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PubMed2005

Munich information center for protein sequences plant genome resources: a framework for integrative and comparative analyses 1(W).

With several plant genomes sequenced, the power of comparative genome analysis can now be applied. However, genome-scale cross-species analyses are limited by the effort for data integration. To develop an integrated cross-species plant genome resource, we maintain comprehensive databases for model plant genomes, including Arabidopsis (Arabidopsis thaliana), maize (Zea mays), Medicago truncatula, and rice (Oryza sativa). Integration of data and resources is emphasized, both in house as well as with external partners and databases. Manual curation and state-of-the-art bioinformatic analysis are combined to achieve quality data. Easy access to the data is provided through Web interfaces and visualization tools, bulk downloads, and Web services for application-level access. This allows a consistent view of the model plant genomes for comparative and evolutionary studies, the transfer of knowledge between species, and the integration with functional genomics data.

Computational Biology↗

PubMed2001

Defrosting the frozen approximation: PROSPECTOR--a new approach to threading.

PROSPECTOR (PROtein Structure Predictor Employing Combined Threading to Optimize Results) is a new threading approach that uses sequence profiles to generate an initial probe-template alignment and then uses this "partly thawed" alignment in the evaluation of pair interactions. Two types of sequence profiles are used: the close set, composed of sequences in which sequence identity lies between 35% and 90%; and the distant set, composed of sequences with a FASTA E-score less than 10. Thus, a total of four scoring functions are used in a hierarchical method: the close (distant) sequence profiles screen a structural database to provide an initial alignment of the probe sequence in each of the templates. The same database is then screened with a scoring function composed of sequence plus secondary structure plus pair interaction profiles. This combined hierarchical threading method is called PROSPECTOR1. For the original Fischer database, 59 of 68 pairs are correctly identified in the top position. Next, the set of the top 20 scoring sequences (four scoring functions times the top five structures) is used to construct a protein-specific pair potential based on consensus side-chain contacts occurring in 25% of the structures. In subsequent threading iterations, this protein-specific pair potential, when combined in a composite manner, is found to be more sensitive in identifying the correct pairs than when the original statistical potential is used, and it increases the number of recognized structures for the combined scoring functions, termed PROSPECTOR2, to a total of 61 Fischer pairs identified in the top position. Application to a second, smaller Fischer database of 27 probe-template pairs places 18 (17) structures in the top position for PROSPECTOR1 (PROSPECTOR2). Overall, these studies show that the use of pair interactions as assessed by the improved Z-score enhances the specificity of probe-template matches. Thus, when the hierarchy of scoring functions is combined, the ability to identify correct probe-template pairs is significantly enhanced. Finally, a web server has been established for use by the academic community (http://bioinformatics.danforthcenter.org/services/threading.html).

Benchmarking↗

PubMed2005

Exploring the genome of Trypanosoma vivax through GSS and in silico comparative analysis.

A survey of the Trypanosoma vivax genome was carried out by the genome sequence survey (GSS) approach resulting in 1,086 genomic sequences. A total of 455 high-quality GSS sequences were generated, consisting of 331 non-redundant sequences distributed in 264 singlets and 67 clusters in a total of 135.5 Kb of the T. vivax genome. The estimation of the overall G+C content, and the prediction of the presence of ORFs and putative genes were carried out using the Glimmer and Jemboss packages. Analysis of the obtained sequences was carried out by BLAST programs against 12 different databases and also using the Conserved Domain Database, InterProScan, and tRNAscan-SE. Along with the existing 23 T. vivax entries in the GenBank, the 32 putative genes predicted and the 331 non-redundant GSS sequences reported herein represent new potential markers for the development of PCRbased assays for specific diagnosis and typing of Trypanosoma vivax.

Algorithms↗

PubMed2006

cisRED: a database system for genome-scale computational discovery of regulatory elements.

We describe cisRED, a database for conserved regulatory elements that are identified and ranked by a genome-scale computational system (www.cisred.org). The database and high-throughput predictive pipeline are designed to address diverse target genomes in the context of rapidly evolving data resources and tools. Motifs are predicted in promoter regions using multiple discovery methods applied to sequence sets that include corresponding sequence regions from vertebrates. We estimate motif significance by applying discovery and post-processing methods to randomized sequence sets that are adaptively derived from target sequence sets, retain motifs with p-values below a threshold and identify groups of similar motifs and co-occurring motif patterns. The database offers information on atomic motifs, motif groups and patterns. It is web-accessible, and can be queried directly, downloaded or installed locally.

Animals↗

PubMed2007

Bioinformatics approaches to cancer gene discovery.

