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BIBI was designed to automate DNA sequence analysis for bacterial identification in the clinical field. BIBI relies on the use of BLAST and CLUSTAL W programs applied to different subsets of sequences extracted from GenBank. These sequences are filtered and stored in a new database, which is adapted to bacterial identification.
BACKGROUND: Massive gene expression changes in different cellular states measured by microarrays, in fact, reflect just an "echo" of real molecular processes in the cells. Transcription factors constitute a class of the regulatory molecules that typically require posttranscriptional modifications or ligand binding in order to exert their function. Therefore, such important functional changes of transcription factors are not directly visible in the microarray experiments. RESULTS: We developed a novel approach to find key transcription factors that may explain concerted expression changes of specific components of the signal transduction network. The approach aims at revealing evidence of positive feedback loops in the signal transduction circuits through activation of pathway-specific transcription factors. We demonstrate that promoters of genes encoding components of many known signal transduction pathways are enriched by binding sites of those transcription factors that are endpoints of the considered pathways. Application of the approach to the microarray gene expression data on TNF-alpha stimulated primary human endothelial cells helped to reveal novel key transcription factors potentially involved in the regulation of the signal transduction pathways of the cells. CONCLUSION: We developed a novel computational approach for revealing key transcription factors by knowledge-based analysis of gene expression data with the help of databases on gene regulatory networks (TRANSFAC and TRANSPATH. The corresponding software and databases are available at http://www.gene-regulation.com.
Russell Doolittle is a biocomputing pioneer who was among the first to use computers in the 1960s to compare sequences. He contributed to the discovery of unforeseen sequence similarities, such as the relationship between v-src and v-mos. Doolittle's reflection demonstrates the enormous advances made in bioinformatics, soft- and hardware, and the concurrent explosion in data storage and acceleration of communication. Today's advanced technology was not available at the beginning of Doolittle's career, when no databases existed, and researchers knew by heart most of the sequences which had been published.
MOTIVATION: By identifying an unknown gene or protein as a member of a known family, we can infer a wealth of previously compiled information pertinent to that family and its members. RESULTS: This paper introduces a method that classifies sequences using familial definitions from the PRINTS database, allowing progress to be made with the identification of distant evolutionary relationships. The approach makes use of the contextual information inherent in a multiple-motif method, and has the power to identify hitherto unidentified relationships in mass genome data. We exemplify our method by a comparison of database searches with uncharacterized sequences from the Caenorhabditis elegans and Saccharomyces cerevisiae genome projects. This analysis tool combines a simple, user-friendly interface with the capacity to provide an 'intelligent', biologically relevant result.
A computational method is proposed for inferring protein interactions from genome sequences on the basis of the observation that some pairs of interacting proteins have homologs in another organism fused into a single protein chain. Searching sequences from many genomes revealed 6809 such putative protein-protein interactions in Escherichia coli and 45,502 in yeast. Many members of these pairs were confirmed as functionally related; computational filtering further enriches for interactions. Some proteins have links to several other proteins; these coupled links appear to represent functional interactions such as complexes or pathways. Experimentally confirmed interacting pairs are documented in a Database of Interacting Proteins.
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A novel computer database program dedicated to storing, cataloging, and accessing information about recombinant clones and libraries has been developed for the IBM (or compatible) personal computer. This program, named CLONES, also stores information about bacterial strains and plasmid and bacteriophage vectors used in molecular biology. The advantages of this method are improved organization of data, fast and easy assimilation of new data, automatic association of new data with existing data, and rapid retrieval of desired records using search criteria specified by the user. Individual records are indexed in the database using B-trees, which automatically index new entries and expedite later access. The use of multiple windows, pull-down menus, scrolling pick-lists, and field-input techniques make the program intuitive to understand and easy to use. Daughter databases can be created to include all records of a particular type, or only those records matching user-specified search criteria. Separate databases can also be merged into a larger database. This computer program provides an easy-to-use and accurate means to organize, maintain, access, and share information about recombinant clones and other laboratory products of molecular biology technology.
