Analysis and representation of biomedical data with concept lattice

Huaiguo Fu, Brendan Jennings, Paul Malone

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

7 Citations (Scopus)

Abstract

As the progress in biology and medical science, especially in DNA technology, large amounts of biomedical data continue to grow inexorably in size, dimension and complexity. We need to develop more scalable and more efficient techniques and methods to analyze and represent the large and high-dimensional biomedical data sets. Formal Concept Analysis (FCA) is an effective tool for data analysis and knowledge discovery. Concept lattice, which is derived from mathematical order theory and lattice theory, is the core of FCA. Many research works of various areas show that concept lattice structure is an effective platform for data mining, machine learning, information retrieval, software engineering, etc. This paper presents FCA for analysis and representation of biomedical data. Furthermore, we present a new lattice-based algorithm for analysis of large and high-dimensional biomedical data.

Original languageEnglish
Title of host publicationProceedings of the 2007 Inaugural IEEE-IES Digital EcoSystems and Technologies Conference, DEST 2007
Pages577-580
Number of pages4
DOIs
Publication statusPublished - 2007
Event2007 Inaugural IEEE-IES Digital EcoSystems and Technologies Conference, DEST 2007 - Cairns, Australia
Duration: 21 Feb 200723 Feb 2007

Publication series

NameProceedings of the 2007 Inaugural IEEE-IES Digital EcoSystems and Technologies Conference, DEST 2007

Conference

Conference2007 Inaugural IEEE-IES Digital EcoSystems and Technologies Conference, DEST 2007
Country/TerritoryAustralia
CityCairns
Period21/02/200723/02/2007

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