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PubMed2003

Gene3D: structural assignments for the biologist and bioinformaticist alike.

The Gene3D database (http://www.biochem.ucl.ac.uk/bsm/cath_new/Gene3D/) provides structural assignments for genes within complete genomes. These are available via the internet from either the World Wide Web or FTP. Assignments are made using PSI-BLAST and subsequently processed using the DRange protocol. The DRange protocol is an empirically benchmarked method for assessing the validity of structural assignments made using sequence searching methods where appropriate assignment statistics are collected and made available. Gene3D links assignments to their appropriate entries in relevent structural and classification resources (PDBsum, CATH database and the Dictionary of Homologous Superfamilies). Release 2.0 of Gene3D includes 62 genomes, 2 eukaryotes, 10 archaea and 40 bacteria. Currently, structural assignments can be made for between 30 and 40 percent of any given genome. In any genome, around half of those genes assigned a structural domain are assigned a single domain and the other half of the genes are assigned multiple structural domains. Gene3D is linked to the CATH database and is updated with each new update of CATH.

Animals↗

PubMed2005

The PEDANT genome database in 2005.

The PEDANT genome database (http://pedant.gsf.de) contains pre-computed bioinformatics analyses of publicly available genomes. Its main mission is to provide robust automatic annotation of the vast majority of amino acid sequences, which have not been subjected to in-depth manual curation by human experts in high-quality protein sequence databases. By design PEDANT annotation is genome-oriented, making it possible to explore genomic context of gene products, and evaluate functional and structural content of genomes using a category-based query mechanism. At present, the PEDANT database contains exhaustive annotation of over 1,240,000 proteins from 270 eubacterial, 23 archeal and 41 eukaryotic genomes.

Computational Biology↗

PubMed2006

LMPD: LIPID MAPS proteome database.

The LIPID MAPS Proteome Database (LMPD) is an object-relational database of lipid-associated protein sequences and annotations. The initial release contains 2959 records, representing human and mouse proteins involved in lipid metabolism. UniProt IDs were obtained based on keyword search of KEGG and GO databases, and this LMPD protein list was then enhanced with annotations from UniProt, EntrezGene, ENZYME, GO, KEGG and other public resources. We also assigned associations with general lipid categories, based on GO and KEGG annotations. Users may search LMPD by database ID or keyword, and filter by species and/or lipid class associations; from the search results, one can then access a compilation of data relevant to each protein of interest, cross-linked to external databases. The LIPID MAPS Proteome Database (LMPD) is publicly available from the LIPID MAPS Consortium website (http://www.lipidmaps.org/). The direct URL is http://www.lipidmaps.org/data/proteome/index.cgi.

Animals↗

PubMed2006

Tractor_DB (version 2.0): a database of regulatory interactions in gamma-proteobacterial genomes.

The version 2.0 of Tractor_DB is now accessible at its three international mirrors: www.bioinfo.cu/Tractor_DB, www.tractor.lncc.br and http://www.ccg.unam.mx/tractorDB. This database contains a collection of computationally predicted Transcription Factors' binding sites in gamma-proteobacterial genomes. These data should aid researchers in the design of microarray experiments and the interpretation of their results. They should also facilitate studies of Comparative Genomics of the regulatory networks of this group of organisms. In this paper we describe the main improvements incorporated to the database in the past year and a half which include incorporating information on the regulatory networks of 13-increasing to 30-new gamma-proteobacteria and developing a new computational strategy to complement the putative sites identified by the original weight matrix-based approach. We have also added dynamically generated navigation tabs to the navigation interfaces. Moreover, we developed a new interface that allows users to directly retrieve information on the conservation of regulatory interactions in the 30 genomes included in the database by navigating a map that represents a core of the known Escherichia coli regulatory network.

Binding Sites↗

PubMed2006

A machine learning approach to predicting peptide fragmentation spectra.

