CGPD: Cancer Genetics and Proteomics Database - A Dataset for Computational Analysis and Online Cancer Diagnostic Centre

Cancer Genetics and Proteomics Database (CGPD) is a repository for genetics and proteomics data of those Homo sapiens genes which are involved in Cancer. These genes are categorized in the database on the basis of cancer type. 72 genes of 13 types of cancers are considered in this database yet. Primers, promoters and peptides of these genes are also made available. Primers provided for each gene, with their features and conditions given to facilitate the researchers, are useful in PCR amplification, especially in cloning experiments. CGPD also contains Online Cancer Diagnostic Center (OCDC). It also contains transcription and translation tools to assist research work in progressive manner. The database is publicly available at http://www.cgpd.comyr.com

BioHackathon series in 2011 and 2012: penetration of ontology and linked data in life science domains

The application of semantic technologies to the integration of biological data and the interoperability of bioinformatics analysis and visualization tools has been the common theme of a series of annual BioHackathons hosted in Japan for the past five years. Here we provide a review of the activities and outcomes from the BioHackathons held in 2011 in Kyoto and 2012 in Toyama. In order to efficiently implement semantic technologies in the life sciences, participants formed various sub-groups and worked on the following topics: Resource Description Framework (RDF) models for specific domains, text mining of the literature, ontology development, essential metadata for biological databases, platforms to enable efficient Semantic Web technology development and interoperability, and the development of applications for Semantic Web data. In this review, we briefly introduce the themes covered by these sub-groups. The observations made, conclusions drawn, and software development projects that emerged from these activities are discussed

Service-Interoperabilität für naturwissenschaftliche Anwendungen : Identifikation und Anpassung von komponentenbasierten Service-Mediatoren

In der Softwareentwicklung wird die Serviceorientierung als neues Realisierungsparadigma propagiert. Sie erlaubt lose gekoppelte Services bedarfsbezogen in Workflows zu aggregieren. Hierbei ist die Überbrückung der Heterogenität dieser Services ein anerkanntes Problem von hohem wirtschaftlichem Interesse. Es besteht der Bedarf die Service-Interoperabilität weitestgehend automatisch herzustellen. In dieser Arbeit wurde ein Konzept für Service-Mediatoren entwickelt, die über eine offene und erweiterbare, software-unterstützte Prozedur (semi-)automatisch identifiziert und problembezogen in einen Workflow eingebettet werden können. Service-Mediatoren über\-brücken die Heterogenität der einzelnen Services und erzielen so die geforderte Service-Interoperabilität. Die offene Architektur und Entwicklung dieser Prozedur erlaubt erstmals die Vorteile gängiger Ansätze zu integrieren. Um einmal entwickelte Service-Mediatoren in verschiedenen Workflows einsetzen und wiederverwenden zu können, bedarf es ihrer gezielten Identifikation und Anpassung. Leider stellt gerade die Suche nach benötigten Service-Mediatoren ein besonders schwieriges Problem da. Dies gilt insbesondere, wenn erst mehrere geeignet verknüpfte Service-Mediatoren zusammen die Service-Interoperabilität erreichen und bereits bei der Suche diese Kombination identifiziert werden muss. Die Aspekte der Suche und der Anpassung erfordern eine Beschreibungssprache, die die Fähig\-keiten eines Service-Mediators sowohl syntaktisch als auch semantisch beschreiben kann. Mit der Mediator Profile Language (MPL) wurde eine derartige, auf OWL basierende Beschreibungssprache entwickelt, die die Grundlage des entworfenen Komponentenmodells der Service-Mediatoren bildet. Sie erlaubt u. a. die Beschreibung der Komposition mehrerer Service-Mediatoren, sowie deren Konfiguration über zustandsbehaftete Eigenschaftsfelder. Die semantische Annotation eines Service-Mediators geschieht hierbei über Konzepte einer Domänenontologie. Im Rahmen dieser Arbeit wurden Matchmaking-Algorithmen zur Suche entwickelt, die eine Identifikation adäquater Service-Mediatoren und deren Komposition erlauben. Durch den Einsatz von Ontologien zur semantischen Annotation der Service-Mediatoren kann die Suche auch über rein syntaktische Merkmale hinaus durchgeführt werden. Trotz der den Servicebeschreibungen innewohnenden Unschärfe wurde ein Verfahren realisiert, welches die Servicebeschreibungen auf MPL abbildet und dabei eine automatische Annotation durch die Konzepte einer Ontologie vornimmt. Die Matchmaking-Algorithmen wurden auch auf das Problem der semantischen Suche nach Service-Operationen übertragen. Die entwickelten ontologiebasierten Matchmaking-Verfahren liefern im Vergleich zu Standard-IR-Techniken signifikant bessere Ergebnisse, wie durch entsprechende Benchmarks mit anschließender Messung von Precision und Recall gezeigt werden konnte.Service Interoperability for Science Applications - Identification and Adaptation of Component-Based Service MediatorsService-orientation is a new software paradigm for building distributed, component-based software. It allows the aggregation of loosely coupled services into value-added workflows. In this context the gap between heterogeneous services is an accepted problem with particular commercial interest. Thus, there is the need to create service interoperability semi-automatically. In this thesis the concept of service mediators is developed. Through a software-aided procedure service mediators are identified, adapted and integrated into workflows in order to bridge the heterogeneity of different services. Service mediators are software components realizing for instance transformation facilities. The open architecture of the developed procedure allows the integration of benefits from current approaches. The discovery of relevant service mediators is a difficult problem, especially if several service mediators have to be combined adequately to reach the desired service interoperability. One major challenge is that such compositions have to be identified during discovery. The discovery and adaptation phases of the software-aided procedure require a suitable description of the capabilities of service mediators. Such a description should contain both syntactical and semantical information. The OWL-based Mediator Profile Language (MPL) addresses these issues. MPL permits among other things the description of compositions of service mediators as well as their customization by stateful properties. Semantical information is assigned by concepts of a domain ontology. In this dissertation different matchmaking algorithms were developed supporting the user in identifying relevant service mediators as well as new compositions of service mediators. Requirements for service mediators are derived from service descriptions and represented by query profiles in MPL. Even though the service descriptions are fuzzy the query generation algorithm automatically creates semantical annotations by mapping syntactical information to concepts of the domain ontology. These annotations are also stored within the query profile. Due to the application of the domain ontology the discovery process enables not only syntactical matchmaking but also semantical matchmaking. Furthermore, the matchmaking algorithms were transferred to the problem of discovering service operations. By measuring precision and recall it could be shown that ontology-based matchmaking is advantageously over standard information retrieval techniques

