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This paper assesses the electrical generating capacity of the Copahue geothermal field. Because it plays a critical role in driving financial support, we discuss these results in terms of its geothermal project. We performed a set of estimates, including the volumetric method and wellhead output calculations. The former was supported by a 3D-geological model that allowed us to subdivide the reservoir into blocks to constraint the parameters to each zone better. The probability models estimate that the proved resource can produce more than 10.2 MWe and 13.5 MWe at 90 % and 50 % confidence level, respectively. The wellhead power output calculations were supported by long- and short- period discharge test performed at three production wells and one slim hole and by the analysis of its decline paths. We estimate 10 MWe in the most optimistic prediction ruling out the identified power plant decline, above 5 % per year. Regardless of the method, our results support less than half of the previously calculated proven power output (i.e., 30 MWe) used to scale the offered tenders to develop a power plant. Overestimation cases worldwide invite us to be even more restricted over our power capacity estimations. Moreover, a tighter characterization of the reservoir volume (e.g., Chilean ranking) could redefine it from proven to probable, increasing the uncertainty over the resource. Throughout its 50 years of history the Copahue Geothermal Project reached significant milestones (first power plant on South America, a district –heating system, and four drilled wells). However, an in-depth review of the project history revealed several setbacks (closure of the power generation and direct use projects because of technical issues, developer retreatments, inadequate tenders) that partially explain its current on-hold status. We concluded that more work is needed before advancing towards the development stage of the project. The vast heat storage at Copahue is beyond doubt, but it is mandatory to improve the estimations of the steam supply, enhance the success rate of wells by a new drilling exploration stage, resize the projected power plant and perform a more accurate feasibility report. New attempts to attract investors and future developers should consider these goals and the project history to avoid new setbacks.

Torrents of genotype-phenotype data are being generated, all of which must be captured, processed, integrated, and exploited. To do this optimally requires the use of standard and interoperable "object models," providing a description of how to partition the total spectrum of information being dealt with into elemental "objects" (such as "alleles," "genotypes," "phenotype values," "methods") with precisely stated logical interrelationships (such as "A objects are made up from one or more B objects"). We herein propose the Phenotype and Genotype Experiment Object Model (PaGE-OM; www.pageom.org), which has been tested and implemented in conjunction with several major databases, and approved as a standard by the Object Management Group (OMG). PaGE-OM is open-source, ready for use by the wider community, and can be further developed as needs arise. It will help to improve information management, assist data integration, and simplify the task of informatics resource design and construction for genotype and phenotype data projects.

Life sciences research is based on individuals, often with diverse skills, assembled into research groups. These groups use their specialist expertise to address scientific problems. The in silico experiments undertaken by these research groups can be represented as workflows involving the co-ordinated use of analysis programs and information repositories that may be globally distributed. With regards to Grid computing, the requirements relate to the sharing of analysis and information resources rather than sharing computational power. The myGrid project has developed the Taverna Workbench for the composition and execution of workflows for the life sciences community. This experience paper describes lessons learnt during the development of Taverna. A common theme is the importance of understanding how workflows fit into the scientists' experimental context. The lessons reflect an evolving understanding of life scientists' requirements on a workflow environment, which is relevant to other areas of data intensive and exploratory science.

SOAP (Simple Object Access Protocol) (http://www.w3.org/TR/soap) based Web Services technology (http://www.w3.org/ws) has gained much attention as an open standard enabling interoperability among applications across heterogeneous architectures and different networks. The European Bioinformatics Institute (EBI) is using this technology to provide robust data retrieval and data analysis mechanisms to the scientific community and to enhance utilization of the biological resources it already provides [N. Harte, V. Silventoinen, E. Quevillon, S. Robinson, K. Kallio, X. Fustero, P. Patel, P. Jokinen and R. Lopez (2004) Nucleic Acids Res., 32, 3-9]. These services are available free to all users from http://www.ebi.ac.uk/Tools/webservices.

