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PubMed2005

An OGSA-based integration of life-scientific resources for drug discovery.

OBJECTIVES: The rapid progress of life-scientific research has the potential to dramatically change the paradigm of drug discovery. Efficient utilization of life-scientific resources, i.e., databases and analytic software tools, poses a challenging issue with regard to the reduction of time and cost in the drug discovery process. In this paper, a variety of heterogeneous Web-based life-scientific resources are integrated toward the improvement of drug discovery performance. METHODS: For the integration of heterogeneous life-scientific resources, a database federation technique based on three-layer architecture has been utilized. With the federation technique, life-scientific resources are integrated step by step through database layers, database integration layers and analysis layers to encapsulate complexity and heterogeneity. In this study, we have taken advantage of the latest Grid technology based on OGSA (Open Grid Services Architecture) for the implementation of our approach. RESULTS: The actual case of life-scientific resources for drug discovery demonstrates that our prototype system developed with the proposed technique works well for the identification process of candidate compounds to a target protein. In other words, the prototype system allows a researcher to retrieve candidate compounds with less effort than before. CONCLUSIONS: The usefulness of the prototypic system represents the ability of our approach to integrate heterogeneous life-scientific resources, which have the potential to dramatically improve efficiency in drug discovery, resulting in the shortening of drug development. On the other hand, the system requires further consideration from the aspect of practical use. Dynamic aggregation of the resources is one example of such a consideration.

Biological Science Disciplines↗

PubMed2003

Provably sensitive indexing strategies for biosequence similarity search.

Fast algorithms for pairwise biosequence similarity search frequently use filtering and indexing strategies to identify potential matches between a query sequence and a database. For the most part, these strategies are not informed by the substitution score matrices commonly used by comparison algorithms to assign numerical scores to pairs of aligned residues. Consequently, although many filtering strategies offer strong formal guarantees about their ability to detect pairs of sequences differing by few substitutions, these methods can make no guarantee of detecting pairs with high similarity scores. We describe a general technique, score simulation, to help resolve the tension between existing filtering techniques and the use of score matrices. Score simulation, using score matrices, maps ungapped similarity search problems to the simpler problem of finding pairs of strings that differ by few substitutions. Score simulation leads to indexing schemes for biosequences that permit efficient ungapped similarity search with arbitrary score matrices while maintaining strong formal guarantees of sensitivity. We introduce the LSH-ALL-PAIRS-SIM algorithm for finding local similarities in large biosequence collections and show that it is both computationally feasible and sensitive in practice.

Computational Biology↗

PubMed2004

GermOnline, a cross-species community knowledgebase on germ cell differentiation.

GermOnline provides information and microarray expression data for genes involved in mitosis and meiosis, gamete formation and germ line development across species. The database has been developed, and is being curated and updated, by life scientists in cooperation with bioinformaticists. Information is contributed through an online form using free text, images and the controlled vocabulary developed by the GeneOntology Consortium. Authors provide up to three references in support of their contribution. The database is governed by an international board of scientists to ensure a standardized data format and the highest quality of GermOnline's information content. Release 2.0 provides exclusive access to microarray expression data from Saccharomyces cerevisiae and Rattus norvegicus, as well as curated information on approximately 700 genes from various organisms. The locus report pages include links to external databases that contain relevant annotation, microarray expression and proteome data. Conversely, the Saccharomyces Genome Database (SGD), S.cerevisiae GeneDB and Swiss-Prot link to the budding yeast section of GermOnline from their respective locus pages. GermOnline, a fully operational prototype subject-oriented knowledgebase designed for community annotation and array data visualization, is accessible at http://www.germonline.org. The target audience includes researchers who work on mitotic cell division, meiosis, gametogenesis, germ line development, human reproductive health and comparative genomics.

Animals↗

PubMed2003

Nonrandom tripeptide sequence distributions at protein carboxyl termini.

The availability of complete genome sequences enables the statistical analysis of sequence features without significant database-imposed bias. The carboxyl termini of proteins often contain regions associated with protein targeting and enhanced translational termination. We analyzed the frequency of occurrence of C-terminal tripeptides in representative archaeal, bacterial, and eukaryotic genomes. The sequence distribution in prokaryotic genomes nearly matches that generated by the randomization of the observed tripeptide set. In contrast, eukaryotic genomes contain large numbers of overrepresented sequences. Some of these correspond to highly repeated sequences from either duplicated endogenous genes or transposon open reading frames. Gratifyingly, others represent previously known targeting signals or sequences associated with an increase in translational termination efficiency. However, a number of overrepresented tripeptides have not been previously noted and may represent novel functional sequences. For example, the sequence XSS may enhance translational termination efficiency in plants, whereas FWC may be a targeting or processing signal for certain amino acid permeases in yeast.

