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LocustDB: a relational database for the transcriptome and biology of the migratory locust (Locusta migratoria).

BACKGROUND: The migratory locust (Locusta migratoria) is an orthopteran pest and a representative member of hemimetabolous insects for biological studies. Its transcriptomic data provide invaluable information for molecular entomology and pave a way for the comparative research of other medically, agronomically, and ecologically relevant insects. We developed the first transcriptomic database of the locust (LocustDB), building necessary infrastructures to integrate, organize, and retrieve data that are either currently available or to be acquired in the future. DESCRIPTION: LocustDB currently hosts 45,474 high-quality EST sequences from the locust, which were assembled into 12,161 unigenes. It, through user-friendly web interfaces, allows investigators to freely access sequence data, including homologous/orthologous sequences, functional annotations, and pathway analysis, based on conserved orthologous groups (COG), gene ontology (GO), protein domain (InterPro), and functional pathways (KEGG). It also provides information from comparative analysis based on data from the migratory locust and five other invertebrate species, including the silkworm, the honeybee, the fruitfly, the mosquito and the nematode. The website address of LocustDB is http://locustdb.genomics.org.cn/. CONCLUSION: LocustDB starts with the first transcriptome information for an orthopteran and hemimetabolous insect and will be extended to provide a framework for incorporating in-coming genomic data of relevant insect groups and a workbench for cross-species comparative studies.

Animals↗

Ultrawide-band electromagnetic pulses induced hypotension in rats.

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.

Animals↗

Sustainable databases.

Although the flood of cell biological knowledge rises relentlessly, many databases face an uncertain future. Unless funding for essential bioinformatic resources is set in stone, the next storm may wash away the foundation of future cell biology research.

Databases as Topic↗

A comparison of microarray databases.

Microarray technology has become one of the most important functional genomics technologies. A proliferation of microarray databases has resulted. It can be difficult for researchers exploring this technology to know which bioinformatics systems best meet their requirements. In order to obtain a better understanding of the available systems, a survey and comparative analysis of microarray databases was undertaken. The survey included databases that are currently available, as well as databases that should become available in early 2001. Databases fall into three categories: (i) those that can be installed locally, (ii) those available for public data submission and (iii) those available for public query. Developers of microarray gene-expression databases were asked questions regarding the scope and availability of their database, its system requirements, its future compliance with MGED (Microarray Gene Expression Database) standards, and its associated analytical tools. Participants included AMAD (Stanford/Berkeley/UCSF), ArrayExpress (EBI), ChipDB (MIT/Whitehead), GeneX (NCGR), GeNet (Silicon Genetics), GeneDirector (BioDiscovery), GEO (NCBI), GXD (Jackson Laboratory), mAdb (NCI), maxdSQL (University of Manchester), NOMAD (UCSF), RAD (University of Pennsylvania) and SMD (Stanford University). Other database developers were contacted but data was not available at the time of manuscript preparation. Each database fulfils a different role, reflecting the widely varying needs of microarray users.

Animals↗

A set-theoretic approach to database searching and clustering.

MOTIVATION: In this paper, we introduce an iterative method of database searching and apply it to design a database clustering algorithm applicable to an entire protein database. The clustering procedure relies on the quality of the database searching routine and further improves its results based on a set-theoretic analysis of a highly redundant yet efficient to generate cluster system. RESULTS: Overall, we achieve unambiguous assignment of 80% of SWISS-PROT sequences to non-overlapping sequence clusters in an entirely automatic fashion. Our results are compared to an expert-generated clustering for validation. The database searching method is fast and the clustering technique does not require time-consuming all-against-all comparison. This allows for fast clustering of large amounts of sequences. AVAILABILITY: The resulting clustering for the PIR1 (Release 51) and SWISS-PROT (Release 34) databases is available over the Internet from http://www.dkfz-heidelberg.de/tbi/services/modest/b rowsesysters.pl. CONTACT: a.krause@dkfz-heidelberg.de; m.vingron@dkfz-heidelberg.de

Algorithms↗

Retrieval and on-the-fly alignment of sequence fragments from the HIV database.

