PlasmoDB: the Plasmodium genome resource. An integrated database providing tools for accessing, analyzing and mapping expression and sequence data (both finished and unfinished)

PlasmoDB (http://PlasmoDB.org) is the official database of the Plasmodium falciparum genome sequencing consortium. This resource incorporates finished and draft genome sequence data and annotation emerging from Plasmodium sequencing projects. PlasmoDB currently houses information from five parasite species and provides tools for cross-species comparisons. Sequence information is also integrated with other genomic-scale data emerging from the Plasmodium research community, including gene expression analysis from EST, SAGE and microarray projects. The relational schemas used to build PlasmoDB [Genomics Unified Schema (GUS) and RNA Abundance Database (RAD)] employ a highly structured format to accommodate the diverse data types generated by sequence and expression projects. A variety of tools allow researchers to formulate complex, biologically based queries of the database. A version of the database is also available on CD-ROM (Plasmodium GenePlot), facilitating access to the data in situations where Internet access is difficult (e.g. by malaria researchers working in the field). The goal of PlasmoDB is to enhance utilization of the vast quantities of data emerging from genome-scale projects by the global malaria research community.     

The mouse genome database: a resource for today and tomorrow

The Mouse Genome Database supports the use of mice in genome research, offering researchers information on gene characterization, genetic maps, comparative genomic data, and phenotypes.     

Biophysical studies of phase separation integrating experimental and computational methods

Biomolecular phase separation that contributes to the formation of membraneless organelles and biomolecular condensates has recently gained tremendous attention because of the importance of these assemblies in physiology, disease, and engineering applications. Understanding and directing biomolecular phase separation requires a multiscale view of the biophysical properties of these phases. Yet, many classic tools to characterize biomolecular properties do not apply in these condensed phases. Here, we discuss insights obtained from spectroscopic methods, in particular nuclear magnetic resonance and optical spectroscopy, in understanding the molecular and atomic interactions that underlie the formation of protein-rich condensates. We also review approaches closely coupling nuclear magnetic resonance data with computational methods especially coarse-grained and all-atom molecular simulations, which provide insight into molecular features of phase separation. Finally, we point to future methodolical developments, particularly visualizing biophysical properties of condensates in cells.     

Chinese hamster genome database: an online resource for the CHO community at www.CHOgenome.org

The Chinese hamster genome database (http://www.chogenome.org/) is an online resource for the Chinese hamster (Cricetulus griseus) and Chinese hamster ovary (CHO) cell communities. CHO cells are important for biomedical research and are widely used in industry for the production of biopharmaceuticals. The genome of the CHO-K1 cell line was recently sequenced and the CHO community has developed an online resource to facilitate accessibility of the genomic data and the development of genomic tools.     

GERMINATE. a generic database for integrating genotypic and phenotypic information for plant genetic resource collections

The extensive germplasm resource collections that are now available for major crop plants and their wild relatives will increasingly provide valuable biological and bioinformatics resources for plant physiologists and geneticists to dissect the molecular basis of key traits and to develop highly adapted plant material to sustain future breeding programs. A key to the efficient deployment of these resources is the development of information systems that will enable the collection and storage of biological information for these plant lines to be integrated with the molecular information that is now becoming available through the use of high-throughput genomics and post-genomics technologies. The GERMINATE database has been designed to hold a diverse variety of data types, ranging from molecular to phenotypic, and to allow querying between such data for any plant species. Data are stored in GERMINATE in a technology-independent manner, such that new technologies can be accommodated in the database as they emerge, without modification of the underlying schema. Users can access data in GERMINATE databases either via a lightweight Perl-CGI Web interface or by the more complex Genomic Diversity and Phenotype Connection software. GERMINATE is released under the GNU General Public License and is available at http://germinate.scri.sari.ac.uk/germinate/.     

Phenosite: a web database integrating the mouse phenotyping platform and the experimental procedures in mice

