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PubMed2005

PRIME: automatically extracted PRotein Interactions and Molecular Information databasE.

With the exponentially increasing amount of information in the biomedical field, the significance of advanced information retrieval and information extraction, as well as the role of databases, has been increasing. PRIME is an integrated gene/protein informatics database based on natural language processing. It provides automatically extracted protein/family/gene/compound interaction information including both physical and genetic interactions, gene ontology based functions, and graphic pathway viewers. Gene/protein/family names and functional terms are recognized based on dictionaries developed in our laboratory. The interaction and functional information are extracted by syntactic dependencies and various phrase patterns. We have included about 920,000 (non-redundant) protein interactions and 360,000 annotated gene-function relationships for major eukaryotes. By combining the sequence and text information, the pathway comparison between two organisms and simple pathway deduction based on other organism interaction data, and pathway filtering using tissue expression data, are also available. This database is accessible at http://prime.ontology.ims.u-tokyo.ac.jp:8081.

Abstracting and Indexing↗
PubMed2004

Microarray-based in vitro evaluation of DNA oligomer libraries designed in silico.

We report on the microarray-based in vitro evaluation of two libraries of DNA oligonucleotide sequences, designed in silico for applications in supramolecular self-assembly, such as DNA computing and DNA-based nanosciences. In this first study which is devoted to the comparison of sequence motif properties theoretically predicted with their performance in real-life, the DNA-directed immobilization (DDI) of proteins was used as an example of DNA-based self-assembly. Since DDI technologies, DNA computing, and DNA nanoconstruction essentially depend on similar prereguisites, in particular, large and uniform hybridization efficiencies combined with low nonspecific cross-reactivity between individual sequences, we anticipate that the microarray approach demonstrated here will enable rapid evaluation of other DNA sequence libraries.

Base Sequence↗
PubMed2005

Tools enabling the elucidation of molecular pathways active in human disease: application to Hepatitis C virus infection.

BACKGROUND: The extraction of biological knowledge from genome-scale data sets requires its analysis in the context of additional biological information. The importance of integrating experimental data sets with molecular interaction networks has been recognized and applied to the study of model organisms, but its systematic application to the study of human disease has lagged behind due to the lack of tools for performing such integration. RESULTS: We have developed techniques and software tools for simplifying and streamlining the process of integration of diverse experimental data types in molecular networks, as well as for the analysis of these networks. We applied these techniques to extract, from genomic expression data from Hepatitis C virus-infected liver tissue, potentially useful hypotheses related to the onset of this disease. Our integration of the expression data with large-scale molecular interaction networks and subsequent analyses identified molecular pathways that appear to be induced or repressed in the response to Hepatitis C viral infection. CONCLUSION: The methods and tools we have implemented allow for the efficient dynamic integration and analysis of diverse data in a major human disease system. This integrated data set in turn enabled simple analyses to yield hypotheses related to the response to Hepatitis C viral infection.

Computational Biology↗
PubMed1999

Class II MHC quantitative binding motifs derived from a large molecular database with a versatile iterative stepwise discriminant analysis meta-algorithm.

MOTIVATION: The identification of T-cell epitopes can be crucial for vaccine development. An epitope is a peptide segment that binds to both a T-cell receptor and a major histocompatibility complex (MHC) molecule. Predicting which peptide segments bind MHC molecules is the first step in epitope prediction. RESULTS: An iterative stepwise discriminant analysis meta-algorithm explores a large molecular database to derive quantitative motifs for peptide binding. The applications presented here demonstrate the algorithm's versatility by producing four closely related models for HLA-DR1. Two models use an expert initial estimate and two do not; two models use amino acid residues as the only predictors and two use amino acid groupings as additional predictors. Each model correctly classifies >90% of the peptides in the database. AVAILABILITY: Software is available commercially; data are free over the Internet.

Algorithms↗
PubMed2002

Detecting compensatory covariation signals in protein evolution using reconstructed ancestral sequences.

When protein sequences divergently evolve under functional constraints, some individual amino acid replacements that reverse the charge (e.g. Lys to Asp) may be compensated by a replacement at a second position that reverses the charge in the opposite direction (e.g. Glu to Arg). When these side-chains are near in space (proximal), such double replacements might be driven by natural selection, if either is selectively disadvantageous, but both together restore fully the ability of the protein to contribute to fitness (are together "neutral"). Accordingly, many have sought to identify pairs of positions in a protein sequence that suffer compensatory replacements, often as a way to identify positions near in space in the folded structure. A "charge compensatory signal" might manifest itself in two ways. First, proximal charge compensatory replacements may occur more frequently than predicted from the product of the probabilities of individual positions suffering charge reversing replacements independently. Conversely, charge compensatory pairs of changes may be observed to occur more frequently in proximal pairs of sites than in the average pair. Normally, charge compensatory covariation is detected by comparing the sequences of extant proteins at the "leaves" of phylogenetic trees. We show here that the charge compensatory signal is more evident when it is sought by examining individual branches in the tree between reconstructed ancestral sequences at nodes in the tree. Here, we find that the signal is especially strong when the positions pairs are in a single secondary structural unit (e.g. alpha helix or beta strand) that brings the side-chains suffering charge compensatory covariation near in space, and may be useful in secondary structure prediction. Also, "node-node" and "node-leaf" compensatory covariation may be useful to identify the better of two equally parsimonious trees, in a way that is independent of the mathematical formalism used to construct the tree itself. Further, compensatory covariation may provide a signal that indicates whether an episode of sequence evolution contains more or less divergence in functional behavior. Compensatory covariation analysis on reconstructed evolutionary trees may become a valuable tool to analyze genome sequences, and use these analyses to extract biomedically useful information from proteome databases.