MOTIVATION: The amount of HIV-1 sequence data generated (presently around 42000 sequences, of which more than 22000 are from the V3 region of the viral envelope) presents a challenge for anyone working on the analysis of these data. A major problem is obtaining the region of interest from the stored sequences, which often contain but are not limited to that region. In addition, multiple alignment programs generally cannot deal with the large numbers of sequences that are available for many HIV-1 regions. We set out to provide our users with a tool that will retrieve and create an initial alignment of the HIV sequences that are available for a given genomic region. RESULTS: The MPAlign (Multiple Pairwise Alignment) web interface is a collection of Perl scripts that retrieves sequences from the Los Alamos HIV sequence database based on a number of search parameters. All sequences were pairwise-aligned to a model sequence using the Hidden Markov Model-based program HMMER. The HMMER model is general enough to accommodate virtually all HIV-1 sequences stored in the database. To create a multiple sequence alignment, gaps were inserted into the sequences during retrieval, so that they are aligned to one another. Retrieving and aligning the almost 560 gp120 sequences (approximately>1500 nt) stored in the database is at least 1500 times faster than a similar Clustal alignment.

Algorithms↗

RHdb: the Radiation Hybrid database.

Since July 1995, the European Bioinformatics Institute (EBI) has maintained RHdb (http://www.ebi.ac.uk/RHdb), a public database for radiation hybrid data. Radiation hybrid mapping is an important technique for determining high resolution maps. RHdb is also served by CORBA servers. The EBI is an Outstation of the European Molecular Biology Laboratory (EMBL).

Animals↗

DomIns: a web resource for domain insertions in known protein structures.

Proteins can be formed by single or multiple domains. The process of recombination at the molecular level has generated a wide variety of multi-domain proteins with specific domain organization to cater to the functional requirements of an organism. The functional and structural costs of inserting a domain into another means that multi-domain proteins are usually formed by covalently linking the N-terminus of one domain to the C-terminus of the preceding domain. While this is true in a large proportion of multi-domain proteins, we find a significant fraction of proteins that are the result of domain insertion. The inserted domain breaks the sequence contiguity of the domain into which it is inserted leading to a novel domain organization. This web resource aims to document domain insertions in known protein structures that are classified in the SCOP database. The web server can be accessed from http://stash.mrc-lmb.cam. ac.uk/DomIns/.

Amino Acid Sequence↗

Metabolic pathway analysis in trypanosomes and malaria parasites.

Identification of novel drug targets is required for the development of new classes of drugs to overcome drug resistance and replace less efficacious treatments. In theory, knowledge of the entire genome of a pathogen identifies every potential drug target in any given microbe. In practice, the sheer complexity and the inadequate or inaccurate annotation of genomic information makes target identification and selection somewhat more difficult. Analysis of metabolic pathways provides a useful conceptual framework for the identification of potential drug targets and also for improving our understanding of microbial responses to nutritional, chemical and other environmental stresses. A number of metabolic databases are available as tools for such analyses. The strengths and weaknesses of this approach are discussed.

Animals↗

Identification and characterization of subfamily-specific signatures in a large protein superfamily by a hidden Markov model approach.

BACKGROUND: Most profile and motif databases strive to classify protein sequences into a broad spectrum of protein families. The next step of such database studies should include the development of classification systems capable of distinguishing between subfamilies within a structurally and functionally diverse superfamily. This would be helpful in elucidating sequence-structure-function relationships of proteins. RESULTS: Here, we present a method to diagnose sequences into subfamilies by employing hidden Markov models (HMMs) to find windows of residues that are distinct among subfamilies (called signatures). The method starts with a multiple sequence alignment (MSA) of the subfamily. Then, we build a HMM database representing all sliding windows of the MSA of a fixed size. Finally, we construct a HMM histogram of the matches of each sliding window in the entire superfamily. To illustrate the efficacy of the method, we have applied the analysis to find subfamily signatures in two well-studied superfamilies: the cadherin and the EF-hand protein superfamilies. As a corollary, the HMM histograms of the analyzed subfamilies revealed information about their Ca2+ binding sites and loops. CONCLUSIONS: The method is used to create HMM databases to diagnose subfamilies of protein superfamilies that complement broad profile and motif databases such as BLOCKS, PROSITE, Pfam, SMART, PRINTS and InterPro.

Binding Sites↗

Domain fusion analysis by applying relational algebra to protein sequence and domain databases.