Recently, a number of collaborative large-scale mouse mutagenesis programs have been launched. These programs aim for a better understanding of the roles of all individual coding genes and the biological systems in which these genes participate. In international efforts to share phenotypic data among facilities/institutes, it is desirable to integrate information obtained from different phenotypic platforms reliably. Since the definitions of specific phenotypes often depend on a tacit understanding of concepts that tends to vary among different facilities, it is necessary to define phenotypes based on the explicit evidence of assay results. We have developed a website termed PhenoSITE (Phenome Semantics Information with Terminology of Experiments: http://www.gsc.riken.jp/Mouse/), in which we are trying to integrate phenotype-related information using an experimental-evidence-based approach. The site's features include (1) a baseline database for our phenotyping platform; (2) an ontology associating international phenotypic definitions with experimental terminologies used in our phenotyping platform; (3) a database for standardized operation procedures of the phenotyping platform; and (4) a database for mouse mutants using data produced from the large-scale mutagenesis program at RIKEN GSC. We have developed two types of integrated viewers to enhance the accessibility to mutant resource information. One viewer depicts a matrix view of the ontology-based classification and chromosomal location of each gene; the other depicts ontology-mediated integration of experimental protocols, baseline data, and mutant information. These approaches rely entirely upon experiment-based evidence, ensuring the reliability of the integrated data from different phenotyping platforms.     

RIKEN tandem mass spectral database (ReSpect) for phytochemicals: A plant-specific MS/MS-based data resource and database

The fragment pattern analysis of tandem mass spectrometry (MS/MS) has long been used for the structural characterization of metabolites. The construction of a plant-specific MS/MS data resource and database will enable complex phytochemical structures to be narrowed down to candidate structures. Therefore, a web-based database of MS/MS data pertaining to phytochemicals was developed and named ReSpect (RIKEN tandem mass spectral database). Of the 3595 metabolites in ReSpect, 76% were derived from 163 literature reports, whereas the rest was obtained from authentic standards. As a main web application of ReSpect, a fragment search was established based on only the m/z values of query data and records. The confidence levels of the annotations were managed using the MS/MS fragmentation association rule, which is an algorithm for discovering common fragmentations in MS/MS data. Using this data resource and database, a case study was conducted for the annotation of untargeted MS/MS data that were selected after quantitative trait locus analysis of the accessions (Gifu and Miyakojima) of a model legume Lotus japonicus. In the case study, unknown metabolites were successfully narrowed down to putative structures in the website.     

OrthoParaMap: Distinguishing orthologs from paralogs by integrating comparative genome data and gene phylogenies

Background  

In eukaryotic genomes, most genes are members of gene families. When comparing genes from two species, therefore, most genes in one species will be homologous to multiple genes in the second. This often makes it difficult to distinguish orthologs (separated through speciation) from paralogs (separated by other types of gene duplication). Combining phylogenetic relationships and genomic position in both genomes helps to distinguish between these scenarios. This kind of comparison can also help to describe how gene families have evolved within a single genome that has undergone polyploidy or other large-scale duplications, as in the case of Arabidopsis thaliana – and probably most plant genomes.     

MITOMAP: a human mitochondrial genome database.

We have developed a comprehensive database (MITOMAP) for the human mitochondrial DNA (mtDNA), the first component of the human genome to be completely sequenced [Anderson et al. (1981) Nature 290, 457-465]. MITOMAP uses the mtDNA sequence as the unifying element for bringing together information on mitochondrial genome structure and function, pathogenic mutations and their clinical characteristics, population associated variation, and gene- gene interactions. As increasingly larger regions of the human genome are sequenced and characterized, the need for integrating such information will grow. Consequently, MITOMAP not only provides a valuable reference for the mitochondrial biologist, it may also provide a model for the development of information storage and retrieval systems for other components of the human genome.     

Redesigning, implementing and integrating Escherichia coli genome software tools with an object-oriented database system

This paper reports our exploratory work to redesign, implementand integrate a collection of genome software tools with anobject-oriented database system. Our software tools deal withgenome data from Escherichia coli K-12, a bacterium that hasbeen studied intensively and provides richer data sets thanany other living organism. The object-oriented DBMS used forthe integration is ONTOS, a commercial object-oriented systemfrom Ontologic Inc. This redesign and implementation task wasperformed in two steps. First, Cprograms were converted intoC+ +, and then the C+ + version programs were modified and integratedwith an object-oriented modeling of the data to form an ONTOSdatabase application. The first step helps us develop a conceptualview for a DBMS-independent object-oriented construct. The secondstep elucidates what additional DBMS-dependent modificationsteps are needed to provide persistency to the objects. Examplesare included to illustrate steps of the redesign and implementation.Overall, the outcome of this project demonstrates that programsand data can be successfully integrated with an object-orienteddatabase, while providing the objects with persistency and shareability.This paper includes discussions using concrete examples on whatadvantage the object–oriented database approach providesover the relational database approach.     