Amino Acid Motifs↗

PubMed2005

Prediction of distant residue contacts with the use of evolutionary information.

In this work we present a novel correlated mutations analysis (CMA) method that is significantly more accurate than previously reported CMA methods. Calculation of correlation coefficients is based on physicochemical properties of residues (predictors) and not on substitution matrices. This results in reliable prediction of pairs of residues that are distant in protein sequence but proximal in its three dimensional tertiary structure. Multiple sequence alignments (MSA) containing a sequence of known structure for 127 families from PFAM database have been selected so that all major protein architectures described in CATH classification database are represented. Protein sequences in the selected families were filtered so that only those evolutionarily close to the target protein remain in the MSA. The average accuracy obtained for the alpha beta class of proteins was 26.8% of predicted proximal pairs with average improvement over random accuracy (IOR) of 6.41. Average accuracy is 20.6% for the mainly beta class and 14.4% for the mainly alpha class. The optimum correlation coefficient cutoff (cc cutoff) was found to be around 0.65. The first predictor, which correlates to hydrophobicity, provides the most reliable results. The other two predictors give good predictions which can be used in conjunction to those of the first one. When stricter cc cutoff is chosen, the average accuracy increases significantly (38.76% for alpha beta class), but the trade off is a smaller number of predictions. The use of solvent accessible area estimations for filtering false positives out of the predictions is promising.

Algorithms↗

PubMed2003

Recognition of translation initiation sites of eukaryotic genes based on an EM algorithm.

With the rapid increase of DNA databases of human and other eukaryotic model organisms, a large great number of genes need to be distinguished from the DNA databases. Exact recognition of translation initiation sites (TISs) of eukaryotic genes is very important to understand the translation initiation process, predict the detailed structure of eukaryotic genes, and annotate uncharacterized sequences. The problem has not been solved satisfactorily, especially for recognizing TISs of the eukaryotic genes with shorter first exons. It is an important task for extracting new features and finding new powerful algorithms for recognizing TISs of eukaryotic genes. In this paper, the important characteristics of shorter flanking fragments around TISs are extracted and an expectation-maximization (EM) algorithm based on incomplete data is used to recognize TISs of eukaryotic genes. The accuracy is up to 87.8% over a six-fold cross-validation test. The result shows that the identification variables are effectively extracted and the EM algorithm is a powerful tool to predict the TISs of eukaryotic genes. The algorithm also can be applied to other classification or clustering tasks in bioinformatics.

Algorithms↗

PubMed2006

CisView: a browser and database of cis-regulatory modules predicted in the mouse genome.

To facilitate the analysis of gene regulatory regions of the mouse genome, we developed a CisView (http://lgsun.grc.nia.nih.gov/cisview), a browser and database of genome-wide potential transcription factor binding sites (TFBSs) that were identified using 134 position-weight matrices and 219 sequence patterns from various sources and were presented with the information about sequence conservation, neighboring genes and their structures, GO annotations, protein domains, DNA repeats and CpG islands. Analysis of the distribution of TFBSs revealed that many TFBSs (N = 145) were over-represented near transcription start sites. We also identified potential cis-regulatory modules (CRMs) defined as clusters of conserved TFBSs in the entire mouse genome. Out of 739 074 CRMs, 157 442 had a significantly higher regulatory potential score than semi-random sequences generated with a 3rd-order Markov process. The CisView browser provides a user-friendly computer environment for studying transcription regulation on a whole-genome scale and can also be used for interpreting microarray experiments and identifying putative targets of transcription factors.

Animals↗

PubMed2004

Bioinformatics for glycomics: status, methods, requirements and perspectives.

The term 'glycomics' describes the scientific attempt to identify and study all the glycan molecules - the glycome - synthesised by an organism. The aim is to create a cell-by-cell catalogue of glycosyltransferase expression and detected glycan structures. The current status of databases and bioinformatics tools, which are still in their infancy, is reviewed. The structures of glycans as secondary gene products cannot be easily predicted from the DNA sequence. Glycan sequences cannot be described by a simple linear one-letter code as each pair of monosaccharides can be linked in several ways and branched structures can be formed. Few of the bioinformatics algorithms developed for genomics/proteomics can be directly adapted for glycomics. The development of algorithms, which allow a rapid, automatic interpretation of mass spectra to identify glycan structures is currently the most active field of research. The lack of generally accepted ways to normalise glycan structures and exchange glycan formats hampers an efficient cross-linking and the automatic exchange of distributed data. The upcoming glycomics should accept that unrestricted dissemination of scientific data accelerates scientific findings and initiates a number of new initiatives to explore the data.