Amino Acid Sequence↗
PubMed1999

Genome-wide bioinformatic and molecular analysis of introns in Saccharomyces cerevisiae.

Introns have typically been discovered in an ad hoc fashion: introns are found as a gene is characterized for other reasons. As complete eukaryotic genome sequences become available, better methods for predicting RNA processing signals in raw sequence will be necessary in order to discover genes and predict their expression. Here we present a catalog of 228 yeast introns, arrived at through a combination of bioinformatic and molecular analysis. Introns annotated in the Saccharomyces Genome Database (SGD) were evaluated, questionable introns were removed after failing a test for splicing in vivo, and known introns absent from the SGD annotation were added. A novel branchpoint sequence, AAUUAAC, was identified within an annotated intron that lacks a six-of-seven match to the highly conserved branchpoint consensus UACUAAC. Analysis of the database corroborates many conclusions about pre-mRNA substrate requirements for splicing derived from experimental studies, but indicates that splicing in yeast may not be as rigidly determined by splice-site conservation as had previously been thought. Using this database and a molecular technique that directly displays the lariat intron products of spliced transcripts (intron display), we suggest that the current set of 228 introns is still not complete, and that additional intron-containing genes remain to be discovered in yeast. The database can be accessed at http://www.cse.ucsc.edu/research/compbi o/yeast_introns.html.

Computational Biology↗
PubMed2001

Functional information in SWISS-PROT: the basis for large-scale characterisation of protein sequences.

With the rapid growth of sequence databases, there is an increasing need for reliable functional characterisation and annotation of newly predicted proteins. To cope with such large data volumes, faster and more effective means of protein sequence characterisation and annotation are required. One promising approach is automatic large-scale functional characterisation and annotation, which is generated with limited human interaction. However, such an approach is heavily dependent on reliable data sources. The SWISS-PROT protein sequence database plays an essential role here owing to its high level of functional information.

Animals↗
PubMed2002

HMM-based databases in InterPro.

Protein family databases are an important resource for protein annotation and understanding protein evolution and function. In recent years hidden Markov models (HMMs) have become one of the key technologies used for detection of members of these families. This paper reviews the Pfam, TIGRFAMs and SMART databases that use the profile-HMMs provided by the HMMER package.

Computational Biology↗
PubMed2005

YeastHub: a semantic web use case for integrating data in the life sciences domain.

MOTIVATION: As the semantic web technology is maturing and the need for life sciences data integration over the web is growing, it is important to explore how data integration needs can be addressed by the semantic web. The main problem that we face in data integration is a lack of widely-accepted standards for expressing the syntax and semantics of the data. We address this problem by exploring the use of semantic web technologies-including resource description framework (RDF), RDF site summary (RSS), relational-database-to-RDF mapping (D2RQ) and native RDF data repository-to represent, store and query both metadata and data across life sciences datasets. RESULTS: As many biological datasets are presently available in tabular format, we introduce an RDF structure into which they can be converted. Also, we develop a prototype web-based application called YeastHub that demonstrates how a life sciences data warehouse can be built using a native RDF data store (Sesame). This data warehouse allows integration of different types of yeast genome data provided by different resources in different formats including the tabular and RDF formats. Once the data are loaded into the data warehouse, RDF-based queries can be formulated to retrieve and query the data in an integrated fashion. AVAILABILITY: The YeastHub website is accessible via the following URL: http://yeasthub.gersteinlab.org.

Biology↗
PubMed1999

The FlyBase database of the Drosophila Genome Projects and community literature.

The FlyBase Drosophila genetics database and the public interfaces of the Berkeley Drosophila Genome Project (BDGP) and European Drosophila Genome Project (EDGP) are in the process of integrating. At present, the data of these projects are available from independent, but hyperlinked, WWW sites (FlyBase URL, http://flybase. bio.indiana.edu/; BDGP URL, http://fruitfly.berkeley.edu/; EDGP URL, http://edgp.ebi.ac.uk/ ). Because of the considerable overlap of data classes between the contributions of the Drosophila genome projects and the Drosophila community, the new and enlarged FlyBase consortium views the implementation of a single integrated Drosophila genomics/genetics server as essential to the scientific community. This integration will occur in a stepwise fashion over the next 1-2 years. In this report, the salient features of the current databases and how to interrogate and navigate the extensive data sets are discussed.