The iPlant Collaborative: Cyberinfrastructure for Plant Biology

The iPlant Collaborative (iPlant) is a United States National Science Foundation (NSF) funded project that aims to create an innovative, comprehensive, and foundational cyberinfrastructure in support of plant biology research (PSCIC, 2006). iPlant is developing cyberinfrastructure that uniquely enables scientists throughout the diverse fields that comprise plant biology to address Grand Challenges in new ways, to stimulate and facilitate cross-disciplinary research, to promote biology and computer science research interactions, and to train the next generation of scientists on the use of cyberinfrastructure in research and education. Meeting humanity's projected demands for agricultural and forest products and the expectation that natural ecosystems be managed sustainably will require synergies from the application of information technologies. The iPlant cyberinfrastructure design is based on an unprecedented period of research community input, and leverages developments in high-performance computing, data storage, and cyberinfrastructure for the physical sciences. iPlant is an open-source project with application programming interfaces that allow the community to extend the infrastructure to meet its needs. iPlant is sponsoring community-driven workshops addressing specific scientific questions via analysis tool integration and hypothesis testing. These workshops teach researchers how to add bioinformatics tools and/or datasets into the iPlant cyberinfrastructure enabling plant scientists to perform complex analyses on large datasets without the need to master the command-line or high-performance computational services

The iPlant Collaborative: Cyberinfrastructure for Plant Biology

The iPlant Collaborative (iPlant) is a United States National Science Foundation (NSF) funded project that aims to create an innovative, comprehensive, and foundational cyberinfrastructure in support of plant biology research (PSCIC, 2006). iPlant is developing cyberinfrastructure that uniquely enables scientists throughout the diverse fields that comprise plant biology to address Grand Challenges in new ways, to stimulate and facilitate cross-disciplinary research, to promote biology and computer science research interactions, and to train the next generation of scientists on the use of cyberinfrastructure in research and education. Meeting humanity's projected demands for agricultural and forest products and the expectation that natural ecosystems be managed sustainably will require synergies from the application of information technologies. The iPlant cyberinfrastructure design is based on an unprecedented period of research community input, and leverages developments in high-performance computing, data storage, and cyberinfrastructure for the physical sciences. iPlant is an open-source project with application programming interfaces that allow the community to extend the infrastructure to meet its needs. iPlant is sponsoring community-driven workshops addressing specific scientific questions via analysis tool integration and hypothesis testing. These workshops teach researchers how to add bioinformatics tools and/or datasets into the iPlant cyberinfrastructure enabling plant scientists to perform complex analyses on large datasets without the need to master the command-line or high-performance computational services

Computational and comparative investigations of syntrophic acetate-oxidising bacteria (SAOB)

Today's main energy sources are the fossil fuels petroleum, coal and natural gas, which are depleting rapidly and are major contributors to global warming. Methane is produced during anaerobic biodegradation of wastes and residues and can serve as an alternative energy source with reduced greenhouse gas emissions. In the anaerobic biodegradation process acetate is a major precursor and degradation can occur through two different pathways: aceticlastic methanogenesis and syntrophic acetate oxidation combined with hydrogenotrophic methanogenesis. Bioinformatics is critical for modern biological research, because different bioinformatics approaches, such as genome sequencing, de novo assembly sequencing and transcriptomics sequencing are providing a distinctly better understanding at the genomic level by predicting genes and pathways and by deciphering the relationships between genotype and phenotype. This thesis describes the genomic analysis of three syntrophic acetate-oxidising bacteria (SAOB), namely Tepidanaerobacter acetatoxydans, Clostridium ultunense and Syntrophaceticus schinkii. These isolates have the ability to perform syntrophic acetate oxidation in the presence of a partner methanogen, which ultimately produces methane in the final step of anaerobic digestion. The genomes were assembled using NGS data and the genomic behaviour was determined through genome annotation. Metabolic pathway analysis revealed the physiological attributes of the SAOB regarding substrate utilisation, intermediate metabolism, energy conservation and genes of the Wood- Ljungdahl pathway, which are known to be involved in acetate oxidation. The results showed that the three SAOB use contrasting strategies for syntrophic acetate oxidation (SAO): T. acetatoxydans possesses all genes involved in the W-L pathway except formate dehydrogenase and thus requires a syntrophic formate-utilising methanogenic partner; S. schinkii possesses the complete set of genes required for the W-L pathway to oxidise acetate in the presence of a hydrogen-utilising methanogenic partner; and C. ultunense uses different ways to oxidise acetate because it does not contain the complete set of W-L pathway genes. Moreover, the three SAOB differ from each other as regards organisation of the W-L pathway genes operon

植物の完全長cDNA収集およびDNA多型探索によるゲノム研究

学位の種別:論文博士University of Tokyo(東京大学