Accurate peptide identification from tandem mass spectrometry experiments is the cornerstone of proteomics. Although various approaches for matching database sequences with experimental spectra have been developed to date (e.g. Sequest, Mascot) the sensitivity and specificity of peptide identification have not yet reached their full potential. This is in part due to the tradeoffs between robustness and accuracy of the existing methods with respect to the non-uniform nature of peptide fragmentation and bond cleavages induced by different mass spectrometers. Accordingly, it is expected that new approaches to de novo predicting peptide fragmentation spectra will enable more accurate peptide identification. To address this problem, here we used a data-driven approach to learn peptide fragmentation rules in mass spectrometry, in the form of posterior probabilities, for various fragment-ion types of doubly and triply charged precursor ions. We show that the accuracy of our neural-network based methodology is useful for subsequent peptide database searches and that the most useful rules of fragmentation significantly differ across ion and precursor types.

Amino Acids↗

PubMed2004

Molecular Genetics Information System (MOLGENIS): alternatives in developing local experimental genomics databases.

MOTIVATION: Genomic research laboratories need adequate infrastructure to support management of their data production and research workflow. But what makes infrastructure adequate? A lack of appropriate criteria makes any decision on buying or developing a system difficult. Here, we report on the decision process for the case of a molecular genetics group establishing a microarray laboratory. RESULTS: Five typical requirements for experimental genomics database systems were identified: (i) evolution ability to keep up with the fast developing genomics field; (ii) a suitable data model to deal with local diversity; (iii) suitable storage of data files in the system; (iv) easy exchange with other software; and (v) low maintenance costs. The computer scientists and the researchers of the local microarray laboratory considered alternative solutions for these five requirements and chose the following options: (i) use of automatic code generation; (ii) a customized data model based on standards; (iii) storage of datasets as black boxes instead of decomposing them in database tables; (iv) loosely linking to other programs for improved flexibility; and (v) a low-maintenance web-based user interface. Our team evaluated existing microarray databases and then decided to build a new system, Molecular Genetics Information System (MOLGENIS), implemented using code generation in a period of three months. This case can provide valuable insights and lessons to both software developers and a user community embarking on large-scale genomic projects. AVAILABILITY: http://www.molgenis.nl

Computational Biology↗

PubMed2004

CBS Genome Atlas Database: a dynamic storage for bioinformatic results and sequence data.

UNLABELLED: Currently, new bacterial genomes are being published on a monthly basis. With the growing amount of genome sequence data, there is a demand for a flexible and easy-to-maintain structure for storing sequence data and results from bioinformatic analysis. More than 150 sequenced bacterial genomes are now available, and comparisons of properties for taxonomically similar organisms are not readily available to many biologists. In addition to the most basic information, such as AT content, chromosome length, tRNA count and rRNA count, a large number of more complex calculations are needed to perform detailed comparative genomics. DNA structural calculations like curvature and stacking energy, DNA compositions like base skews, oligo skews and repeats at the local and global level are just a few of the analysis that are presented on the CBS Genome Atlas Web page. Complex analysis, changing methods and frequent addition of new models are factors that require a dynamic database layout. Using basic tools like the GNU Make system, csh, Perl and MySQL, we have created a flexible database environment for storing and maintaining such results for a collection of complete microbial genomes. Currently, these results counts to more than 220 pieces of information. The backbone of this solution consists of a program package written in Perl, which enables administrators to synchronize and update the database content. The MySQL database has been connected to the CBS web-server via PHP4, to present a dynamic web content for users outside the center. This solution is tightly fitted to existing server infrastructure and the solutions proposed here can perhaps serve as a template for other research groups to solve database issues. AVAILABILITY: A web based user interface which is dynamically linked to the Genome Atlas Database can be accessed via www.cbs.dtu.dk/services/GenomeAtlas/. SUPPLEMENTARY INFORMATION: This paper has a supplemental information page which links to the examples presented: www.cbs.dtu.dk/services/GenomeAtlas/suppl/bioinfdatabase.

Algorithms↗

PubMed2004

TrSDB: a proteome database of transcription factors.