Animals↗
PubMed2005

DSD--an integrated, web-accessible database of Dehydrogenase Enzyme Stereospecificities.

BACKGROUND: Dehydrogenase enzymes belong to the oxidoreductase class and utilise the coenzymes NAD and NADP. Stereo-selectivity is focused on the C4 hydrogen atoms of the nicotinamide ring of NAD(P). Depending upon which hydrogen is transferred at the C4 location, the enzyme is designated as A or B stereospecific. DESCRIPTION: The Dehydrogenase Stereospecificity Database v1.0 (DSD) provides a compilation of enzyme stereochemical data, as sourced from the primary literature, in the form of a web-accessible database. There are two search engines, a menu driven search and a BLAST search. The entries are also linked to several external databases, including the NCBI and the Protein Data Bank, providing wide background information. The database is freely available online at: http://www.jenner.ac.uk/DSD/. CONCLUSION: DSD is a unique compilation available on-line for the first time which provides a key resource for the comparative analysis of reductase hydrogen transfer stereospecificity. As databases increasingly form the backbone of science, largely complete databases such as DSD, are a vital addition.

Computational Biology↗
PubMed2005

IMGT-Choreography for immunogenetics and immunoinformatics.

IMGT, the international ImMunoGeneTics information system (http://imgt.cines.fr), was created in 1989 at Montpellier, France. IMGT is a high quality integrated knowledge resource specialized in immunoglobulins (IG), T cell receptors (TR), major histocompatibility complex (MHC) of human and other vertebrates, and related proteins of the immune system (RPI) which belong to the immunoglobulin superfamily (IgSF) and MHC superfamily (MhcSF). IMGT provides a common access to standardized data from genome, proteome, genetics and three-dimensional structures. The accuracy and the consistency of IMGT data are based on IMGT-ONTOLOGY, a semantic specification of terms to be used in immunogenetics and immunoinformatics. IMGT-ONTOLOGY has been formalized using XML Schema (IMGT-ML) for interoperability with other information systems. We are developing Web services to automatically query IMGT databases and tools. This is the first step towards IMGT-Choreography which will trigger and coordinate dynamic interactions between IMGT Web services to process complex significant biological and clinical requests. IMGT-Choreography will further increase the IMGT leadership in immunogenetics and immunoinformatics for medical research (repertoire analysis of the IG antibody sites and of the TR recognition sites in autoimmune and infectious diseases, AIDS, leukemias, lymphomas, myelomas), veterinary research (IG and TR repertoires in farm and wild life species), genome diversity and genome evolution studies of the adaptive immune responses, biotechnology related to antibody engineering (single chain Fragment variable (scFv), phage displays, combinatorial libraries, chimeric, humanized and human antibodies), diagnostics (detection and follow up of residual diseases) and therapeutical approaches (grafts, immunotherapy, vaccinology). IMGT is freely available at http://imgt.cines.fr.

Alleles↗
PubMed2005

Ontological visualization of protein-protein interactions.

BACKGROUND: Cellular processes require the interaction of many proteins across several cellular compartments. Determining the collective network of such interactions is an important aspect of understanding the role and regulation of individual proteins. The Gene Ontology (GO) is used by model organism databases and other bioinformatics resources to provide functional annotation of proteins. The annotation process provides a mechanism to document the binding of one protein with another. We have constructed protein interaction networks for mouse proteins utilizing the information encoded in the GO annotations. The work reported here presents a methodology for integrating and visualizing information on protein-protein interactions. RESULTS: GO annotation at Mouse Genome Informatics (MGI) captures 1318 curated, documented interactions. These include 129 binary interactions and 125 interaction involving three or more gene products. Three networks involve over 30 partners, the largest involving 109 proteins. Several tools are available at MGI to visualize and analyze these data. CONCLUSIONS: Curators at the MGI database annotate protein-protein interaction data from experimental reports from the literature. Integration of these data with the other types of data curated at MGI places protein binding data into the larger context of mouse biology and facilitates the generation of new biological hypotheses based on physical interactions among gene products.

Animals↗
PubMed2004

High-throughput molecular pathology in human tissues as a method for driving drug discovery.

To facilitate prioritization of potential drug targets, gene expression can be localized to individual cell types in normal and diseased tissues. Given the complexity of molecular physiology and pathology, the creation of large-scale molecular pathology databases collating data obtained from human tissues is a challenging marriage of old and new technologies, particularly when considering the many issues that preclude easy access to substantial quantities of human tissues. Molecular pathology databases are powerful tools and are essential for early-stage drug discovery, enabling informed decisions to be made with respect to scientific direction and follow-up research.

Computational Biology↗