The Cancer Gene Anatomy Project (CGAP) database of the National Cancer Institute has thousands of known and novel expressed sequence tags (ESTs). These ESTs, derived from diverse normal and tumor cDNA libraries, offer an attractive starting point for cancer gene discovery. Data-mining the CGAP database led to the identification of ESTs that were predicted to be specific to select solid tumors. Two genes from these efforts were taken to proof of concept for diagnostic and therapeutics indications of cancer. Microarray technology was used in conjunction with bioinformatics to understand the mechanism of one of the targets discovered. These efforts provide an example of gene discovery by using bioinformatics approaches. The strengths and weaknesses of this approach are discussed in this review.

Basic Helix-Loop-Helix Proteins↗

PubMed2003

Synergistic computational and experimental proteomics approaches for more accurate detection of active serine hydrolases in yeast.

An analysis of the structurally and catalytically diverse serine hydrolase protein family in the Saccharomyces cerevisiae proteome was undertaken using two independent but complementary, large-scale approaches. The first approach is based on computational analysis of serine hydrolase active site structures; the second utilizes the chemical reactivity of the serine hydrolase active site in complex mixtures. These proteomics approaches share the ability to fractionate the complex proteome into functional subsets. Each method identified a significant number of sequences, but 15 proteins were identified by both methods. Eight of these were unannotated in the Saccharomyces Genome Database at the time of this study and are thus novel serine hydrolase identifications. Three of the previously uncharacterized proteins are members of a eukaryotic serine hydrolase family, designated as Fsh (family of serine hydrolase), identified here for the first time. OVCA2, a potential human tumor suppressor, and DYR-SCHPO, a dihydrofolate reductase from Schizosaccharomyces pombe, are members of this family. Comparing the combined results to results of other proteomic methods showed that only four of the 15 proteins were identified in a recent large-scale, "shotgun" proteomic analysis and eight were identified using a related, but similar, approach (neither identifies function). Only 10 of the 15 were annotated using alternate motif-based computational tools. The results demonstrate the precision derived from combining complementary, function-based approaches to extract biological information from complex proteomes. The chemical proteomics technology indicates that a functional protein is being expressed in the cell, while the computational proteomics technology adds details about the specific type of function and residue that is likely being labeled. The combination of synergistic methods facilitates analysis, enriches true positive results, and increases confidence in novel identifications. This work also highlights the risks inherent in annotation transfer and the use of scoring functions for determination of correct annotations.

Amino Acid Sequence↗

PubMed2000

Using database matches with for HMMGene for automated gene detection in Drosophila.

The application of the gene finder HMMGene to the Adh region of the Drosophila melanogaster is described, and the prediction results are analyzed. HMMGene is based on a probabilistic model called a hidden Markov model, and the probabilistic framework facilitates the inclusion of database matches of varying degrees of certainty. It is shown that database matches clearly improve the performance of the gene finder. For instance, the sensitivity for coding exons predicted with both ends correct grows from 62% to 70% on a high-quality test set, when matches to proteins, cDNAs, repeats, and transposons are included. The specificity drops more than the sensitivity increases when ESTs are used. This is due to the high noise level in EST matches, and it is discussed in more detail why this is and how it might be improved.

Alcohol Dehydrogenase↗

PubMed2006

Generation, annotation, and analysis of an extensive Aspergillus niger EST collection.

BACKGROUND: Aspergillus niger, a saprophyte commonly found on decaying vegetation, is widely used and studied for industrial purposes. Despite its place as one of the most important organisms for commercial applications, the lack of available information about its genetic makeup limits research with this filamentous fungus. RESULTS: We present here the analysis of 12,820 expressed sequence tags (ESTs) generated from A. niger cultured under seven different growth conditions. These ESTs identify about 5,108 genes of which 44.5% code for proteins sharing similarity (E < or = 1e(-5)) with GenBank entries of known function, 38% code for proteins that only share similarity with GenBank entries of unknown function and 17.5% encode proteins that do not have a GenBank homolog. Using the Gene Ontology hierarchy, we present a first classification of the A. niger proteins encoded by these genes and compare its protein repertoire with other well-studied fungal species. We have established a searchable web-based database that includes the EST and derived contig sequences and their annotation. Details about this project and access to the annotated A. niger database are available. CONCLUSION: This EST collection and its annotation provide a significant resource for fundamental and applied research with A. niger. The gene set identified in this manuscript will be highly useful in the annotation of the genome sequence of A. niger, the genes described in the manuscript, especially those encoding hydrolytic enzymes will provide a valuable source for researchers interested in enzyme properties and applications.

Aspergillus niger↗

PubMed2005

Immunogenetics Sequence Annotation: the Strategy of IMGT based on IMGT-ONTOLOGY.