TrSDB-TranScout Database-(http://ibb.uab.es/trsdb) is a proteome database of eukaryotic transcription factors based upon predicted motifs by TranScout and data sources such as InterPro and Gene Ontology Annotation. Nine eukaryotic proteomes are included in the current version. Extensive and diverse information for each database entry, different analyses considering TranScout classification and similarity relationships are offered for research on transcription factors or gene expression.

Amino Acid Motifs↗

PubMed2003

The Danish Registry for Plastic Surgery of the Breast: establishment of a nationwide registry for prospective follow-up, quality assessment, and investigation of breast surgery.

Although numerous epidemiologic studies have examined the long-term safety of silicone breast implants during the past decade, there is a relative lack of surveillance data on short-term health effects and complications following cosmetic surgery of the breast. The Danish Registry for Plastic Surgery of the Breast, established in May of 1999, provides plastic surgeons with a nationwide system for the collection of preoperative, perioperative, and postoperative data on women undergoing breast implantation, breast reduction, or mastopexy. The purpose of the Registry is to examine short-term and, eventually, long-term local complications and possible health effects, and to contribute to an ongoing evaluation of surgical results and surveillance of the products. Furthermore, the Registry will allow the identification of new areas for research into cosmetic and reconstructive breast surgery. Women accepting registration in the Danish Registry for Plastic Surgery of the Breast complete a self-administered questionnaire focusing on medical history and demographic and behavioral factors. Preoperative blood samples are drawn for storage. Surgical data, postoperative results, and complications are registered following surgery and at postoperative visits. Currently, registration has been initiated at 24 private and public clinics, representing more than 80 percent of the plastic surgery clinics in Denmark. As of November of 2001, a total of 1472 women with breast implants and 560 women with breast reduction were included in the Registry. These figures are expected to increase annually by 1000 women undergoing breast implantation and 500 women undergoing breast reduction or mastopexy. The authors present their experience of establishing the first nationwide comprehensive clinical-epidemiologic database and biological bank for cosmetic and reconstructive surgery procedures.

Breast Implants↗

PubMed2004

LySDB - Lysozyme Structural DataBase.

LySDB (Lysozyme Structural DataBase) is an integrated database containing 740 three-dimensional structures of lysozyme available in the Protein Data Bank. The database can be used to visualize the three-dimensional structure of the entire protein model or the substructures in which the user is interested (for example, insertions and deletions of amino acids) using the three-dimensional atomic coordinates. The database is provided with a search engine with several useful built-in facilities. The public domain graphics program RASMOL has been deployed for visualization. The three-dimensional structures used to create the database are updated at regular intervals and hence the users are provided with the current information available in the literature. The database LySDB is available over the World Wide Web and can be accessed at the URL http://iris.physics.iisc.ernet.in/lysdb/ or http://144.16.71.2/lysdb/.

Computational Biology↗

PubMed2003

Ascidians as a vertebrate-like model organism for physiological studies of Rho GTPase signaling.

GTPases of the Rho family are evolutionarily conserved proteins that control cell shape dynamics during physiological processes as diverse as cell migration and polarity, axon outgrowth and guidance, apoptosis and phagocytosis. In mammals, 18 Rho proteins are distributed in 7 subfamilies. Rho, Rac and Cdc42 are the best-characterized ones, benefiting from the use of worm and drosophila, which only express these 3 subfamilies. An additional model would therefore help understand the physiological role of other mammalian subfamilies. We identified in genome databases the complete Rho family of two ascidians, Ciona intestinalis and Ciona savignyi, and showed that these families contain single ancestors of most mammalian Rho subfamilies. In Ciona intestinalis, all Rho genes are expressed and display specific developmental variations of mRNA expression during tadpole formation. Although C. intestinalis expresses five additional Rac compared to the closely related Ciona savignyi, only two appeared fully active in functional assays. Last, we identified in Ciona intestinalis database more than 50 Rho regulators (RhoGEFs and RhoGAPs) and 20 effector targets, whose analysis further supports the notion that Rho signaling components are of comparable complexity in mammals and ascidians. Since the tadpole of ascidians combines vertebrate-like developmental features with reduced cell number, particularly adapted to evolutionary and developmental biology studies, our data advocate this model for physiological studies of Rho signaling pathways.