BACKGROUND: Domain fusion analysis is a useful method to predict functionally linked proteins that may be involved in direct protein-protein interactions or in the same metabolic or signaling pathway. As separate domain databases like BLOCKS, PROSITE, Pfam, SMART, PRINTS-S, ProDom, TIGRFAMs, and amalgamated domain databases like InterPro continue to grow in size and quality, a computational method to perform domain fusion analysis that leverages on these efforts will become increasingly powerful. RESULTS: This paper proposes a computational method employing relational algebra to find domain fusions in protein sequence databases. The feasibility of this method was illustrated on the SWISS-PROT+TrEMBL sequence database using domain predictions from the Pfam HMM (hidden Markov model) database. We identified 235 and 189 putative functionally linked protein partners in H. sapiens and S. cerevisiae, respectively. From scientific literature, we were able to confirm many of these functional linkages, while the remainder offer testable experimental hypothesis. Results can be viewed at http://calcium.uhnres.utoronto.ca/pi. CONCLUSION: As the analysis can be computed quickly on any relational database that supports standard SQL (structured query language), it can be dynamically updated along with the sequence and domain databases, thereby improving the quality of predictions over time.

Alternative Splicing↗

Biomedical informatics methods in pharmacogenomics.

Pharmacogenomics is the study of the genetic basis of individual variation in response to therapeutic agents. Pharmacogenomics may potentially affect on every step of health care and every drug treatment protocol. The optimal approach to pharmacogenomics in hypertension requires the integration of different disciplines, in which biomedical informatics plays an essential role. This chapter describes biomedical informatics methods used in dealing with key issues in pharmacogenomics. These key issues include the association between structure and function, the interaction between gene and drug, and the correlation between genotype and phenotype. Heterogeneous resources, including web sites, databases, and software analysis tools, are selected, organized, and integrated in practical methods to support these studies. Bioinformatics methods described in this chapter include genetic sequence searching, comparison, structural modeling, functional analysis, and systems biology studies, with emphasis on single-nucleotide polymorphism (SNP) analysis. Medical informatics methods such as disease and drug information and clinical terminology are also embraced in this chapter. This combination of both biological and medical informatics provides comprehensive methodologies to resolve complex problems in pharmacogenomics.

Computational Biology↗

A database of unique protein sequence identifiers for proteome studies.

In proteome studies, identification of proteins requires searching protein sequence databases. The public protein sequence databases (e.g., NCBInr, UniProt) each contain millions of entries, and private databases add thousands more. Although much of the sequence information in these databases is redundant, each database uses distinct identifiers for the identical protein sequence and often contains unique annotation information. Users of one database obtain a database-specific sequence identifier that is often difficult to reconcile with the identifiers from a different database. When multiple databases are used for searches or the databases being searched are updated frequently, interpreting the protein identifications and associated annotations can be problematic. We have developed a database of unique protein sequence identifiers called Sequence Globally Unique Identifiers (SEGUID) derived from primary protein sequences. These identifiers serve as a common link between multiple sequence databases and are resilient to annotation changes in either public or private databases throughout the lifetime of a given protein sequence. The SEGUID Database can be downloaded (http://bioinformatics.anl.gov/SEGUID/) or easily generated at any site with access to primary protein sequence databases. Since SEGUIDs are stable, predictions based on the primary sequence information (e.g., pI, Mr) can be calculated just once; we have generated approximately 500 different calculations for more than 2.5 million sequences. SEGUIDs are used to integrate MS and 2-DE data with bioinformatics information and provide the opportunity to search multiple protein sequence databases, thereby providing a higher probability of finding the most valid protein identifications.

Amino Acid Sequence↗

Plant genome databases: from references to inference tools.

Plant genome databases play an important role in the archiving and dissemination of data arising from the international genome projects. Recent developments in bioinformatics, such as new software tools, programming languages and standards, have produced better access across the Internet to the data held within them. An increasing emphasis is placed on data analysis and indeed many resources now provide tools allied to the databases, to aid in the analysis and interpretation of the data. However, a considerable wealth of information lies untapped by considering the databases as single entities and will only be exploited by linking them with a wide range of data sources. Data from research programs such as comparative mapping and germplasm studies may be used as tools, to gain additional knowledge but without additional experimentation. To date, the current plant genome databases are not yet linked comprehensively with each other or with these additional resources, although they are clearly moving toward this. Here, the current wealth of public plant genome databases is reviewed, together with an overview of initiatives underway to bind them to form a single plant genome infrastructure.

Computational Biology↗

BioMolQuest: integrated database-based retrieval of protein structural and functional information.

MOTIVATION: Information about a particular protein or protein family is usually distributed among multiple databases and often in more than one entry in each database. Retrieval and organization of this information can be a laborious task. This task is complicated even further by the existence of alternative terms for the same concept. RESULTS: The PDB, SWISS-PROT, ENZYME, and CATH databases have been imported into a combined relational database, BIOMOLQUEST: A powerful search engine has been built using this database as a back end. The search engine achieves significant improvements in query performance by automatically utilizing cross-references between the legacy databases. The results of the queries are presented in an organized, hierarchical way.