A Bayesian system integrating expression data with sequence patterns for localizing proteins: comprehensive application to the yeast genome

We develop a probabilistic system for predicting the subcellular localization of proteins and estimating the relative population of the various compartments in yeast. Our system employs a Bayesian approach, updating a protein's probability of being in a compartment, based on a diverse range of 30 features. These range from specific motifs (e.g. signal sequences or the HDEL motif) to overall properties of a sequence (e.g. surface composition or isoelectric point) to whole-genome data (e.g. absolute mRNA expression levels or their fluctuations). The strength of our approach is the easy integration of many features, particularly the whole-genome expression data. We construct a training and testing set of approximately 1300 yeast proteins with an experimentally known localization from merging, filtering, and standardizing the annotation in the MIPS, Swiss-Prot and YPD databases, and we achieve 75 % accuracy on individual protein predictions using this dataset. Moreover, we are able to estimate the relative protein population of the various compartments without requiring a definite localization for every protein. This approach, which is based on an analogy to formalism in quantum mechanics, gives better accuracy in determining relative compartment populations than that obtained by simply tallying the localization predictions for individual proteins (on the yeast proteins with known localization, 92% versus 74%). Our training and testing also highlights which of the 30 features are informative and which are redundant (19 being particularly useful). After developing our system, we apply it to the 4700 yeast proteins with currently unknown localization and estimate the relative population of the various compartments in the entire yeast genome. An unbiased prior is essential to this extrapolated estimate; for this, we use the MIPS localization catalogue, and adapt recent results on the localization of yeast proteins obtained by Snyder and colleagues using a minitransposon system. Our final localizations for all approximately 6000 proteins in the yeast genome are available over the web at: http://bioinfo.mbb.yale. edu/genome/localize.     

A comprehensive database of verified experimental data on protein folding kinetics

Insights into protein folding rely increasingly on the synergy between experimental and theoretical approaches. Developing successful computational models requires access to experimental data of sufficient quantity and high quality. We compiled folding rate constants for what initially appeared to be 184 proteins from 15 published collections/web databases. To generate the highest confidence in the dataset, we verified the reported lnk_f value and exact experimental construct and conditions from the original experimental report(s). The resulting comprehensive database of 126 verified entries, ACPro, will serve as a freely accessible resource ( https://www.ats.amherst.edu/protein/ ) for the protein folding community to enable confident testing of predictive models. In addition, we provide a streamlined submission form for researchers to add new folding kinetics results, requiring specification of all the relevant experimental information according to the standards proposed in 2005 by the protein folding consortium organized by Plaxco. As the number and diversity of proteins whose folding kinetics are studied expands, our curated database will enable efficient and confident incorporation of new experimental results into a standardized collection. This database will support a more robust symbiosis between experiment and theory, leading ultimately to more rapid and accurate insights into protein folding, stability, and dynamics.     

The peptaibol database: a sequence and structure resource.

The peptaibols are a large family of membrane-active peptides with considerable sequence homology, but with different biological properties and three-dimensional structures. They constitute a rich resource of naturally occurring 'mutants' which are potentially valuable for structure/function studies of ion channels. A searchable on-line database of sequences and structures of the peptaibols has been created at http://www.cryst.bbk.ac.uk/peptaibol, as a resource for the biological and structural community. In this paper, the contents and organization of the website are discussed as well as procedures for submission of new entries to the database. At present, more than 300 peptaibol sequences are stored in the database. Each sequence entry contains its full literature reference and information about its biological source. Tools are provided for searching for specific peptaibol sequences or groupings of sequences, and for locating peptaibols containing specified sequence motifs. In addition the website acts as a database for structural information. The coordinates of all currently available peptaibol x-ray and NMR structures are included and complemented, where appropriate. with molecular graphics illustrations. These include figures of model channel structures and comparisons between different peptaibol structures. The peptaibol database thus provides a tool for ready access to information and a means of investigating the sequences and structures of this class of polypeptides.     

Breast cancer: integrating the patient with her genome

Increasingly, gene expression data are becoming the currency of the realm in assessing disease prognosis. This has been especially evident in cancer, particularly those malignancies for which tumor samples are fairly accessible and understanding prognostic factors has clear implications for treatment decisions. Recently, Pittman et al. demonstrated substantially increased accuracy of personalized disease outcome prediction in breast cancer by integrating gene-expression profile data with traditional clinical risk factors in a set of 158 breast cancer patients.     

From Jabberwocky to genome: Lewis Carroll and computational biology.

In addition to his literary output, Lewis Carroll created a vast range of games and puzzles that depend upon wordplay of various kinds, especially the manipulation of alphabetic symbols in diverse contexts. Such wordplay reveals a turn of mind well suited to methodologies used in modern computational biology.