Protein fold recognition is an important step towards understanding protein three-dimensional structures and their functions. A conditional graphical model, i.e., segmentation conditional random fields (SCRFs), is proposed as an effective solution to this problem. In contrast to traditional graphical models, such as the hidden Markov model (HMM), SCRFs follow a discriminative approach. Therefore, it is flexible to include any features in the model, such as overlapping or long-range interaction features over the whole sequence. The model also employs a convex optimization function, which results in globally optimal solutions to the model parameters. On the other hand, the segmentation setting in SCRFs makes their graphical structures intuitively similar to the protein 3-D structures and more importantly provides a framework to model the long-range interactions between secondary structures directly. Our model is applied to predict the parallel beta-helix fold, an important fold in bacterial pathogenesis and carbohydrate binding/cleavage. The cross-family validation shows that SCRFs not only can score all known beta-helices higher than non-beta-helices in the Protein Data Bank (PDB), but also accurately locates rungs in known beta-helix proteins. Our method outperforms BetaWrap, a state-of-the-art algorithm for predicting beta-helix folds, and HMMER, a general motif detection algorithm based on HMM, and has the additional advantage of general application to other protein folds. Applying our prediction model to the Uniprot Database, we identify previously unknown potential beta-helices.
MOTIVATION: Optimal sequence alignment based on the Smith-Waterman algorithm is usually too computationally demanding to be practical for searching large sequence databases. Heuristic programs like FASTA and BLAST have been developed which run much faster, but at the expense of sensitivity. RESULTS: In an effort to approximate the sensitivity of an optimal alignment algorithm, a new algorithm has been devised for the computation of a gapped alignment of two sequences. After scanning for high-scoring words and extensions of these to form fragments of similarity, the algorithm uses dynamic programming to build an accurate alignment based on the fragments initially identified. The algorithm has been implemented in a program called SALSA and the performance has been evaluated on a set of test sequences. The sensitivity was found to be close to the Smith-Waterman algorithm, while the speed was similar to FASTA (ktup = 2). AVAILABILITY: Searches can be performed from the SALSA homepage at http://dna.uio.no/salsa/ using a wide range of databases. Source code and precompiled executables are also available. CONTACT: torbjorn.rognes@labmed.uio.no
An elaboration of HERVd (http://herv.img.cas.cz) is being carried out in two directions. One of them is the integration and better classification of families that diverge considerably from typical retroviral genomes. This leads to a more precise identification of members with individual families. The second improvement is better accessibility of the database and connection with human genome annotation.
Gap penalty is an important component of the scoring scheme that is needed when searching for homologous proteins and for accurate alignment of protein sequences. Most homology search and sequence alignment algorithms employ a heuristic 'affine gap penalty' scheme q + r x n, in which q is the penalty for opening a gap, r the penalty for extending it and n the gap length. In order to devise a more rational scoring scheme, we examined the pattern of gaps that occur in a database of structurally aligned protein domain pairs. We find that the logarithm of the frequency of gaps varies linearly with the length of the gap, but with a break at a gap of length 3, and is well approximated by two linear regression lines with R2 values of 1.0 and 0.99. The bilinear behavior is retained when gaps are categorized by secondary structures of the two residues flanking the gap. Similar results were obtained when another, totally independent, structurally aligned protein pair database was used. These results suggest a modification of the affine gap penalty function.
BACKGROUND: Catalytic RNA molecules are called ribozymes. The aptamers are DNA or RNA molecules that have been selected from vast populations of random sequences, through a combinatorial approach known as SELEX. The selected oligo-nucleotide sequences (~200 bp in length) have the ability to recognize broad range of specific ligands by forming binding pockets. These novel aptamer sequences can bind to nucleic acids, proteins or small organic and inorganic chemical compounds and have many potential uses in medicine and technology. RESULTS: The comprehensive sequence information on aptamers and ribozymes that have been generated by in vitro selection methods are included in this RiboaptDB database. Such types of unnatural data generated by in vitro methods are not available in the public 'natural' sequence databases such as GenBank and EMBL. The amount of sequence data generated by in vitro selection experiments has been accumulating exponentially. There are 370 artificial ribozyme sequences and 3842 aptamer sequences in the total 4212 sequences from 423 citations in this RiboaptDB. We included general search feature, and individual feature wise search, user submission form for new data through online and also local BLAST search. CONCLUSION: This database, besides serving as a storehouse of sequences that may have diagnostic or therapeutic utility in medicine, provides valuable information for computational and theoretical biologists. The RiboaptDB is extremely useful for garnering information about in vitro selection experiments as a whole and for better understanding the distribution of functional nucleic acids in sequence space. The database is updated regularly and is publicly available at http://mfgn.usm.edu/ebl/riboapt/.
The Protein Information Resource (PIR) recently joined the European Bioinformatics Institute (EBI) and Swiss Institute of Bioinformatics (SIB) to establish UniProt--the Universal Protein Resource--which now unifies the PIR, Swiss-Prot and TrEMBL databases. The PIRSF (SuperFamily) classification system is central to the PIR/UniProt functional annotation of proteins, providing classifications of whole proteins into a network structure to reflect their evolutionary relationships. Data integration and associative studies of protein family, function and structure are supported by the iProClass database, which offers value-added descriptions of all UniProt proteins with highly informative links to more than 50 other databases. The PIR system allows consistent, rich and accurate protein annotation for all investigators.