Abstracting and Indexing↗

Semi-automated update and cleanup of structural RNA alignment databases.

UNLABELLED: We have developed a series of programs which assist in maintenance of structural RNA databases. A main program BLASTs the RNA database against GenBank and automatically extends and realigns the sequences to include the entire range of the RNA query sequences. After manual update of the database, other programs can examine base pair consistency and phylogenetic support. The output can be applied iteratively to refine the structural alignment of the RNA database. Using these tools, the number of potential misannotations per sequence was reduced from 20 to 3 in the Signal Recognition Particle RNA database. AVAILABILITY: A quick-server and programs are available at http://www.bioinf.au.dk/rnadbtool/

Base Sequence↗

SUPFAM: a database of sequence superfamilies of protein domains.

BACKGROUND: SUPFAM database is a compilation of superfamily relationships between protein domain families of either known or unknown 3-D structure. In SUPFAM, sequence families from Pfam and structural families from SCOP are associated, using profile matching, to result in sequence superfamilies of known structure. Subsequently all-against-all family profile matches are made to deduce a list of new potential superfamilies of yet unknown structure. DESCRIPTION: The current version of SUPFAM (release 1.4) corresponds to significant enhancements and major developments compared to the earlier and basic version. In the present version we have used RPS-BLAST, which is robust and sensitive, for profile matching. The reliability of connections between protein families is ensured better than before by use of benchmarked criteria involving strict e-value cut-off and a minimal alignment length condition. An e-value based indication of reliability of connections is now presented in the database. Web access to a RPS-BLAST-based tool to associate a query sequence to one of the family profiles in SUPFAM is available with the current release. In terms of the scientific content the present release of SUPFAM is entirely reorganized with the use of 6190 Pfam families and 2317 structural families derived from SCOP. Due to a steep increase in the number of sequence and structural families used in SUPFAM the details of scientific content in the present release are almost entirely complementary to previous basic version. Of the 2286 families, we could relate 245 Pfam families with apparently no structural information to families of known 3-D structures, thus resulting in the identification of new families in the existing superfamilies. Using the profiles of 3904 Pfam families of yet unknown structure, an all-against-all comparison involving sequence-profile match resulted in clustering of 96 Pfam families into 39 new potential superfamilies. CONCLUSION: SUPFAM presents many non-trivial superfamily relationships of sequence families involved in a variety of functions and hence the information content is of interest to a wide scientific community. The grouping of related proteins without a known structure in SUPFAM is useful in identifying priority targets for structural genomics initiatives and in the assignment of putative functions. Database URL: http://pauling.mbu.iisc.ernet.in/~supfam.

Amino Acid Sequence↗

CASCAD: a database of annotated candidate single nucleotide polymorphisms associated with expressed sequences.

BACKGROUND: With the recent progress made in large-scale genome sequencing projects a vast amount of novel data is becoming available. A comparative sequence analysis, exploiting sequence information from various resources, can be used to uncover hidden information, such as genetic variation. Although there are enormous amounts of SNPs for a wide variety of organisms submitted to NCBI dbSNP and annotated in most genome assembly viewers like Ensembl and the UCSC Genome Browser, these platforms do not easily allow for extensive annotation and incorporation of experimental data supporting the polymorphism. However, such information is very important for selecting the most promising and useful candidate polymorphisms for use in experimental setups. DESCRIPTION: The CASCAD database is designed for presentation and query of candidate SNPs that are retrieved by in silico mining of high-throughput sequencing data. Currently, the database provides collections of laboratory rat (Rattus norvegicus) and zebrafish (Danio rerio) candidate SNPs. The database stores detailed information about raw data supporting the candidate, extensive annotation and links to external databases (e.g. GenBank, Ensembl, UniGene, and LocusLink), verification information, and predictions of a potential effect for non-synonymous polymorphisms in coding regions. The CASCAD website allows search based on an arbitrary combination of 27 different parameters related to characteristics like candidate SNP quality, genomic localization, and sequence data source or strain. In addition, the database can be queried with any custom nucleotide sequences of interest. The interface is crosslinked to other public databases and tightly coupled with primer design and local genome assembly interfaces in order to facilitate experimental verification of candidates. CONCLUSIONS: The CASCAD database discloses detailed information on rat and zebrafish candidate SNPs, including the raw data underlying its discovery. An advanced web-based search interface http://cascad.niob.knaw.nl allows universal access to the database content and allows various queries supporting many types of research utilizing single nucleotide polymorphisms.

Animals↗