Actins↗

PubMed2004

Comprehensive de novo structure prediction in a systems-biology context for the archaea Halobacterium sp. NRC-1.

BACKGROUND: Large fractions of all fully sequenced genomes code for proteins of unknown function. Annotating these proteins of unknown function remains a critical bottleneck for systems biology and is crucial to understanding the biological relevance of genome-wide changes in mRNA and protein expression, protein-protein and protein-DNA interactions. The work reported here demonstrates that de novo structure prediction is now a viable option for providing general function information for many proteins of unknown function. RESULTS: We have used Rosetta de novo structure prediction to predict three-dimensional structures for 1,185 proteins and protein domains (<150 residues in length) found in Halobacterium NRC-1, a widely studied halophilic archaeon. Predicted structures were searched against the Protein Data Bank to identify fold similarities and extrapolate putative functions. They were analyzed in the context of a predicted association network composed of several sources of functional associations such as: predicted protein interactions, predicted operons, phylogenetic profile similarity and domain fusion. To illustrate this approach, we highlight three cases where our combined procedure has provided novel insights into our understanding of chemotaxis, possible prophage remnants in Halobacterium NRC-1 and archaeal transcriptional regulators. CONCLUSIONS: Simultaneous analysis of the association network, coordinated mRNA level changes in microarray experiments and genome-wide structure prediction has allowed us to glean significant biological insights into the roles of several Halobacterium NRC-1 proteins of previously unknown function, and significantly reduce the number of proteins encoded in the genome of this haloarchaeon for which no annotation is available.

Archaeal Proteins↗

PubMed2005

Where are we in genomics?

Genomic studies provide scientists with methods to quickly analyse genes and their products en masse. The first high-throughput techniques to be developed were sequencing methods. A great number of genomes from different organisms have thus been sequenced. Genomics is now shifting to the study of gene expression and function. In the past 5-10 years genomics, proteomics and high-throughput microarray technologies have fundamentally changed our ability to study the molecular basis of cells and tissues in health and diseases, giving a new comprehensive view. For example, in cancer research we have seen new diagnostic opportunities for tumour classification, and prognostication. A new exciting development is metabolomics and lab-on-a-chip techniques (which combine miniaturization and automation) for metabolic studies. However, to interpret the large amount of data, extensive computational development is required. In the coming years, we will see the study of biological networks dominating the scene in Physiology. The great accumulation of genomics information will be used in computer programs to simulate biologic processes. Originally developed for genome analysis, bioinformatics now encompasses a wide range of fields in biology from gene studies to integrated biology (i.e. combination of different data sets from genes to metabolites). This is systems biology which aims to study biological organisms as a whole. In medicine, scientific results and applied biotechnologies arising from genomics will be used for effective prediction of diseases and risk associated with drugs. Preventive medicine and medical therapy will be personalized. Widespread applications of genomics for personalized medicine will require associations of gene expression pattern with diagnoses, treatment and clinical data. This will help in the discovery and development of drugs. In agriculture and animal science, the outcomes of genomics will include improvement in food safety, in crop yield, in traceability and in quality of animal products (dairy products and meat) through increased efficiency in breeding and better knowledge of animal physiology. Genomics and integrated biology are huge tasks and no single lab can pursue this alone. We are probably at the end of the beginning rather than at the beginning of the end because Genomics will probably change Biology to a greater extent than previously forecasted. In addition, there is a great need for more information and better understanding of genomics before complete public acceptance.

Animals↗

PubMed2005

YAKUSA: a fast structural database scanning method.