Motivation: In silico experiments in bioinformatics involve the co-ordinated use of computational tools and information repositories. A growing number of these resources are being made available with programmatic access in the form of Web services. Bioinformatics scientists will need to orchestrate these Web services in workflows as part of their analyses. Results: The Taverna project has developed a tool for the composition and enactment of bioinformatics workflows for the life sciences community. The tool includes a workbench application which provides a graphical user interface for the composition of workflows. These workflows are written in a new language called the simple conceptual unified flow language (Scufl), where by each step within a workflow represents one atomic task. Two examples are used to illustrate the ease by which in silico experiments can be represented as Scufl workflows using the workbench application. Availability: The Taverna workflow system is available as open source and can be downloaded with example Scufl workflows from http://taverna.sourceforge.net

The Generation Challenge programme (GCP) is a global crop research consortium directed toward crop improvement through the application of comparative biology and genetic resources characterization to plant breeding. A key consortium research activity is the development of a GCP crop bioinformatics platform to support GCP research. This platform includes the following: (i) shared, public platform-independent domain models, ontology, and data formats to enable interoperability of data and analysis flows within the platform; (ii) web service and registry technologies to identify, share, and integrate information across diverse, globally dispersed data sources, as well as to access high-performance computational (HPC) facilities for computationally intensive, high-throughput analyses of project data; (iii) platform-specific middleware reference implementations of the domain model integrating a suite of public (largely open-access/-source) databases and software tools into a workbench to facilitate biodiversity analysis, comparative analysis of crop genomic data, and plant breeding decision making.

We aim to develop an open software system to handle human genome data. The system, called Integrated Genomic Database (IGD), will integrate information from many genomic databases and experimental resources into a comprehensive target-end database (IGD TED). Users will access front-end client systems (IGD FRED) to download data of interest to their computers and merge them with their own local data. FREDs will provide persistent storage of, and instant access to, retrieved data; a friendly graphical interface; tools for querying, browsing, analyzing, and editing local data; interface to external analysis; and tools for communicating with the outside world. The TED will be accessible over the network (online and offline) as a read-only resource for multiple clients. It collects data from major databases for nucleotide and protein sequences and structures, genome maps, experimental reagents, phenotypes, and bibliographic data, and sets of raw data produced at genome centers and laboratories. Beside character-based access via Gopher, WAIS, FTP, and several query language interfaces to the TED, we will develop a specialized front-end client, IGD FRED, with its own database manager, based on the ACEDB program. The FRED will support graphical display methods for sequence feature maps, chromosomal genetic and physical maps, and experimental objects like clone grids, etc. FRED will also provide an interface to important analysis software packages and tools for submitting data to external databases in their own format.

The ‘Crop Ontology’ database we describe provides a controlled vocabulary for several economically important crops. It facilitates data integration and discovery from global databases and digital literature. This allows researchers to exploit comparative phenotypic and genotypic information of crops to elucidate functional aspects of traits., Background and aims Agricultural crop databases maintained in gene banks of the Consultative Group on International Agricultural Research (CGIAR) are valuable sources of information for breeders. These databases provide comparative phenotypic and genotypic information that can help elucidate functional aspects of plant and agricultural biology. To facilitate data sharing within and between these databases and the retrieval of information, the crop ontology (CO) database was designed to provide controlled vocabulary sets for several economically important plant species. Methodology Existing public ontologies and equivalent catalogues of concepts covering the range of crop science information and descriptors for crops and crop-related traits were collected from breeders, physiologists, agronomists, and researchers in the CGIAR consortium. For each crop, relationships between terms were identified and crop-specific trait ontologies were constructed following the Open Biomedical Ontologies (OBO) format standard using the OBO-Edit tool. All terms within an ontology were assigned a globally unique CO term identifier. Principal results The CO currently comprises crop-specific traits for chickpea (Cicer arietinum), maize (Zea mays), potato (Solanum tuberosum), rice (Oryza sativa), sorghum (Sorghum spp.) and wheat (Triticum spp.). Several plant-structure and anatomy-related terms for banana (Musa spp.), wheat and maize are also included. In addition, multi-crop passport terms are included as controlled vocabularies for sharing information on germplasm. Two web-based online resources were built to make these COs available to the scientific community: the ‘CO Lookup Service’ for browsing the CO; and the ‘Crops Terminizer’, an ontology text mark-up tool. Conclusions The controlled vocabularies of the CO are being used to curate several CGIAR centres' agronomic databases. The use of ontology terms to describe agronomic phenotypes and the accurate mapping of these descriptions into databases will be important steps in comparative phenotypic and genotypic studies across species and gene-discovery experiments.

Web services have become a key technology for bioinformatics, since life science databases are globally decentralized and the exponential increase in the amount of available data demands for efficient systems without the need to transfer entire databases for every step of an analysis. However, various incompatibilities among database resources and analysis services make it difficult to connect and integrate these into interoperable workflows. To resolve this situation, we invited domain specialists from web service providers, client software developers, Open Bio* projects, the BioMoby project and researchers of emerging areas where a standard exchange data format is not well established, for an intensive collaboration entitled the BioHackathon 2008. The meeting was hosted by the Database Center for Life Science (DBCLS) and Computational Biology Research Center (CBRC) and was held in Tokyo from February 11th to 15th, 2008. In this report we highlight the work accomplished and the common issues arisen from this event, including the standardization of data exchange formats and services in the emerging fields of glycoinformatics, biological interaction networks, text mining, and phyloinformatics. In addition, common shared object development based on BioSQL, as well as technical challenges in large data management, asynchronous services, and security are discussed. Consequently, we improved interoperability of web services in several fields, however, further cooperation among major database centers and continued collaborative efforts between service providers and software developers are still necessary for an effective advance in bioinformatics web service technologies.