IMGT, the international ImMunoGeneTics information system((R))(http://imgt.cines.fr) created in 1989, by the Laboratoire d'ImmunoGénétique Moléculaire (LIGM), Université Montpellier II and CNRS, Montpellier, France, is a high quality integrated information system, secialized in immunoglobulins (IG), T cell receptors (TR), major histocompatibility complex of human and other vertebrates and related proteins of the immune system that belong to the IgSF and Mhc superfamilies. IMGT/LIGM-DB, the first and the largest IMGT database, manages more than 92,000 IG and TR nucleotide sequences from human and 150 other vertebrate species in May 2005. IMGT/LIGM-DB provides expertly annotated sequences and standardized knowledge based on IMGT-ONTOLOGY, the first ontology for immunogenetics and immunoinformatics. The strategy developed by IMGT, for the IG and TR nucleotide sequence annotation, involves two different approaches that depend on the nature of the sequences, genomic DNA (gDNA) or complementary DNA (cDNA).

Animals↗

PubMed2004

MODBASE, a database of annotated comparative protein structure models, and associated resources.

MODBASE (http://salilab.org/modbase) is a relational database of annotated comparative protein structure models for all available protein sequences matched to at least one known protein structure. The models are calculated by MODPIPE, an automated modeling pipeline that relies on the MODELLER package for fold assignment, sequence-structure alignment, model building and model assessment (http:/salilab.org/modeller). MODBASE uses the MySQL relational database management system for flexible querying and CHIMERA for viewing the sequences and structures (http://www.cgl.ucsf.edu/chimera/). MODBASE is updated regularly to reflect the growth in protein sequence and structure databases, as well as improvements in the software for calculating the models. For ease of access, MODBASE is organized into different data sets. The largest data set contains 1,26,629 models for domains in 659,495 out of 1,182,126 unique protein sequences in the complete Swiss-Prot/TrEMBL database (August 25, 2003); only models based on alignments with significant similarity scores and models assessed to have the correct fold despite insignificant alignments are included. Another model data set supports target selection and structure-based annotation by the New York Structural Genomics Research Consortium; e.g. the 53 new structures produced by the consortium allowed us to characterize structurally 24,113 sequences. MODBASE also contains binding site predictions for small ligands and a set of predicted interactions between pairs of modeled sequences from the same genome. Our other resources associated with MODBASE include a comprehensive database of multiple protein structure alignments (DBALI, http://salilab.org/dbali) as well as web servers for automated comparative modeling with MODPIPE (MODWEB, http://salilab. org/modweb), modeling of loops in protein structures (MODLOOP, http://salilab.org/modloop) and predicting functional consequences of single nucleotide polymorphisms (SNPWEB, http://salilab. org/snpweb).

Amino Acid Sequence↗

PubMed2006

Dynamic tables: an architecture for managing evolving, heterogeneous biomedical data in relational database management systems.

Data sparsity and schema evolution issues affecting clinical informatics and bioinformatics communities have led to the adoption of vertical or object-attribute-value-based database schemas to overcome limitations posed when using conventional relational database technology. This paper explores these issues and discusses why biomedical data are difficult to model using conventional relational techniques. The authors propose a solution to these obstacles based on a relational database engine using a sparse, column-store architecture. The authors provide benchmarks comparing the performance of queries and schema-modification operations using three different strategies: (1) the standard conventional relational design; (2) past approaches used by biomedical informatics researchers; and (3) their sparse, column-store architecture. The performance results show that their architecture is a promising technique for storing and processing many types of data that are not handled well by the other two semantic data models.

Computational Biology↗

PubMed2001

Recent advances in computational genomics.

In the post-genomic era, the new discipline of functional genomics is now facing the challenge of associating a function (as well as estimating its relevance to industrial applications) to about 100,000 microbial, plant or animal genes of known sequence but unknown function. Besides the design of databases, computational methods are increasingly becoming intimately linked with the various experimental approaches. Consequently, bioinformatics is rapidly evolving into independent fields addressing the specific problems of interpreting i) genomic sequences, ii) protein sequences and 3D-structures, as well as iii) transcriptome and macromolecular interaction data. It is thus increasingly difficult for the biologist to choose the computational approaches that perform best in these various areas. This paper attempts to review the most useful developments of the last 2 years.

Computational Biology↗

PubMed2006

SPEED: a molecular-evolution-based database of mammalian orthologous groups.

MOTIVATION: The abundance of nucleotide sequence information available has expanded horizons of inquiry for molecular evolution; however, the full potential of whole-genome analysis has not been realized because of inadequate tools. Here, we present one of the first toolkits to aid multidisciplinary high-throughput analysis. SUMMARY: SPEED was created to integrate molecular evolutionary data with existing genetic resources and provide a straightforward user interface to 17,352 orthologous gene groups, containing representatives from eight mammalian species and an avian outgroup. AVAILABILITY: See http://bioinfobase.umkc.edu/speed/ for access.

Algorithms↗

PubMed2005

Comparison of the yeast proteome to other fungal genomes to find core fungal genes.

