, which consisted of four (beta alpha) units stabilized by dimerization [Lang et al., Science 289 (2000) 1546-550; Höcker et al., Nat. Struct. Biol. 8 (2001) 32-36; Gerlt and Babbitt, Nat. Struct. Biol. 8 (2001) 5-7]. Here, by performing a comprehensive database search, we detect a striking and unexpected structural and amino acid sequence similarity between (beta alpha)(4) half-barrels and members of the (beta alpha)(5) flavodoxin-like fold. These findings provoke the hypothesis that a large fraction of the modern-day enzymes evolved from a basic structural building block, which can be identified by a combination of sequence and structural analyses.

Computational Biology↗
PubMed2003

Additional SNPs and linkage-disequilibrium analyses are necessary for whole-genome association studies in humans.

More than 5 million single-nucleotide polymorphisms (SNPs) with minor-allele frequency greater than 10% are expected to exist in the human genome. Some of these SNPs may be associated with risk of developing common diseases. To assess the power of currently available SNPs to detect such associations, we resequenced 50 genes in two ethnic samples and measured patterns of linkage disequilibrium between the subset of SNPs reported in dbSNP and the complete set of common SNPs. Our results suggest that using all 2.7 million SNPs currently in the database would detect nearly 80% of all common SNPs in European populations but only 50% of those common in the African American population and that efficient selection of a minimal subset of SNPs for use in association studies requires measurement of allele frequency and linkage disequilibrium relationships for all SNPs in dbSNP.

Alleles↗
PubMed2000

T(E)Xtopo: shaded membrane protein topology plots in LAT(E)X2epsilon.

UNLABELLED: T(E)Xtopo is a LAT(E)X2epsilon macro package for plotting topology data directly from PHD predictions or SwissProt database files in publication-ready quality. The plot can be shaded automatically to emphasize conserved residues or functional properties of the residue sidechains. The addition of rich decorations, such as labels, annotations and legends, is easily accomplished. AVAILABILITY: The T(E)Xtopo macro package and a full on-line documentation are freely available at http://homepages.uni-tuebingen.de/beitz/ CONTACT: eric.beitz@uni-tuebingen.de

Amino Acid Sequence↗
PubMed2002

SST: an algorithm for finding near-exact sequence matches in time proportional to the logarithm of the database size.

MOTIVATION: Searches for near exact sequence matches are performed frequently in large-scale sequencing projects and in comparative genomics. The time and cost of performing these large-scale sequence-similarity searches is prohibitive using even the fastest of the extant algorithms. Faster algorithms are desired. RESULTS: We have developed an algorithm, called SST (Sequence Search Tree), that searches a database of DNA sequences for near-exact matches, in time proportional to the logarithm of the database size n. In SST, we partition each sequence into fragments of fixed length called 'windows' using multiple offsets. Each window is mapped into a vector of dimension 4(k) which contains the frequency of occurrence of its component k-tuples, with k a parameter typically in the range 4-6. Then we create a tree-structured index of the windows in vector space, with tree-structured vector quantization (TSVQ). We identify the nearest neighbors of a query sequence by partitioning the query into windows and searching the tree-structured index for nearest-neighbor windows in the database. When the tree is balanced this yields an O(logn) complexity for the search. This complexity was observed in our computations. SST is most effective for applications in which the target sequences show a high degree of similarity to the query sequence, such as assembling shotgun sequences or matching ESTs to genomic sequence. The algorithm is also an effective filtration method. Specifically, it can be used as a preprocessing step for other search methods to reduce the complexity of searching one large database against another. For the problem of identifying overlapping fragments in the assembly of 120 000 fragments from a 1.5 megabase genomic sequence, SST is 15 times faster than BLAST when we consider both building and searching the tree. For searching alone (i.e. after building the tree index), SST 27 times faster than BLAST. AVAILABILITY: Request from the authors.

Algorithms↗
PubMed2006

Query Chem: a Google-powered web search combining text and chemical structures.

Query Chem (www.QueryChem.com) is a Web program that integrates chemical structure and text-based searching using publicly available chemical databases and Google's Web Application Program Interface (API). Query Chem makes it possible to search the Web for information about chemical structures without knowing their common names or identifiers. Furthermore, a structure can be combined with textual query terms to further restrict searches. Query Chem's search results can retrieve many interesting structure-property relationships of biomolecules on the Web.

Algorithms↗
PubMed2004

The Ensembl core software libraries.

Systems for managing genomic data must store a vast quantity of information. Ensembl stores these data in several MySQL databases. The core software libraries provide a practical and effective means for programmers to access these data. By encapsulating the underlying database structure, the libraries present end users with a simple, abstract interface to a complex data model. Programs that use the libraries rather than SQL to access the data are unaffected by most schema changes. The architecture of the core software libraries, the schema, and the factors influencing their design are described. All code and data are freely available.

Animals↗
PubMed2004

The reagent database at dbMHC.

The reagent database dbMHC was built by the National Center for Biotechnology Information (NCBI) as an open resource for registration and characterization of HLA DNA-typing kits and reagents. Each reagent is uniquely identified as sequence-specific oligonucleotide (SSO) or primer (SSP), SSO mix, or SSP mix. Computerized prediction of allele reactivities, based on annealing stringency, is performed on all submissions to the reagent database. User-specified allele reactivities may be added or deleted independently of the prediction algorithm. Updates of allele reactivities are performed in synchronization with the IMGT/HLA database, in order to account for newly discovered alleles. Probe and primer sequences aligned to allelic sequences can be displayed at any time. Reagents registered in the reagent database are grouped in typing kits. Each kit or kit batch is uniquely identified. Group-specific amplification of alleles can be specified for an entire kit or for sections of each kit. Kits designed to test multiple loci are supported. Kits can be entered and updated via the web or submitted as batches in extensible markup language (XML) format. A tool for online interpretation of typing results is available. Both the reagent database and the typing kit database have been designed to facilitate the exchange of HLA typing based on raw typing data using the unique identifiers of kits or individual reagents. In addition, batch-wise reinterpretation of previous typing data can be performed either using the NCBI web site or by locally using downloaded allele-reactivity lists. Reinterpretation by the NCBI requires submission of raw typing data in XML format.

Computational Biology↗
PubMed2005

MACiE: a database of enzyme reaction mechanisms.

SUMMARY: MACiE (mechanism, annotation and classification in enzymes) is a publicly available web-based database, held in CMLReact (an XML application), that aims to help our understanding of the evolution of enzyme catalytic mechanisms and also to create a classification system which reflects the actual chemical mechanism (catalytic steps) of an enzyme reaction, not only the overall reaction. AVAILABILITY: http://www-mitchell.ch.cam.ac.uk/macie/.

Catalysis↗
PubMed2004

STCDB: Signal Transduction Classification Database.

The Signal Transduction Classification Database (STCDB) is a database of information relative to the classification of signal transduction. It is based primarily on a proposed classification of signal transduction and it describes each type of characterized signal transduction for which a unique ST number has been provided. This document presents, in its first version, the classification of signal transduction in eukaryotic cells. Approved classifications are available for web browsing at http://www.techfak.uni-bielefeld.de/~ mchen/STCDB.

Animals↗