Integration of large datasets for plant model organisms

This dissertation is concerned with bioinformatics data integration. The first chapter illustrates the current state of biological pathway databases in general, and in particular, plant pathway databases. Key studies are cited to illustrate the potential benefits that may come from further research into integration methods. Different models are explored to interface with the various stakeholders of biological data repositories. A public website (http://www.metnetonline.org) was built to address the role of a bioinformatics data warehouse as a server for external third parties. A dedicated API (MetNetAPI: http://www.metnetonline.org/api) accommodates bioinformaticians (and software developers in general) who wish to build advanced applications on top of MetNet. The API (implemented as .NET and Java libraries) was designed to be as user-friendly to programmers, as the public website is to end-users. Finally, a hybrid model is examined: the use of XML as a repository for information integration, downstream processing, and data manipulation. An overview of the use of XML in biological applications is included. MetNetAPI functions according to certain principles; a subset of the API is abstracted and implemented to interface with a range of other public databases. This results in a new bioinformatics toolkit that can be used to mix and match data from heterogeneous sources in a transparent manner. An example would be the grafting of protein-protein interaction data on top of araCyc pathways. Biological network data is often distributed over a variety of independently modeled databases. This dissertation makes two contributions to the field of bioinformatics: A new service - MetNet Online - is now operating which offers access to the earlier created and integrated MetNetDB data repository. The service is geared toward end-users, students and researchers alike, as well as seasoned bioinformatics software developers who wish to build their own applications on top of an already integrated datasource. Furthermore, integrated databases are only useful when they can be synchronized with their respective external sources. Thus, a framework was created that allows for a systematic approach to such integration efforts. In closing, this work provides a roadmap to maintain current as well as prepare for future integrated biological database projects

MetNet Online: a novel integrated resource for plant systems biology

BACKGROUND: Plants are important as foods, pharmaceuticals, biorenewable chemicals, fuel resources, bioremediation tools and general tools for recombinant technology. The study of plant biological pathways is advanced by easy access to integrated data sources. Today, various plant data sources are scattered throughout the web, making it increasingly complicated to build comprehensive datasets. RESULTS: MetNet Online is a web-based portal that provides access to a regulatory and metabolic plant pathway database. The database and portal integrate Arabidopsis, soybean (Glycine max) and grapevine (Vitis vinifera) data. Pathways are enriched with known or predicted information on sub cellular location. MetNet Online enables pathways, interactions and entities to be browsed or searched by multiple categories such as sub cellular compartment, pathway ontology, and GO term. In addition to this, the “My MetNet” feature allows registered users to bookmark content and track, import and export customized lists of entities. Users can also construct custom networks using existing pathways and/or interactions as building blocks. CONCLUSION: The site can be reached at http://www.metnetonline.org. Extensive video tutorials on how to use the site are available through http://www.metnetonline.org/tutorial/

MetNetAPI: A flexible method to access and manipulate biological network data from MetNet

<p>Abstract</p> <p>Background</p> <p>Convenient programmatic access to different biological databases allows automated integration of scientific knowledge. Many databases support a function to download files or data snapshots, or a webservice that offers "live" data. However, the functionality that a database offers cannot be represented in a static data download file, and webservices may consume considerable computational resources from the host server.</p> <p>Results</p> <p>MetNetAPI is a versatile Application Programming Interface (API) to the MetNetDB database. It abstracts, captures and retains operations away from a biological network repository and website. A range of database functions, previously only available online, can be immediately (and independently from the website) applied to a dataset of interest. Data is available in four layers: molecular entities, localized entities (linked to a specific organelle), interactions, and pathways. Navigation between these layers is intuitive (e.g. one can request the molecular entities in a pathway, as well as request in what pathways a specific entity participates). Data retrieval can be customized: Network objects allow the construction of new and integration of existing pathways and interactions, which can be uploaded back to our server. In contrast to webservices, the computational demand on the host server is limited to processing data-related queries only.</p> <p>Conclusions</p> <p>An API provides several advantages to a systems biology software platform. MetNetAPI illustrates an interface with a central repository of data that represents the complex interrelationships of a metabolic and regulatory network. As an alternative to data-dumps and webservices, it allows access to a current and "live" database and exposes analytical functions to application developers. Yet it only requires limited resources on the server-side (thin server/fat client setup). The API is available for Java, Microsoft.NET and R programming environments and offers flexible query and broad data- retrieval methods. Data retrieval can be customized to client needs and the API offers a framework to construct and manipulate user-defined networks. The design principles can be used as a template to build programmable interfaces for other biological databases. The API software and tutorials are available at <url>http://www.metnetonline.org/api</url>.</p

International consensus guidelines for scoring the histopathological growth patterns of liver metastasis