To improve the accuracy of rapid homology searching it is common practice to filter all queries to mask low complexity regions prior to searching. We show in this paper, through a large-scale study of querying the PIR database, that applying popular filtering techniques unselectively to all queries may reduce retrieval effectiveness. We also show that masking queries with our new technique, cafefilter, which uses the overall distribution of motifs in a database, is at least as effective as current popular query filtering tools in large-scale tests.
In this paper we aim at presenting the main flavours and uses that are given to the term ontology in the bio-domains. The paper does not intend to be a thorough review of the existing work in the area. It highlights the uses that are given to ontologies in the Scientific Databases and Visualisation Group at EML Research, in Heidelberg.
The ultrawide-band (UWB) electromagnetic pulses are used as a new modality in radar technology. Biological effects of extremely high peak E-field, fast rise time, ultrashort pulse width, and ultrawide band have not been investigated heretofore due to the lack of animal exposure facilities. A new biological effects database is needed to establish personnel protection guidelines for these new type of radiofrequency radiation. Functional indices of the cardiovascular system (heart rate, systolic, mean, and diastolic pressures) were selected to represent biological end points that may be susceptible to the UWB radiation. A noninvasive tail-cuff photoelectric sensor sphygmomanometer was used. Male Wistar-Kyoto rats were subjected to sham exposure, 0.5-kHz (93 kV/m, 180 ps rise time, 1.00 ns pulse width, whole-body averaged specific absorption rate, SAR = 70 mW/kg) or a 1-kHz (85 kV/m, 200 ps rise time, 1.03 ns pulse width, SAR = 121 mW/kg) UWB fields in a tapered parallel plate GTEM cell for 6 min. Cardiovascular functions were evaluated from 45 min to 4 weeks after exposures. Significant decrease in arterial blood pressures (hypotension) was found. In contrast, heart rate was not altered by these exposures. The UWB radiation-induced hypotension was a robust, consistent, and persistent effect.
In this paper we will examine some ethical aspects of the role that computers and computing increasingly play in new genetics. Our claim is that there is no new genetics without computer science. Computer science is important for the new genetics on two levels: (1) from a theoretical perspective, and (2) from the point of view of geneticists practice. With respect to (1), the new genetics is fully impregnate with concepts that are basic for computer science. Regarding (2), recent developments in the Human Genome Project (HGP) have shown that computers shape the practices of molecular genetics; an important example is the Shotgun Method's contribution to accelerating the mapping of the human genome. A new challenge to the HGP is provided by the Open Source Philosophy (I computer science), which is another way computer technologies now influence the shaping of public policy debates involving genomics.
BACKGROUND: The metabolism of bacterial peptidoglycan is a dynamic process, synthases and cleavage enzymes are functionally coordinated. Lytic Transglycosylase enzymes (LT) are part of multienzyme complexes which regulate bacterial division and elongation. LTs are also involved in peptidoglycan turnover and in macromolecular transport systems. Despite their central importance, no LTs have been identified in the human pathogen Streptococcus pneumoniae. We report the identification of the first putative LT enzyme in S. pneumoniae and discuss its role in pneumococcal peptidoglycan metabolism. RESULTS: Homology searches of the pneumococcal genome allowed the identification of a new domain putatively involved in peptidoglycan cleavage (PECACE, PEptidoglycan CArbohydrate Cleavage Enzyme). This sequence has been found exclusively in Gram-positive bacteria and gene clusters containing pecace are conserved among Streptococcal species. The PECACE domain is, in some instances, found in association with other domains known to catalyze peptidoglycan hydrolysis. CONCLUSIONS: A new domain, PECACE, putatively involved in peptidoglycan hydrolysis has been identified in S. pneumoniae. The probable enzymatic activity deduced from the detailed analysis of the amino acid sequence suggests that the PECACE domain may proceed through a LT-type or goose lyzosyme-type cleavage mechanism. The PECACE function may differ largely from the other hydrolases already identified in the pneumococcus: LytA, LytB, LytC, CBPD and PcsB. The multimodular architecture of proteins containing the PECACE domain is another example of the many activities harbored by peptidoglycan hydrolases, which is probably required for the regulation of peptidoglycan metabolism. The release of new bacterial genomes sequences will probably add new members to the five groups identified so far in this work, and new groups could also emerge. Conversely, the functional characterization of the unknown domains mentioned in this work can now become easier, since bacterial peptidoglycan is proposed to be the substrate.