The purpose of this research was to search for evolutionarily conserved fungal sequences to test the hypothesis that fungi have a set of core genes that are not found in other organisms, as these genes may indicate what makes fungi different from other organisms. By comparing 6355 predicted or known yeast (Saccharomyces cerevisiae) genes to the genomes of 13 other fungi using Standalone TBLASTN at an e-value <1E-5, a list of 3340 yeast genes was obtained with homologs present in at least 12 of 14 fungal genomes. By comparing these common fungal genes to complete genomes of animals (Fugu rubripes, Caenorhabditis elegans), plants (Arabidopsis thaliana, Oryza sativa), and bacteria (Agrobacterium tumefaciens, Xylella fastidiosa), a list of common fungal genes with homologs in these plants, animals, and bacteria was produced (938 genes), as well as a list of exclusively fungal genes without homologs in these other genomes (60 genes). To ensure that the 60 genes were exclusively fungal, these were compared using TBLASTN to the major sequence databases at GenBank: NR (nonredundant), EST (expressed sequence tags), GSS (genome survey sequences), and HTGS (unfinished high-throughput genome sequences). This resulted in 17 yeast genes with homologs in other fungal genomes, but without known homologs in other organisms. These 17 core, fungal genes were not found to differ from other yeast genes in GC content or codon usage patterns. More intensive study is required of these 17 genes and other common fungal genes to discover unique features of fungi compared to other organisms.

Computational Biology↗

PubMed1998

EUCLID: automatic classification of proteins in functional classes by their database annotations.

UNLABELLED: A tool is described for the automatic classification of sequences in functional classes using their database annotations. The Euclid system is based on a simple learning procedure from examples provided by human experts. AVAILABILITY: Euclid is freely available for academics at http://www.gredos.cnb.uam.es/EUCLID, with the corresponding dictionaries for the generation of three, eight and 14 functional classes. CONTACT: E-mail: valencia@cnb.uam.es SUPPLEMENTARY INFORMATION: The results of the EUCLID classification of different genomes are available at http://www.sander.ebi.ac. uk/genequiz/. A detailed description of the different applications mentioned in the text is available at http://www.gredos.cnb.uam. es/EUCLID/Full_Paper

Computational Biology↗

PubMed2003

E-MSD: the European Bioinformatics Institute Macromolecular Structure Database.

The E-MSD macromolecular structure relational database (http://www.ebi.ac.uk/msd) is designed to be a single access point for protein and nucleic acid structures and related information. The database is derived from Protein Data Bank (PDB) entries. Relational database technologies are used in a comprehensive cleaning procedure to ensure data uniformity across the whole archive. The search database contains an extensive set of derived properties, goodness-of-fit indicators, and links to other EBI databases including InterPro, GO, and SWISS-PROT, together with links to SCOP, CATH, PFAM and PROSITE. A generic search interface is available, coupled with a fast secondary structure domain search tool.

Animals↗

PubMed2004

Update of NUREBASE: nuclear hormone receptor functional genomics.

Nuclear hormone receptors are an abundant class of ligand-activated transcriptional regulators, found in varying numbers in all animals. Based on our experience of managing the official nomenclature of nuclear receptors, we have developed NUREBASE, a database containing protein and DNA sequences, reviewed protein alignments and phylogenies, taxonomy and annotations for all nuclear receptors. New developments in NUREBASE include explicit declaration of alternative transcripts of each gene, and expression data for human and mouse nuclear receptors. The core of NUREBASE is reviewed, and it is completed by NUREBASE_DAILY, automatically updated every 24 h. All information on accessing and installing NUREBASE may be found at http://www. ens-lyon.fr/LBMC/laudet/nurebase/nurebase.html.

Alternative Splicing↗

PubMed2005

GLYCOSCIENCES.de: an Internet portal to support glycomics and glycobiology research.

The development of glycan-related databases and bioinformatics applications is considerably lagging behind compared with the wealth of available data and software tools in genomics and proteomics. Because the encoding of glycan structures is more complex, most of the bioinformatics approaches cannot be applied to glycan structures. No standard procedures exist where glycan structures found in various species, organs, tissues or cells can be routinely deposited. In this article the concepts of the GLYCOSCIENCES.de portal are described. It is demonstrated how an efficient structure-based cross-linking of various glycan-related data originating from different resources can be accomplished using a single user interface. The structure oriented retrieval options-exact structure, substructure, motif, composition and sugar components-are discussed. The types of available data-references, composition, spatial structures, nuclear magnetic resonance (NMR) shifts (experimental and estimated), theoretically calculated fragments and Protein Database (PDB) entries-are exemplified for Man(3.) The free availability and unrestricted use of glycan-related data is an absolute prerequisite to efficiently share distributed resources. Additionally, there is an urgent need to agree to a generally accepted exchange format as well as to a common software interface. An open access repository for glyco-related experimental data will secure that the loss of primary data will be considerably reduced.

Computational Biology↗