Animals↗

PubMed2005

CGMIM: automated text-mining of Online Mendelian Inheritance in Man (OMIM) to identify genetically-associated cancers and candidate genes.

BACKGROUND: Online Mendelian Inheritance in Man (OMIM) is a computerized database of information about genes and heritable traits in human populations, based on information reported in the scientific literature. Our objective was to establish an automated text-mining system for OMIM that will identify genetically-related cancers and cancer-related genes. We developed the computer program CGMIM to search for entries in OMIM that are related to one or more cancer types. We performed manual searches of OMIM to verify the program results. RESULTS: In the OMIM database on September 30, 2004, CGMIM identified 1943 genes related to cancer. BRCA2 (OMIM *164757), BRAF (OMIM *164757) and CDKN2A (OMIM *600160) were each related to 14 types of cancer. There were 45 genes related to cancer of the esophagus, 121 genes related to cancer of the stomach, and 21 genes related to both. Analysis of CGMIM results indicate that fewer than three gene entries in OMIM should mention both, and the more than seven-fold discrepancy suggests cancers of the esophagus and stomach are more genetically related than current literature suggests. CONCLUSION: CGMIM identifies genetically-related cancers and cancer-related genes. In several ways, cancers with shared genetic etiology are anticipated to lead to further etiologic hypotheses and advances regarding environmental agents. CGMIM results are posted monthly and the source code can be obtained free of charge from the BC Cancer Research Centre website http://www.bccrc.ca/ccr/CGMIM

Algorithms↗

PubMed2001

Indexing huge genome sequences for solving various problems.

Because of the increase in the size of genome sequence databases, the importance of indexing the sequences for fast queries grows. Suffix trees and suffix arrays are used for simple queries. However these are not suitable for complicated queries from huge amount of sequences because the indices are stored in disk which has slow access speed. We propose storing the indices in memory in a compressed form. We use the compressed suffix array. It compactly stores the suffix array at the cost of theoretically a small slowdown in access speed. We experimentally show that the overhead of using the compressed suffix array is reasonable in practice. We also propose an approximate string matching algorithm which is suitable for the compressed suffix array. Furthermore, we have constructed the compressed suffix array of the whole human genome. Because its size is about 2G bytes, a workstation can handle the search index for the whole data in main memory, which will accelerate the speed of solving various problems in genome informatics.

Abstracting and Indexing↗

PubMed2004

Improved protein structure selection using decoy-dependent discriminatory functions.

BACKGROUND: A key component in protein structure prediction is a scoring or discriminatory function that can distinguish near-native conformations from misfolded ones. Various types of scoring functions have been developed to accomplish this goal, but their performance is not adequate to solve the structure selection problem. In addition, there is poor correlation between the scores and the accuracy of the generated conformations. RESULTS: We present a simple and nonparametric formula to estimate the accuracy of predicted conformations (or decoys). This scoring function, called the density score function, evaluates decoy conformations by performing an all-against-all Calpha RMSD (Root Mean Square Deviation) calculation in a given decoy set. We tested the density score function on 83 decoy sets grouped by their generation methods (4state_reduced, fisa, fisa_casp3, lmds, lattice_ssfit, semfold and Rosetta). The density scores have correlations as high as 0.9 with the Calpha RMSDs of the decoy conformations, measured relative to the experimental conformation for each decoy. We previously developed a residue-specific all-atom probability discriminatory function (RAPDF), which compiles statistics from a database of experimentally determined conformations, to aid in structure selection. Here, we present a decoy-dependent discriminatory function called self-RAPDF, where we compiled the atom-atom contact probabilities from all the conformations in a decoy set instead of using an ensemble of native conformations, with a weighting scheme based on the density scores. The self-RAPDF has a higher correlation with Calpha RMSD than RAPDF for 76/83 decoy sets, and selects better near-native conformations for 62/83 decoy sets. Self-RAPDF may be useful not only for selecting near-native conformations from decoy sets, but also for fold simulations and protein structure refinement. CONCLUSIONS: Both the density score and the self-RAPDF functions are decoy-dependent scoring functions for improved protein structure selection. Their success indicates that information from the ensemble of decoy conformations can be used to derive statistical probabilities and facilitate the identification of near-native structures.

Computational Biology↗

PubMed2001

A structural census of metabolic networks for E. coli.

