Biomedical subjects

Peter Mork

Publications and source records attributed to Peter Mork.

4 recordsLinked to original sources

PubMed2006

Data integration and genomic medicine.

Genomic medicine aims to revolutionize health care by applying our growing understanding of the molecular basis of disease. Research in this arena is data intensive, which means data sets are large and highly heterogeneous. To create knowledge from data, researchers must integrate these large and diverse data sets. This presents daunting informatic challenges such as representation of data that is suitable for computational inference (knowledge representation), and linking heterogeneous data sets (data integration). Fortunately, many of these challenges can be classified as data integration problems, and technologies exist in the area of data integration that may be applied to these challenges. In this paper, we discuss the opportunities of genomic medicine as well as identify the informatics challenges in this domain. We also review concepts and methodologies in the field of data integration. These data integration concepts and methodologies are then aligned with informatics challenges in genomic medicine and presented as potential solutions. We conclude this paper with challenges still not addressed in genomic medicine and gaps that remain in data integration research to facilitate genomic medicine.

Biomedical Research↗

PubMed2004

Challenges in precisely aligning models of human anatomy using generic schema matching.

This paper describes how we used generic schema matching algorithms to align the Foundational Model of Anatomy (FMA) and the GALEN Common Reference Model (CRM), two large models of human anatomy. We summarize the generic schema matching algorithms we used to identify correspondences. We present sample results that highlight the similarities and differences between the FMA and the CRM. We also identify uses of aggregation, transitivity, and reification, for which generic schema matching fails to produce an accurate mapping and present manually constructed solutions for them.

Algorithms↗

PubMed2004

The BioMediator system as a data integration tool to answer diverse biologic queries.

We present the BioMediator (www.biomediator.org) system and the process of executing queries on it. The system was designed as a tool for posing queries across semantically and syntactically heterogeneous data particularly in the biological arena. We use examples from researchers at the University of Washington, and the University of Missouri-Columbia, to discuss the BioMediator system architecture, query execution, modifications to the system to support the queries, and summarize our findings and our future directions. Finally, we discuss the system's flexibility and generalized approach and give examples of how the system can be extended for a variety of objectives.

Computational Biology↗

PubMed2003

OQAFMA Querying agent for the Foundational Model of Anatomy: a prototype for providing flexible and efficient access to large semantic networks.

The development of large semantic networks, such as the UMLS, which are intended to support a variety of applications, requires a flexible and efficient query interface for the extraction of information. Using one of the source vocabularies of UMLS as a test bed, we have developed such a prototype query interface. We first identify common classes of queries needed by applications that access these semantic networks. Next, we survey StruQL, an existing query language that we adopted, which supports all of these classes of queries. We then describe the OQAFMA Querying Agent for the Foundational Model of Anatomy (OQAFMA), which provides an efficient implementation of a subset of StruQL by pre-computing a variety of indices. We describe how OQAFMA leverages database optimization by converting StruQL queries to SQL. We evaluate the flexibility and efficiency of our implementation using English queries written by anatomists. This evaluation verifies that OQAFMA provides flexible, efficient access to one such large semantic network, the Foundational Model of Anatomy, and suggests that OQAFMA could be an efficient query interface to other large biomedical knowledge bases, such as the Unified Medical Language System.

Abstracting and Indexing↗