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Aaron_Albin_MS_Thesis.pdf (1.93 MB)

ETD Abstract Container

Abstract Header

Building an online UMLS knowledge discovery platform using graph indexing

Albin, Aaron
http://rave.ohiolink.edu/etdc/view?acc_num=osu1398946883

Abstract Details

2014, Master of Science, Ohio State University, Computer Science and Engineering.
The UMLS is a rich collection of biomedical concepts which are connected by semantic relations. Using transitively associated information for knowledge discovery has been shown to be effective for many applications in the biomedical field. Although there are a few tools and methods available for extracting transitive knowledge from the UMLS, they usually have major restrictions on the length of transitive relations or on the number of data sources. To overcome these restrictions, the web platform onGrid was developed to support efficient path queries and knowledge discovery on the UMLS. This platform provides several features such as converting natural language queries into UMLS concepts, performing efficient queries, and visualizing the result paths. It also builds relationship and distance matrices for two sets of biomedical terms, making it possible to perform effective knowledge discovery on these concepts. onGrid can be applied to study biomedical concept relations between any two sets or within one set of biomedical concepts. In this work, onGrid is used to study the gene-gene relationships in HUGO as well as disease-disease relationships in OMIM. By cross validating the results with external datasets, it is demonstrated that onGrid is very efficient to be used for conceptual-based knowledge discovery on the UMLS. onGrid is a very efficient tool for querying the UMLS for transitive relations, studying relationships between biomedical terms, and generating hypotheses. The online UMLS knowledge discovery platform has been tested on the BMI Netlab server (URL: https://netlab.bmi.osumc.edu/ongrid).
Yang Xiang (Advisor)
Rajiv Ramnath (Committee Member)
45 p.
Computer Science
UMLS; graph indexing; knowledge discovery

Recommended Citations

Citations

  • Albin, A. (2014). Building an online UMLS knowledge discovery platform using graph indexing [Master's thesis, Ohio State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=osu1398946883

    APA Style (7th edition)

  • Albin, Aaron. Building an online UMLS knowledge discovery platform using graph indexing. 2014. Ohio State University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=osu1398946883.

    MLA Style (8th edition)

  • Albin, Aaron. "Building an online UMLS knowledge discovery platform using graph indexing." Master's thesis, Ohio State University, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=osu1398946883

    Chicago Manual of Style (17th edition)

osu1398946883
871
© 2014, some rights reserved.Creative Commons License Building an online UMLS knowledge discovery platform using graph indexing by Aaron Albin is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License. Based on a work at etd.ohiolink.edu.
This open access ETD is published by The Ohio State University and OhioLINK.