951 resultados para sequence based alignments
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The EMBL Nucleotide Sequence Database (http://www.ebi.ac.uk/embl/) is maintained at the European Bioinformatics Institute (EBI) in an international collaboration with the DNA Data Bank of Japan (DDBJ) and GenBank at the NCBI (USA). Data is exchanged amongst the collaborating databases on a daily basis. The major contributors to the EMBL database are individual authors and genome project groups. Webin is the preferred web-based submission system for individual submitters, whilst automatic procedures allow incorporation of sequence data from large-scale genome sequencing centres and from the European Patent Office (EPO). Database releases are produced quarterly. Network services allow free access to the most up-to-date data collection via ftp, email and World Wide Web interfaces. EBI’s Sequence Retrieval System (SRS), a network browser for databanks in molecular biology, integrates and links the main nucleotide and protein databases plus many specialized databases. For sequence similarity searching a variety of tools (e.g. Blitz, Fasta, BLAST) are available which allow external users to compare their own sequences against the latest data in the EMBL Nucleotide Sequence Database and SWISS-PROT.
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BodyMap is a human and mouse gene expression database that is based on site-directed 3′-expressed sequence tags generated at Osaka University. To date, it contains more than 300 000 tag sequences from 64 human and 39 mouse tissues. For the recent release, the precise anatomical expression patterns for more than half of the human gene entries were generated by introduced amplified fragment length polymorphism (iAFLP), which is a PCR-based high-throughput expression profiling method. The iAFLP data incorporated into BodyMap describe the relative contents of more than 12 000 transcripts across 30 tissue RNAs. In addition, a newly developed gene ranking system helps users obtain lists of genes that have desired expression patterns according to their significance. BodyMap supports complete transfer of unique data sets and provides analysis that is accessible through the WWW at http://bodymap.ims.u-tokyo.ac.jp.
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In order to support the structural genomic initiatives, both by rapidly classifying newly determined structures and by suggesting suitable targets for structure determination, we have recently developed several new protocols for classifying structures in the CATH domain database (http://www.biochem.ucl.ac.uk/bsm/cath). These aim to increase the speed of classification of new structures using fast algorithms for structure comparison (GRATH) and to improve the sensitivity in recognising distant structural relatives by incorporating sequence information from relatives in the genomes (DomainFinder). In order to ensure the integrity of the database given the expected increase in data, the CATH Protein Family Database (CATH-PFDB), which currently includes 25 320 structural domains and a further 160 000 sequence relatives has now been installed in a relational ORACLE database. This was essential for developing more rigorous validation procedures and for allowing efficient querying of the database, particularly for genome analysis. The associated Dictionary of Homologous Superfamilies [Bray,J.E., Todd,A.E., Pearl,F.M.G., Thornton,J.M. and Orengo,C.A. (2000) Protein Eng., 13, 153–165], which provides multiple structural alignments and functional information to assist in assigning new relatives, has also been expanded recently and now includes information for 903 homologous superfamilies. In order to improve coverage of known structures, preliminary classification levels are now provided for new structures at interim stages in the classification protocol. Since a large proportion of new structures can be rapidly classified using profile-based sequence analysis [e.g. PSI-BLAST: Altschul,S.F., Madden,T.L., Schaffer,A.A., Zhang,J., Zhang,Z., Miller,W. and Lipman,D.J. (1997) Nucleic Acids Res., 25, 3389–3402], this provides preliminary classification for easily recognisable homologues, which in the latest release of CATH (version 1.7) represented nearly three-quarters of the non-identical structures.
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BAliBASE is specifically designed to serve as an evaluation resource to address all the problems encountered when aligning complete sequences. The database contains high quality, manually constructed multiple sequence alignments together with detailed annotations. The alignments are all based on three-dimensional structural superpositions, with the exception of the transmembrane sequences. The first release provided sets of reference alignments dealing with the problems of high variability, unequal repartition and large N/C-terminal extensions and internal insertions. Here we describe version 2.0 of the database, which incorporates three new reference sets of alignments containing structural repeats, transmembrane sequences and circular permutations to evaluate the accuracy of detection/prediction and alignment of these complex sequences. BAliBASE can be viewed at the web site http://www-igbmc.u-strasbg.fr/BioInfo/BAliBASE2/index.html or can be downloaded from ftp://ftp-igbmc.u-strasbg.fr/pub/BAliBASE2/.