BACKGROUND: Liver metastases present with distinct histopathological growth patterns (HGPs), including the desmoplastic, pushing and replacement HGPs and two rarer HGPs. The HGPs are defined owing to the distinct interface between the cancer cells and the adjacent normal liver parenchyma that is present in each pattern and can be scored from standard haematoxylin-and-eosin-stained (H&E) tissue sections. The current study provides consensus guidelines for scoring these HGPs. METHODS: Guidelines for defining the HGPs were established by a large international team. To assess the validity of these guidelines, 12 independent observers scored a set of 159 liver metastases and interobserver variability was measured. In an independent cohort of 374 patients with colorectal liver metastases (CRCLM), the impact of HGPs on overall survival after hepatectomy was determined. RESULTS: Good-to-excellent correlations (intraclass correlation coefficient >0.5) with the gold standard were obtained for the assessment of the replacement HGP and desmoplastic HGP. Overall survival was significantly superior in the desmoplastic HGP subgroup compared with the replacement or pushing HGP subgroup (P=0.006). CONCLUSIONS: The current guidelines allow for reproducible determination of liver metastasis HGPs. As HGPs impact overall survival after surgery for CRCLM, they may serve as a novel biomarker for individualised therapies

Integration of large datasets for plant model organisms

This dissertation is concerned with bioinformatics data integration. The first chapter illustrates the current state of biological pathway databases in general, and in particular, plant pathway databases. Key studies are cited to illustrate the potential benefits that may come from further research into integration methods. Different models are explored to interface with the various stakeholders of biological data repositories. A public website (http://www.metnetonline.org) was built to address the role of a bioinformatics data warehouse as a server for external third parties. A dedicated API (MetNetAPI: http://www.metnetonline.org/api) accommodates bioinformaticians (and software developers in general) who wish to build advanced applications on top of MetNet. The API (implemented as .NET and Java libraries) was designed to be as user-friendly to programmers, as the public website is to end-users. Finally, a hybrid model is examined: the use of XML as a repository for information integration, downstream processing, and data manipulation. An overview of the use of XML in biological applications is included. MetNetAPI functions according to certain principles; a subset of the API is abstracted and implemented to interface with a range of other public databases. This results in a new bioinformatics toolkit that can be used to mix and match data from heterogeneous sources in a transparent manner. An example would be the grafting of protein-protein interaction data on top of araCyc pathways. Biological network data is often distributed over a variety of independently modeled databases. This dissertation makes two contributions to the field of bioinformatics: A new service - MetNet Online - is now operating which offers access to the earlier created and integrated MetNetDB data repository. The service is geared toward end-users, students and researchers alike, as well as seasoned bioinformatics software developers who wish to build their own applications on top of an already integrated datasource. Furthermore, integrated databases are only useful when they can be synchronized with their respective external sources. Thus, a framework was created that allows for a systematic approach to such integration efforts. In closing, this work provides a roadmap to maintain current as well as prepare for future integrated biological database projects.</p

Evolution and applications of plant pathway resources and databases

Plants are important sources of food and plant products are essential for modern human life. Plants are increasingly gaining importance as drug and fuel resources, bioremediation tools and as tools for recombinant technology. Considering these applications, database infrastructure for plant model systems deserves much more attention. Study of plant biological pathways, the interconnection between these pathways and plant systems biology on the whole has in general lagged behind human systems biology. In this article we review plant pathway databases and the resources that are currently available. We lay out trends and challenges in the ongoing efforts to integrate plant pathway databases and the applications of database integration. We also discuss how progress in non-plant communities can serve as an example for the improvement of the plant pathway database landscape and thereby allow quantitative modeling of plant biosystems.We propose Good Database Practice as a possible model for collab-oration and to ease future integration efforts

MetNetAPI: A flexible method to access and manipulate biological network data from MetNet

BackgroundConvenient programmatic access to different biological databases allows automated integration of scientific knowledge. Many databases support a function to download files or data snapshots, or a webservice that offers "live" data. However, the functionality that a database offers cannot be represented in a static data download file, and webservices may consume considerable computational resources from the host server. ResultsMetNetAPI is a versatile Application Programming Interface (API) to the MetNetDB database. It abstracts, captures and retains operations away from a biological network repository and website. A range of database functions, previously only available online, can be immediately (and independently from the website) applied to a dataset of interest. Data is available in four layers: molecular entities, localized entities (linked to a specific organelle), interactions, and pathways. Navigation between these layers is intuitive (e.g. one can request the molecular entities in a pathway, as well as request in what pathways a specific entity participates). Data retrieval can be customized: Network objects allow the construction of new and integration of existing pathways and interactions, which can be uploaded back to our server. In contrast to webservices, the computational demand on the host server is limited to processing data-related queries only. ConclusionsAn API provides several advantages to a systems biology software platform. MetNetAPI illustrates an interface with a central repository of data that represents the complex interrelationships of a metabolic and regulatory network. As an alternative to data-dumps and webservices, it allows access to a current and "live" database and exposes analytical functions to application developers. Yet it only requires limited resources on the server-side (thin server/fat client setup). The API is available for Java, Microsoft.NET and R programming environments and offers flexible query and broad data- retrieval methods. Data retrieval can be customized to client needs and the API offers a framework to construct and manipulate user-defined networks. The design principles can be used as a template to build programmable interfaces for other biological databases. The API software and tutorials are available at http://www.metnetonline.org/api.This article is from BMC Research Notes 3 (2010): 312, doi:10.1186/1756-0500-3-312. Posted with permission.</p