YAKUSA is a program designed for rapid scanning of a structural database with a query protein structure. It searches for the longest common substructures called SHSPs (structural high-scoring pairs) existing between a query structure and every structure in the structural database. It makes use of protein backbone internal coordinates (alpha angles) in order to describe protein structures as sequences of symbols. The structural similarities are established in 5 steps, the first 3 being analogous to those used in BLAST: (1) building up a deterministic finite automaton describing all patterns identical or similar to those in the query structure; (2) searching for all these patterns in every structure in the database; (3) extending the patterns to longer matching substructures (i.e., SHSPs); (4) selecting compatible SHSPs for each query-database structure pair; and (5) ranking the query-database structure pairs using 3 scores based on SHSP similarity, on SHSP probabilities, and on spatial compatibility of SHSPs. Structural fragment probabilities are estimated according to a mixture transition distribution model, which is an approximation of a high-order Markov chain model. With regard to sensitivity and selectivity of the structural matches, YAKUSA compares well to the best related programs, although it is by far faster: A typical database scan takes about 40 s CPU time on a desktop personal computer. It has also been implemented on a Web server for real-time searches.

Algorithms↗

PubMed2001

Statistical inference of sequence-dependent mutation rates.

Several lines of research are now converging towards an integrated understanding of mutational mechanisms and their evolutionary implications. Experimentally, crystal structures reveal the effect of sequence context on polymerase fidelity; large-scale sequencing projects generate vast amounts of sequence polymorphism data; and locus-specific databases are being constructed. Computationally, software and analytical tools have been developed to analyze mutational data, to identify mutational hot spots, and to compare the signatures of mutagenic agents.

Computational Biology↗

PubMed2000

ASAP: analysis of peptide composition.

SUMMARY: ASAP is a web tool designed to search for specific dipeptides, tripeptides and tetrapeptides in a protein sequence database. The server allows for: (a) identification of frequent and infrequent peptides and the creation of peptide probability tables for a given database of sequences (GenerNet program), (b) determination of the compatibility of an amino-acid sequence to the given peptide probability tables (ClonErrNet program); and (c) comparison of different protein databases based on peptide composition (CompNet program). ASAP server can be useful in protein engineering and/or protein classification studies.

Computational Biology↗

PubMed2001

GEST: a gene expression search tool based on a novel Bayesian similarity metric.

Gene expression array technology has made possible the assay of expression levels of tens of thousands of genes at a time; large databases of such measurements are currently under construction. One important use of such databases is the ability to search for experiments that have similar gene expression levels as a query, potentially identifying previously unsuspected relationships among cellular states. Such searches depend crucially on the metric used to assess the similarity between pairs of experiments. The complex joint distribution of gene expression levels, particularly their correlational structure and non-normality, make simple similarity metrics such as Euclidean distance or correlational similarity scores suboptimal for use in this application. We present a similarity metric for gene expression array experiments that takes into account the complex joint distribution of expression values. We provide a computationally tractable approximation to this measure, and have implemented a database search tool based on it. We discuss implementation issues and efficiency, and we compare our new metric to other standard metrics.

Bayes Theorem↗

PubMed1999

PRINTS prepares for the new millennium.

PRINTS is a diagnostic collection of protein fingerprints. Fingerprints exploit groups of motifs to build characteristic family signatures, offering improved diagnostic reliability over single-motif approaches by virtue of the mutual context provided by motif neighbours. Around 1000 fingerprints have now been created and stored in PRINTS. The September 1998 release (version 20.0), encodes approximately 5700 motifs, covering a range of globular and membrane proteins, modular polypeptides and so on. The database is accessible via the DbBrowser Web Server at http://www.biochem.ucl.ac.uk/bsm/dbbrowser /. In addition to supporting its continued growth, recent enhancements to the resource include a BLAST server, and more efficient fingerprint search software, with improved statistics for estimating the reliability of retrieved matches. Current efforts are focused on the design of more automated methods for database maintenance; implementation of an object-relational schema for efficient data management; and integration with PROSITE, profiles, Pfam and ProDom, as part of the international InterPro project, which aims to unify protein pattern databases and offer improved tools for genome analysis.

Amino Acid Sequence↗