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The emotif database is a collection of more than 170 000 highly specific and sensitive protein sequence motifs representing conserved biochemical properties and biological functions. These protein motifs are derived from 7697 sequence alignments in the BLOCKS+ database (released on June 23, 2000) and all 8244 protein sequence alignments in the PRINTS database (version 27.0) using the emotif-maker algorithm developed by Nevill-Manning et al. (Nevill-Manning,C.G., Wu,T.D. and Brutlag,D.L. (1998) Proc. Natl Acad. Sci. USA, 95, 5865–5871; Nevill-Manning,C.G., Sethi,K.S., Wu,T.D. and Brutlag,D.L. (1997) ISMB-97, 5, 202–209). Since the amino acids and the groups of amino acids in these sequence motifs represent critical positions conserved in evolution, search algorithms employing the emotif patterns can identify and classify more widely divergent sequences than methods based on global sequence similarity. The emotif protein pattern database is available at http://motif.stanford.edu/emotif/.
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SBASE 8.0 is the eighth release of the SBASE library of protein domain sequences that contains 294 898 annotated structural, functional, ligand-binding and topogenic segments of proteins, cross-referenced to most major sequence databases and sequence pattern collections. The entries are clustered into over 2005 statistically validated domain groups (SBASE-A) and 595 non-validated groups (SBASE-B), provided with several WWW-based search and browsing facilities for online use. A domain-search facility was developed, based on non-parametric pattern recognition methods, including artificial neural networks. SBASE 8.0 is freely available by anonymous ‘ftp’ file transfer from ftp.icgeb.trieste.it. Automated searching of SBASE can be carried out with the WWW servers http://www.icgeb.trieste.it/sbase/ and http://sbase.abc.hu/sbase/.
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The Plasmodium falciparum Genome Database (http://PlasmoDB.org) integrates sequence information, automated analyses and annotation data emerging from the P.falciparum genome sequencing consortium. To date, raw sequence coverage is available for >90% of the genome, and two chromosomes have been finished and annotated. Data in PlasmoDB are organized by chromosome (1–14), and can be accessed using a variety of tools for graphical and text-based browsing or downloaded in various file formats. The GUS (Genomics Unified Schema) implementation of PlasmoDB provides a multi-species genomic relational database, incorporating data from human and mouse, as well as P.falciparum. The relational schema uses a highly structured format to accommodate diverse data sets related to genomic sequence and gene expression. Tools have been designed to facilitate complex biological queries, including many that are specific to Plasmodium parasites and malaria as a disease. Additional projects seek to integrate genomic information with the rich data sets now becoming available for RNA transcription, protein expression, metabolic pathways, genetic and physical mapping, antigenic and population diversity, and phylogenetic relationships with other apicomplexan parasites. The overall goal of PlasmoDB is to facilitate Internet- and CD-ROM-based access to both finished and unfinished sequence information by the global malaria research community.
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When many protein sequences are available for estimating the time of divergence between two species, it is customary to estimate the time for each protein separately and then use the average for all proteins as the final estimate. However, it can be shown that this estimate generally has an upward bias, and that an unbiased estimate is obtained by using distances based on concatenated sequences. We have shown that two concatenation-based distances, i.e., average gamma distance weighted with sequence length (d2) and multiprotein gamma distance (d3), generally give more satisfactory results than other concatenation-based distances. Using these two distance measures for 104 protein sequences, we estimated the time of divergence between mice and rats to be approximately 33 million years ago. Similarly, the time of divergence between humans and rodents was estimated to be approximately 96 million years ago. We also investigated the dependency of time estimates on statistical methods and various assumptions made by using sequence data from eubacteria, protists, plants, fungi, and animals. Our best estimates of the times of divergence between eubacteria and eukaryotes, between protists and other eukaryotes, and between plants, fungi, and animals were 3, 1.7, and 1.3 billion years ago, respectively. However, estimates of ancient divergence times are subject to a substantial amount of error caused by uncertainty of the molecular clock, horizontal gene transfer, errors in sequence alignments, etc.