The Generation Challenge Programme (GCP – "http://www.generationcp.org":http://www.generationcp.org) is a globally distributed crop research consortium directed toward crop improvement through the application of comparative biology and genetic resources characterization to plant breeding. GCP adopted the development paradigm of a ‘model-driven architecture’ to achieve the interoperability and integration of diverse GCP data types that are available through distributed data sources and consumed by end-user data analysis tools. Its objective is to ensure semantic compatibility across the Consortium that will lead to the creation of robust global public goods from GCP research results. The GCP scientific domain model is an object model that encapsulates key crop science concepts and is documented using Unified Modeling Language (see GCP Models on "http://pantheon.generationcp.org/index.php":http://pantheon.generationcp.org/index.php). At the core of the GCP architecture is a scientific domain model, which is heavily parameterized with GCP-indexed ontology terms. The GCP-indexed ontology reuses established international standards where available, converts other publicly available controlled vocabularies into formally managed ontology, and develops novel ontology if no public vocabularies yet exist. General and crop-specific GCP ontologies are being developed by crop teams involving GCP and external scientific experts – in particular, for crop-specific ontology relating to plant anatomy, developmental stage, trait and phenotype for selected GCP crops. Crop ontologies are being developed for chickpea, maize, Musa, potato, rice, sorghum and wheat. The Bioversity crop descriptor lists already loaded into OBO format files provide the primary structure to develop the crop ontologies. Then, terms to be mapped to the ontologies are extracted from the crop databases where trait values have been stored by crop scientists. These sources allow the ontology teams to identify the most commonly used concept names and their interrelations. Experts validate the selection of keywords that will build the controlled vocabulary. These GCP ontologies will allow researchers and end users to query keywords related to traits, plant structure, growth stage, and molecular function, and link them to associated phenotyping and genotyping data sets including data on germplasm, crop physiology, geographic information, genes, QTL, etc. To reach that stage, the crop ontologies will be integrated into the data-entry user interface or data templates as picklists facilitating data annotation and submission of new terms. In addition, the GCP ontologies will be integrated with Plant Ontology (PO) and Gramene (Trait Ontology, TO; Environment Ontology, EO) to develop a common, internationally shared crop trait and anatomy ontology. The team will initiate collaboration with SONet (Scientific Observations Network) and OBOE (Extensible Observation Ontology), which proposed to integrate the GCP ontology as a study case.The Open Biomedical Ontologies (OBO) edit tool has been used to develop the ontologies for rice, wheat and maize traits, which are currently available at "http://cropforge.org/projects/gcpontology/":http://cropforge.org/projects/gcpontology/ . The crop-specific work plans and ontologies related to other materials are published at "http://pantheon.generationcp.org":http://pantheon.generationcp.org. The development and curation of general-purpose ontologies will be continued and made available on the Pantheon and CropForge websites.

National audience

The BioMoby project was initiated in 2001 from within the model organism database community. It aimed to standardize methodologies to facilitate information exchange and access to analytical resources, using a consensus driven approach. Six years later, the BioMoby development community is pleased to announce the release of the 1.0 version of the interoperability framework, registry Application Programming Interface and supporting Perl and Java code-bases. Together, these provide interoperable access to over 1400 bioinformatics resources worldwide through the BioMoby platform, and this number continues to grow. Here we highlight and discuss the features of BioMoby that make it distinct from other Semantic Web Service and interoperability initiatives, and that have been instrumental to its deployment and use by a wide community of bioinformatics service providers. The standard, client software, and supporting code libraries are all freely available at http://www.biomoby.org/.

The Generation Challenge Programme (GCP) is an international research consortium striving to apply molecular biological advances to crop improvement for developing countries. Central to its activities is the creation of a next generation global crop information platform and network to share genetic resources, genomics, and crop improvement information. This system is being designed based on a comprehensive scientific domain object model and associated shared ontology. This model covers germplasm, genotype, phenotype, functional genomics, and geographical information data types needed in GCP research. This paper provides an overview of this modeling effort. This paper is part of the special issue of OMICS on data standards.