A structural survey of the Escherichia coli proteins occurring in metabolic networks in the KEGG database (release 19 of LIGAND) has been carried out. A measure of structural coverage of a network is defined and calculated for each network. Twenty-four networks have 50 % or more of the enzyme steps assigned in E. coli and of these 21 have a structural coverage of 50 % or more. For those proteins that have a region matching a SCOP domain 50 % fall on or below the 30 % sequence identity threshold and represent non-trivial comparative modelling targets highlighting the need for experimental structure determination studies. The survey reveals the predominance of alpha/beta and alpha+beta folds for enzymes involved in metabolic pathways and that this general trend is maintained at the level of each pathway. The most popular superfamilies are coenzyme binding domains and are involved in the supply of energy to reactions. Although a few superfamilies are found in many pathways, in general there is a specificity of a particular superfamily for a particular pathway.

Binding Sites↗

PubMed2006

[A novel method of the genome-wide prediction for the target genes and its application].

Based on the protein databases of several model species, this study developed a new method of the Genome-wide prediction for the target genes, using Hidden Markov model by Perl programming. The advantages of this method are high throughput, high quality and easy prediction, especially in the case of multi-domains proteins families. By this method, we predicted the PPR and TPR proteins families in whole genome of several model species. There were 536 PPR proteins and 199 TPR proteins in Oryza sativa ssp. japonica, 519 PPR proteins and 177 TPR proteins in Oryza sativa L. ssp. indica, 735 PPR proteins and 292 TPR proteins in Arabidopsis thaliana, 6 PPR proteins and 32 TPR proteins in Cyanidioschyzon merolae. Synechococcus and Thermophilic archaebacterium did not have PPR proteins. By contrast, 10 TPR proteins were found in Synechococcus and 4 TPR proteins were found in Thermophilic archaebacterium. Moreover, of these results, some further bioinformatics analyses were conducted.

Bacterial Proteins↗

PubMed2004

FLAGdb++: a database for the functional analysis of the Arabidopsis genome.

FLAGdb++ is dedicated to the integration and visualization of data for high-throughput functional analysis of a fully sequenced genome, as illustrated for Arabidopsis. FLAGdb++ displays the predicted or experimental data in a position-dependent way and displays correlations and relationships between different features. FLAGdb++ provides for a given genome region, summarized characteristics of experimental materials like probe lengths, locations and specificities having an impact upon the confidence we will put in the experimental results. A selected subset of the available information is linked to a locus represented on an easy-to-interpret and memorable graphical display. Data are curated, processed and formatted before their integration into FLAGdb++. FLAGdb++ contains different options for easy back and forth navigation through many loci selected at the start of a session. It includes an original two-component visualization of the data, a genome-wide and a local view, which are permanently linked and display complementary information. Density curves along the chromosomes may be displayed in parallel for suggesting correlations between different structural and functional data. FLAGdb++ is fully accessible at http://genoplante-info.infobiogen.fr/FLAGdb/.

Arabidopsis↗

PubMed2006

Mycobacterium tuberculosis complex genetic diversity: mining the fourth international spoligotyping database (SpolDB4) for classification, population genetics and epidemiology.

BACKGROUND: The Direct Repeat locus of the Mycobacterium tuberculosis complex (MTC) is a member of the CRISPR (Clustered regularly interspaced short palindromic repeats) sequences family. Spoligotyping is the widely used PCR-based reverse-hybridization blotting technique that assays the genetic diversity of this locus and is useful both for clinical laboratory, molecular epidemiology, evolutionary and population genetics. It is easy, robust, cheap, and produces highly diverse portable numerical results, as the result of the combination of (1) Unique Events Polymorphism (UEP) (2) Insertion-Sequence-mediated genetic recombination. Genetic convergence, although rare, was also previously demonstrated. Three previous international spoligotype databases had partly revealed the global and local geographical structures of MTC bacilli populations, however, there was a need for the release of a new, more representative and extended, international spoligotyping database. RESULTS: The fourth international spoligotyping database, SpolDB4, describes 1939 shared-types (STs) representative of a total of 39,295 strains from 122 countries, which are tentatively classified into 62 clades/lineages using a mixed expert-based and bioinformatical approach. The SpolDB4 update adds 26 new potentially phylogeographically-specific MTC genotype families. It provides a clearer picture of the current MTC genomes diversity as well as on the relationships between the genetic attributes investigated (spoligotypes) and the infra-species classification and evolutionary history of the species. Indeed, an independent Naïve-Bayes mixture-model analysis has validated main of the previous supervised SpolDB3 classification results, confirming the usefulness of both supervised and unsupervised models as an approach to understand MTC population structure. Updated results on the epidemiological status of spoligotypes, as well as genetic prevalence maps on six main lineages are also shown. Our results suggests the existence of fine geographical genetic clines within MTC populations, that could mirror the passed and present Homo sapiens sapiens demographical and mycobacterial co-evolutionary history whose structure could be further reconstructed and modelled, thereby providing a large-scale conceptual framework of the global TB Epidemiologic Network. CONCLUSION: Our results broaden the knowledge of the global phylogeography of the MTC complex. SpolDB4 should be a very useful tool to better define the identity of a given MTC clinical isolate, and to better analyze the links between its current spreading and previous evolutionary history. The building and mining of extended MTC polymorphic genetic databases is in progress.

