Background: Currently, a lack of consensus exists on how best to perform and interpret quantitative real-time PCR (qPCR) experiments. The problem is exacerbated by a lack of sufficient experimental detail in many publications, which impedes a reader’s ability to evaluate critically the quality of the results presented or to repeat the experiments.

Content: The Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE) guidelines target the reliability of results to help ensure the integrity of the scientific literature, promote consistency between laboratories, and increase experimental transparency. MIQE is a set of guidelines that describe the minimum information necessary for evaluating qPCR experiments. Included is a checklist to accompany the initial submission of a manuscript to the publisher. By providing all relevant experimental conditions and assay characteristics, reviewers can assess the validity of the protocols used. Full disclosure of all reagents, sequences, and analysis methods is necessary to enable other investigators to reproduce results. MIQE details should be published either in abbreviated form or as an online supplement.

Summary: Following these guidelines will encourage better experimental practice, allowing more reliable and unequivocal interpretation of qPCR results.

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The MIQE Guidelines: Minimum Information for Publication of Quantitative Real-Time PCR Experiments

物件導向軟體之架構(Object-Oriented Software Construction)探討

Many practical computing problems concern large graphs. Standard examples include the Web graph and various social networks. The scale of these graphs - in some cases billions of vertices, trillions of edges - poses challenges to their efficient processing. In this paper we present a computational model suitable for this task. Programs are expressed as a sequence of iterations, in each of which a vertex can receive messages sent in the previous iteration, send messages to other vertices, and modify its own state and that of its outgoing edges or mutate graph topology. This vertex-centric approach is flexible enough to express a broad set of algorithms. The model has been designed for efficient, scalable and fault-tolerant implementation on clusters of thousands of commodity computers, and its implied synchronicity makes reasoning about programs easier. Distribution-related details are hidden behind an abstract API. The result is a framework for processing large graphs that is expressive and easy to program.

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Pregel: a system for large-scale graph processing

The Unified Medical Language System (http:// umlsks.nlm.nih.gov) is a repository of biomedical vocabularies developed by the US National Library of Medicine. The UMLS integrates over 2 million names for some 900 000 concepts from more than 60 families of biomedical vocabularies, as well as 12 million relations among these concepts. Vocabularies integrated in the UMLS Metathesaurus include the NCBI taxonomy, Gene Ontology, the Medical Subject Headings (MeSH), OMIM and the Digital Anatomist Symbolic Knowledge Base. UMLS concepts are not only inter-related, but may also be linked to external resources such as GenBank. In addition to data, the UMLS includes tools for customizing the Metathesaurus (MetamorphoSys), for generating lexical variants of concept names (lvg) and for extracting UMLS concepts from text (MetaMap). The UMLS knowledge sources are updated quarterly. All vocabularies are available at no fee for research purposes within an institution, but UMLS users are required to sign a license agreement. The UMLS knowledge sources are distributed on CD-ROM and by FTP.

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The Unified Medical Language System (UMLS): integrating biomedical terminology

KEGG(Kyoto Encyclopedia of Genes and Genomes)〔和文〕 (特集 ゲノム医学の現在と未来--基礎と臨床) -- (データベース)

Accurate gathering of requirements is a major concern during conceptual modelling. Such accurateness can only be achieved through major involvement of users, who should check whether the system's specification conforms with their expectations. This task can be facilitated both by intuitive conceptual constructs and by executable models that allow interaction with the user to explain the behaviour of the system in accordance with its specification. This work proposes the notions of stimuli and business policies as intuitive behavioural constructs, and the use of the event calculus as an appropriate formalism for building executable specifications for behavioural models. The approach is borne out by an early implementation that allows the user to question why and how a given state is reached, where the answer is given in terms of the specifications, i.e. stimuli and policies, being applied.

Stimuli and business policies as modelling constructs: Their definition and validation through the event calculus

In data intensive applications, both programming and declarative query languages have attractions, the former in comprehensiveness and the latter for ease of use. Databases sometimes support the calling of side-effect free user defined functions from within declarative queries. As well as enabling more efficient coding of computationally intensive functions, this provision not only moves computation to data in a client-server setting, but also enables speedup through data parallel execution if the server is parallel. There has been little work on the combined use of query and program based database access in the context of parallel servers. We believe Polar is the first parallel object-oriented database which supports this arbitrary navigation both in a client application and in functions (operations) which may be called from within declarative queries. This work introduces Polar's support for navigation and for calling operations from within parallel queries and presents performance results for example navigational requests for the large OO7 benchmark.

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Speeding Up Navigational Requests in a Parallel Object Database System

Search Computing has been proposed to support the integration of the results of search engines with other data and computational resources. A key feature of the resulting integration platform is direct support for multi-domain ordered data, reflecting the fact that search engines produce ranked outputs, which should be taken into account when the results of several requests are combined. In the life sciences, there are many different types of ranked data. For example, ranked data may represent many different phenomena, including physical ordering within a genome, algorithmically assigned scores that represent levels of sequence similarity, and experimentally measured values such as expression levels. This chapter explores the extent to which the search computing functionalities designed for use with search engine results may be applicable for different forms of ranked data that are encountered when carrying out data integration in the life sciences. This is done by classifying different types of ranked data in the life sciences, providing examples of different types of ranking and ranking integration needs in the life sciences, identifying issues in the integration of such ranked data, and discussing techniques for drawing conclusions from diverse rankings.

Search Computing and the Life Sciences

Data Integration in the Life Sciences

The Grid is rising to prominence both as a vision and as an infrastructure. The vision is of dynamically formed virtual organisations that collaborate to address shared goals. The infrastructure, although still a work in progress, is a middleware that facilitates the sharing of networked resources on a global scale. Databases are important resources that are central to many organisations, and as such must be able to be accessed, integrated and managed in a Grid environment. How should this be done? What problems must be overcome when working in a Grid environment? What new expectations, opportunities and patterns of use come to the fore? This presentation both discusses core grid data access services and the wider implications and opportunities of Grids for database technologies.

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Norman W. Paton

Papers

Stimuli and business policies as modelling constructs: Their definition and validation through the event calculus

Speeding Up Navigational Requests in a Parallel Object Database System

Search Computing and the Life Sciences

Data Integration in the Life Sciences

Databases and the Grid: JDBC in WSDL, or Something Altogether Different?