Motivation:In silico experiments necessitate the virtual organization of people, data, tools and machines. The scientific process also necessitates an awareness of the experience base, both of personal data as well as the wider context of work. The management of all these data and the co-ordination of resources to manage such virtual organizations and the data surrounding them needs significant computational infra-structure support. Results: In this paper, we show that myGrid, middleware for the Semantic Grid, enables biologists to perform and manage in silico experiments, then explore and exploit the results of their experiments. We demonstrate myGrid in the context of a series of bioinformatics experiments focused on a 1.5 Mb region on chromosome 7 which is deleted in Williams--Beuren syndrome (WBS). Due to the highly repetitive nature of sequence flanking/in the WBS critical region (WBSCR), sequencing of the region is incomplete leaving documented gaps in the released sequence. myGrid was used in a series of experiments to find newly sequenced human genomic DNA clones that extended into these 'gap' regions in order to produce a complete and accurate map of the WBSCR. Once placed in this region, these DNA sequences were analysed with a battery of prediction tools in order to locate putative genes and regulatory elements possibly implicated in the disorder. Finally, any genes discovered were submitted to a range of standard bioinformatics tools for their characterization. We report how myGrid has been used to create workflows for these in silico experiments, run those workflows regularly and notify the biologist when new DNA and genes are discovered. The myGrid services collect and co-ordinate data inputs and outputs for the experiment, as well as much provenance information about the performance of experiments on WBS. Availability: The myGrid software is available via http://www.mygrid.org.uk

The Bioperl project is an international open-source collaboration of biologists, bioinformaticians, and computer scientists that has evolved over the past 7 yr into the most comprehensive library of Perl modules available for managing and manipulating life-science information. Bioperl provides an easy-to-use, stable, and consistent programming interface for bioinformatics application programmers. The Bioperl modules have been successfully and repeatedly used to reduce otherwise complex tasks to only a few lines of code. The Bioperl object model has been proven to be flexible enough to support enterprise-level applications such as EnsEMBL, while maintaining an easy learning curve for novice Perl programmers. Bioperl is capable of executing analyses and processing results from programs such as BLAST, ClustalW, or the EMBOSS suite. Interoperation with modules written in Python and Java is supported through the evolving BioCORBA bridge. Bioperl provides access to data stores such as GenBank and SwissProt via a flexible series of sequence input/output modules, and to the emerging common sequence data storage format of the Open Bioinformatics Database Access project. This study describes the overall architecture of the toolkit, the problem domains that it addresses, and gives specific examples of how the toolkit can be used to solve common life-sciences problems. We conclude with a discussion of how the open-source nature of the project has contributed to the development effort.[Supplemental material is available online at www.genome.org. Bioperl is available as open-source software free of charge and is licensed under the Perl Artistic License (http://www.perl.com/pub/a/language/misc/Artistic.html). It is available for download at http://www.bioperl.org. Support inquiries should be addressed to bioperl-l@bioperl.org.]

Silver-copper ionization was used for controlling Legionella distribution in a German university hospital hot water plumbing system for 4 years. In the beginning, silver concentrations were not allowed to exceed 10 microg/L because of drinking water regulation limits in Germany. Water samples were monitored for Legionella counts, temperature, and silver and copper concentrations. A significant (P

MOTIVATION: The user-friendly, graphical X-windows interface (WPI) to the GCG sequence analysis package can often not be used due to the lack of an X-server on PC or Macintosh computers. Because Web browsers like Netscape are much more common on those platforms, we decided to develop W2H, a WWW interface to the GCG Sequence Analysis Software Package with nearly the same functionality as the X-windows interface WPI. RESULTS: The new WWW interface (W2H) to the GCG Sequence Analysis Software Package (Wisconsin Package) supports modern Web technologies, like client-pull method, or embedded scripting language, and provides a reasonable platform independence. The interface is quite comprehensive with advanced features like sequence selector, search set builder, enzyme chooser, access to sequence databases, uploading client files to the GCG server or displaying and manipulating graphical outputs in addition to GCG analysis programs. W2H also manages secure access to both GCG server and user data. For special environments, like workshops, conferences and company intranets, there is a special mode (Intranet mode) with less security constraints. The behaviour of W2H is mostly controlled by meta-data files describing the applications and giving a base for dynamic creation of HTML documents. This paper presents mainly the development approaches used, and architectural design aspects of W2H. AVAILABILITY: W2H is available by ftp://ftp.ebi.ac. uk/pub/software/unix/w2h or ftp://genome.dkfz-heidelberg.de/pub/w2h CONTACT: m.senger@ebi.ac.uk