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The reactivation of telomerase activity in most cancer cells supports the concept that telomerase is a relevant target in oncology, and telomerase inhibitors have been proposed as new potential anticancer agents. The telomeric G-rich single-stranded DNA can adopt in vitro an intramolecular quadruplex structure, which has been shown to inhibit telomerase activity. We used a fluorescence assay to identify molecules that stabilize G-quadruplexes. Intramolecular folding of an oligonucleotide with four repeats of the human telomeric sequence into a G-quadruplex structure led to fluorescence excitation energy transfer between a donor (fluorescein) and an acceptor (tetramethylrhodamine) covalently attached to the 5′ and 3′ ends of the oligonucleotide, respectively. The melting of the G-quadruplex was monitored in the presence of putative G-quadruplex-binding molecules by measuring the fluorescence emission of the donor. A series of compounds (pentacyclic crescent-shaped dibenzophenanthroline derivatives) was shown to increase the melting temperature of the G-quadruplex by 2–20°C at 1 μM dye concentration. This increase in Tm value was well correlated with an increase in the efficiency of telomerase inhibition in vitro. The best telomerase inhibitor showed an IC50 value of 28 nM in a standard telomerase repeat amplification protocol assay. Fluorescence energy transfer can thus be used to reveal the formation of four-stranded DNA structures, and its stabilization by quadruplex-binding agents, in an effort to discover new potent telomerase inhibitors.
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We present here the complete genome sequence of a common avian clone of Pasteurella multocida, Pm70. The genome of Pm70 is a single circular chromosome 2,257,487 base pairs in length and contains 2,014 predicted coding regions, 6 ribosomal RNA operons, and 57 tRNAs. Genome-scale evolutionary analyses based on pairwise comparisons of 1,197 orthologous sequences between P. multocida, Haemophilus influenzae, and Escherichia coli suggest that P. multocida and H. influenzae diverged ≈270 million years ago and the γ subdivision of the proteobacteria radiated about 680 million years ago. Two previously undescribed open reading frames, accounting for ≈1% of the genome, encode large proteins with homology to the virulence-associated filamentous hemagglutinin of Bordetella pertussis. Consistent with the critical role of iron in the survival of many microbial pathogens, in silico and whole-genome microarray analyses identified more than 50 Pm70 genes with a potential role in iron acquisition and metabolism. Overall, the complete genomic sequence and preliminary functional analyses provide a foundation for future research into the mechanisms of pathogenesis and host specificity of this important multispecies pathogen.
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The release of vast quantities of DNA sequence data by large-scale genome and expressed sequence tag (EST) projects underlines the necessity for the development of efficient and inexpensive ways to link sequence databases with temporal and spatial expression profiles. Here we demonstrate the power of linking cDNA sequence data (including EST sequences) with transcript profiles revealed by cDNA-AFLP, a highly reproducible differential display method based on restriction enzyme digests and selective amplification under high stringency conditions. We have developed a computer program (GenEST) that predicts the sizes of virtual transcript-derived fragments (TDFs) of in silico-digested cDNA sequences retrieved from databases. The vast majority of the resulting virtual TDFs could be traced back among the thousands of TDFs displayed on cDNA-AFLP gels. Sequencing of the corresponding bands excised from cDNA-AFLP gels revealed no inconsistencies. As a consequence, cDNA sequence databases can be screened very efficiently to identify genes with relevant expression profiles. The other way round, it is possible to switch from cDNA-AFLP gels to sequences in the databases. Using the restriction enzyme recognition sites, the primer extensions and the estimated TDF size as identifiers, the DNA sequence(s) corresponding to a TDF with an interesting expression pattern can be identified. In this paper we show examples in both directions by analyzing the plant parasitic nematode Globodera rostochiensis. Various novel pathogenicity factors were identified by combining ESTs from the infective stage juveniles with expression profiles of ∼4000 genes in five developmental stages produced by cDNA-AFLP.
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The epsilon enhancer element is a pyrimidine-rich sequence that increases expression of T7 gene 10 and a number of Escherichia coli mRNAs during initiation of translation and inhibits expression of the recF mRNA during elongation. Based on its complementarity to the 460 region of 16S rRNA, it has been proposed that epsilon exerts its enhancer activity by base pairing to this complementary rRNA sequence. We have tested this model of enhancer action by constructing mutations in the 460 region of 16S rRNA and examining expression of epsilon-containing CAT reporter genes and recF–lacZ fusions in strains expressing the mutant rRNAs. Replacement of the 460 E.coli stem–loop with that of Salmonella enterica serovar Typhimurium or a stem–loop containing a reversal of all 8 bp in the helical region produced fully functional rRNAs with no apparent effect on cell growth or expression of any epsilon-containing mRNA. Our experiments confirm the reported effects of the epsilon elements on gene expression but show that these effects are independent of the sequence of the 460 region of 16S rRNA, indicating that epsilon–rRNA base pairing does not occur.
