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{bio,medical} informatics

Thursday, September 27, 2001

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find related articles. powered by google. GenomeWeb EBI's XEMBL Project Supports DoubleTwist's AGAVE Genomic Annotation Format

"DoubleTwist said Thursday that the European Bioinformatics Institute, an outstation of the European Molecular Biology Laboratory, now supports DoubleTwist's genomic annotation XML format, AGAVE."

"Researchers can use the data transformation tools to convert data from publicly available genomics databases such as GenBank, EMBL, and Swiss-Prot into AGAVE format. Converted data can then be used in viewers and programs that support the format."

find related articles. powered by google. XEMBL Project What is the XEMBL Project?

"XEMBL is all about bringing EMBL Nucleotide Sequence data to our users in a variety of formats. The publically available EMBL/GenBank/DDBJ data is kept at the EBI in an Oracle database, from which flatfiles are created at every release for the purpose of distribution. As you might be aware of, flat-files have severe limitations, and we have been asked various times if we are going to distribute the EMBL data in different formats as well, XML being the one most prominently mentioned. In short, the XEMBL project will bring to the user several alternative formats of EMBL data."

redux [07.10.01]
find related articles. powered by google. Individual.Com DoubleTwist Releases Genomic Annotation XML Format as Open Standard; New Web Site Launched to Provide Access to Data Format and Tools

"DoubleTwist, Inc. today announced that the genomic annotation XML format used to create its annotated human genome database is now freely available as an open standard to the life sciences community. AGAVE (Architecture for Genomic Annotation, Visualization and Exchange) allows users to manage, visualize and share annotations of genomic sequences using the document type definition (DTD) and associated tools available through"

"AGAVE was originally developed as part of DoubleTwist's bioinformatics architecture for high-throughput analysis of the human genome, which relies heavily on XML and Java technologies and tools. Central to AGAVE is a Java Object Model and a corresponding XML Document Type Definition (DTD) that facilitate data exchange, data integration and data transformation between components."

find related articles. powered by google. Agave.Org Introduction

"The design goals of AGAVE are to provide a comprehensive, extensible, open and readable markup language for genomic annotation. AGAVE is comprehensive because it can represent all the relevant biological data in public databases such as NCBI's GenBank, including the full sequence location format. It is extensible because it uses generic elements for computational results that can easily be used to capture results from new sequence annotation algorithms. Because AGAVE is XML-based, it is easy to use as an open standard for data storage and exchange. You can write programs to manipulate and extract genomic data using standard XML libraries, and you can easily transform data in the AGAVE format from and to other XML-based formats using tools such as XSLT (eXtensible Style Language Transformation). For example, you can easily transform data in GAME format to AGAVE format using XSLT templates. To aid readability, AGAVE focuses on biological data and uses standard biological terminology with a minimum of abbreviation."

redux [02.28.01]
find related articles. powered by google. PENN Database Research Group K2/Kleisli and GUS: Experiments in integrated access to genomic data sources

"The integration of heterogeneous data sources and software systems is a major issue in the biomedical community and several approaches have been explored: linking databases, "on-the-fly" integration through views, and integration through warehousing. In this paper we report on our experiences with two systems that were developed at the University of Pennsylvania: an integration system called K2, which has primarily been used to provide views over multiple external data sources and software systems; and a data warehouse called GUS which downloads, cleans, integrates and annotates data from multiple external data sources. Although the view and warehouse approaches each have their advantages, there is no clear "winner". Therefore, users must consider how the data is to be used, what the performance guarantees must be, and how much programmer time and expertise is available to choose the best strategy for a particular application. Our experiences also point to some practical tips on how updates should be published by the community, and how XML can be used to facilitate the processing of updates in a warehousing environment."

redux [03.22.01]
find related articles. powered by google. Peter Karp A Vision of DB Interoperation

"To realize the full potential of biological databases requires more than the interactive, hypertext flavor of database interoperation that is now so popular in the bioinformatics community. Interoperation based on declarative queries to multiple network-accessible databases will support analyses and investigations that are orders of magnitude faster and more powerful than what can be accomplished through interactive navigation. I present a vision of the capabilities that a query-based interoperation infrastructure should provide, and identify assumptions behind, and requirements of, this vision. I then propose an architecture for query-based interoperation that identifies a number of novel components of an information infrastructure for molecular biology. Those components include: A knowledge base that describes relationships among the conceptualizations used in different biological databases; a module that can determine what known DBs are relevant to a particular query; a module that can translate a query, or the results of a query, from one conceptualization to another; a family of DB drivers that provide uniform physical access to different DBMSs; a family of translators that can interconvert among different database schema languages; and a database that describes the network location and access methods for biological databases. A number of the components are translators because biological databases exhibit heterogeneity at several different levels, including the conceptual level, the data model, the query language, and data formats."

[ rhetoric ]

Bioinformatics will be at the core of biology in the 21st century. In fields ranging from structural biology to genomics to biomedical imaging, ready access to data and analytical tools are fundamentally changing the way investigators in the life sciences conduct research and approach problems. Complex, computationally intensive biological problems are now being addressed and promise to significantly advance our understanding of biology and medicine. No biological discipline will be unaffected by these technological breakthroughs.


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