Management and analysis of nucleotide and protein sequence and structure data constitute a traditional area of bioinformatics. Since the analytical programs are frequently developed by researchers, rather than software engineers, they tend to suffer from idiosyncratic and non-ergonomic man-machine interfaces. We report on HUSAR, our 140+ collection of third-party, as well as in-house developed or adapted, sequence manipulation and analysis tools, well integrated into the UNIX operating system environment and accessible via consistent menu-aware interface. Most of the HUSAR programs can be completely specified by UNIX command-line options; they can thus be run in batches or combined into pipes. Adding such a program into the HUSAR environment is almost a ‘plug-and-play’ exercise. HUSAR has been recently complemented with a graphical client interface, X-HUSAR, to support users on UNIX platforms with X11 windowing systems. The whole X-HUSAR interface is based on a single generic program, COMLIGEN, and a number of specific configuration files. COMLIGEN interprets those files and renders appropriate windows, menus, and other interactive elements, which help the end user in selecting application programs and specifying their options. Efforts of extending both HUSAR and X-HUSAR are roughly linear to the size of the collection.

Meaningful exchange of microarray data is currently difficult because it is rare that published data provide sufficient information depth or are even in the same format from one publication to another. MAGE will help microarray data producers and users to exchange information by providing a common platform for data exchange, and MAGE-STK will make the adoption of MAGE easier., Background Meaningful exchange of microarray data is currently difficult because it is rare that published data provide sufficient information depth or are even in the same format from one publication to another. Only when data can be easily exchanged will the entire biological community be able to derive the full benefit from such microarray studies. Results To this end we have developed three key ingredients towards standardizing the storage and exchange of microarray data. First, we have created a minimal information for the annotation of a microarray experiment (MIAME)-compliant conceptualization of microarray experiments modeled using the unified modeling language (UML) named MAGE-OM (microarray gene expression object model). Second, we have translated MAGE-OM into an XML-based data format, MAGE-ML, to facilitate the exchange of data. Third, some of us are now using MAGE (or its progenitors) in data production settings. Finally, we have developed a freely available software tool kit (MAGE-STK) that eases the integration of MAGE-ML into end users' systems. Conclusions MAGE will help microarray data producers and users to exchange information by providing a common platform for data exchange, and MAGE-STK will make the adoption of MAGE easier.

My Grid is an e-Science Grid project that aims to help biologists and bioinformaticians to perform workflow-based in silico experiments, and help them to automate the management of such workflows through personalisation, notification of change and publication of experiments. In this paper, we describe the architecture of my Grid and how it will be used by the scientist. We then show how my Grid can benefit from agents technologies. We have identified three key uses of agent technologies in my Grid: user agents, able to customize and personalise data, agent communication languages offering a generic and portable communication medium, and negotiation allowing multiple distributed entities to reach service level agreements.

Background The interaction between biological researchers and the bioinformatics tools they use is still hampered by incomplete interoperability between such tools. To ensure interoperability initiatives are effectively deployed, end-user applications need to be aware of, and support, best practices and standards. Here, we report on an initiative in which software developers and genome biologists came together to explore and raise awareness of these issues: BioHackathon 2009. Results Developers in attendance came from diverse backgrounds, with experts in Web services, workflow tools, text mining and visualization. Genome biologists provided expertise and exemplar data from the domains of sequence and pathway analysis and glyco-informatics. One goal of the meeting was to evaluate the ability to address real world use cases in these domains using the tools that the developers represented. This resulted in i) a workflow to annotate 100,000 sequences from an invertebrate species; ii) an integrated system for analysis of the transcription factor binding sites (TFBSs) enriched based on differential gene expression data obtained from a microarray experiment; iii) a workflow to enumerate putative physical protein interactions among enzymes in a metabolic pathway using protein structure data; iv) a workflow to analyze glyco-gene-related diseases by searching for human homologs of glyco-genes in other species, such as fruit flies, and retrieving their phenotype-annotated SNPs. Conclusions Beyond deriving prototype solutions for each use-case, a second major purpose of the BioHackathon was to highlight areas of insufficiency. We discuss the issues raised by our exploration of the problem/solution space, concluding that there are still problems with the way Web services are modeled and annotated, including: i) the absence of several useful data or analysis functions in the Web service "space"; ii) the lack of documentation of methods; iii) lack of compliance with the SOAP/WSDL specification among and between various programming-language libraries; and iv) incompatibility between various bioinformatics data formats. Although it was still difficult to solve real world problems posed to the developers by the biological researchers in attendance because of these problems, we note the promise of addressing these issues within a semantic framework.