Computational Biology↗

PubMed2002

Long terminal repeat retrotransposons of Oryza sativa.

BACKGROUND: Long terminal repeat (LTR) retrotransposons constitute a major fraction of the genomes of higher plants. For example, retrotransposons comprise more than 50% of the maize genome and more than 90% of the wheat genome. LTR retrotransposons are believed to have contributed significantly to the evolution of genome structure and function. The genome sequencing of selected experimental and agriculturally important species is providing an unprecedented opportunity to view the patterns of variation existing among the entire complement of retrotransposons in complete genomes. RESULTS: Using a new data-mining program, LTR_STRUC, (LTR retrotransposon structure program), we have mined the GenBank rice (Oryza sativa) database as well as the more extensive (259 Mb) Monsanto rice dataset for LTR retrotransposons. Almost two-thirds (37) of the 59 families identified consist of copia-like elements, but gypsy-like elements outnumber copia-like elements by a ratio of approximately 2:1. At least 17% of the rice genome consists of LTR retrotransposons. In addition to the ubiquitous gypsy- and copia-like classes of LTR retrotransposons, the rice genome contains at least two novel families of unusually small, non-coding (non-autonomous) LTR retrotransposons. CONCLUSIONS: Each of the major clades of rice LTR retrotransposons is more closely related to elements present in other species than to the other clades of rice elements, suggesting that horizontal transfer may have occurred over the evolutionary history of rice LTR retrotransposons. Like LTR retrotransposons in other species with relatively small genomes, many rice LTR retrotransposons are relatively young, indicating a high rate of turnover.

Animals↗

PubMed2004

SCOR: Structural Classification of RNA, version 2.0.

SCOR, the Structural Classification of RNA (http://scor.lbl.gov), is a database designed to provide a comprehensive perspective and understanding of RNA motif three-dimensional structure, function, tertiary interactions and their relationships. SCOR 2.0 represents a major expansion and introduces a new classification organization. The new version represents the classification as a Directed Acyclic Graph (DAG), which allows a classification node to have multiple parents, in contrast to the strictly hierarchical classification used in SCOR 1.2. SCOR 2.0 supports three types of query terms in the updated search engine: PDB or NDB identifier, nucleotide sequence and keyword. We also provide parseable XML files for all information. This new release contains 511 RNA entries from the PDB as of 15 May 2003. A total of 5880 secondary structural elements are classified: 2104 hairpin loops and 3776 internal loops. RNA motifs reported in the literature, such as 'Kink turn' and 'GNRA loops', are now incorporated into the structural classification along with definitions and descriptions.

Animals↗

PubMed2004

Computational discovery of DNA motifs associated with cell type-specific gene expression in Ciona.

Temporally and spatially co-expressed genes are expected to be regulated by common transcription factors and therefore to share cis-regulatory elements. In the ascidian Ciona intestinalis, the whole-genome sequences and genome-scale gene expression profiles allow the use of computational techniques to investigate cis-elements that control transcription. We collected 5' flanking sequences of 50 tissue-specific genes from genome databases of C. intestinalis and a closely related species Ciona savignyi. We searched for DNA motifs over-represented in upstream regions of a group of co-expressed genes. Several motifs were distributed predominantly in upstream regions of photoreceptor, pan-neuronal, or muscle-specific gene groups. One muscle-specific motif, M2, was distributed preferentially in regions from -200 to -100 bp relative to the translational start sites. Promoters of muscle-specific genes of C. intestinalis were isolated, connected with a green fluorescent protein gene (GFP), and introduced into C. intestinalis embryos. In muscle cells, these promoters specifically drove GFP expression, which mutations of the M2 sites greatly reduced. When M2 sites were located upstream of a basal promoter, the reporter GFP was specifically expressed in muscle cells. These results suggest the validity of our computational prediction of cis-regulatory elements. Thus, bioinformatics can help identify cis-regulatory elements involved in chordate development.

Animals↗