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As the number of protein folds is quite limited, a mode of analysis that will be increasingly common in the future, especially with the advent of structural genomics, is to survey and re-survey the finite parts list of folds from an expanding number of perspectives. We have developed a new resource, called PartsList, that lets one dynamically perform these comparative fold surveys. It is available on the web at http://bioinfo.mbb.yale.edu/partslist and http://www.partslist.org. The system is based on the existing fold classifications and functions as a form of companion annotation for them, providing ‘global views’ of many already completed fold surveys. The central idea in the system is that of comparison through ranking; PartsList will rank the approximately 420 folds based on more than 180 attributes. These include: (i) occurrence in a number of completely sequenced genomes (e.g. it will show the most common folds in the worm versus yeast); (ii) occurrence in the structure databank (e.g. most common folds in the PDB); (iii) both absolute and relative gene expression information (e.g. most changing folds in expression over the cell cycle); (iv) protein–protein interactions, based on experimental data in yeast and comprehensive PDB surveys (e.g. most interacting fold); (v) sensitivity to inserted transposons; (vi) the number of functions associated with the fold (e.g. most multi-functional folds); (vii) amino acid composition (e.g. most Cys-rich folds); (viii) protein motions (e.g. most mobile folds); and (ix) the level of similarity based on a comprehensive set of structural alignments (e.g. most structurally variable folds). The integration of whole-genome expression and protein–protein interaction data with structural information is a particularly novel feature of our system. We provide three ways of visualizing the rankings: a profiler emphasizing the progression of high and low ranks across many pre-selected attributes, a dynamic comparer for custom comparisons and a numerical rankings correlator. These allow one to directly compare very different attributes of a fold (e.g. expression level, genome occurrence and maximum motion) in the uniform numerical format of ranks. This uniform framework, in turn, highlights the way that the frequency of many of the attributes falls off with approximate power-law behavior (i.e. according to V–b, for attribute value V and constant exponent b), with a few folds having large values and most having small values.
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Ligand transport through myoglobin (Mb) has been observed by using optically heterodyne-detected transient grating spectroscopy. Experimental implementation using diffractive optics has provided unprecedented sensitivity for the study of protein motions by enabling the passive phase locking of the four beams that constitute the experiment, and an unambiguous separation of the Real and Imaginary parts of the signal. Ligand photodissociation of carboxymyoglobin (MbCO) induces a sequence of events involving the relaxation of the protein structure to accommodate ligand escape. These motions show up in the Real part of the signal. The ligand (CO) transport process involves an initial, small amplitude, change in volume, reflecting the transit time of the ligand through the protein, followed by a significantly larger volume change with ligand escape to the surrounding water. The latter process is well described by a single exponential process of 725 ± 15 ns at room temperature. The overall dynamics provide a distinctive signature that can be understood in the context of segmental protein fluctuations that aid ligand escape via a few specific cavities, and they suggest the existence of discrete escape pathways.
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We present a method for discovering conserved sequence motifs from families of aligned protein sequences. The method has been implemented as a computer program called emotif (http://motif.stanford.edu/emotif). Given an aligned set of protein sequences, emotif generates a set of motifs with a wide range of specificities and sensitivities. emotif also can generate motifs that describe possible subfamilies of a protein superfamily. A disjunction of such motifs often can represent the entire superfamily with high specificity and sensitivity. We have used emotif to generate sets of motifs from all 7,000 protein alignments in the blocks and prints databases. The resulting database, called identify (http://motif.stanford.edu/identify), contains more than 50,000 motifs. For each alignment, the database contains several motifs having a probability of matching a false positive that range from 10−10 to 10−5. Highly specific motifs are well suited for searching entire proteomes, while generating very few false predictions. identify assigns biological functions to 25–30% of all proteins encoded by the Saccharomyces cerevisiae genome and by several bacterial genomes. In particular, identify assigned functions to 172 of proteins of unknown function in the yeast genome.