Knowledge discovery and data mining in biological databases

Vladimir Brusic; John Zeleznikow

doi:10.1017/S0269888999003069

Knowledge discovery and data mining in biological databases

Vladimir Brusic, John Zeleznikow

Research output: Journal Publication › Article › peer-review

27 Citations (Scopus)

Abstract

The new technologies for Knowledge Discovery from Databases (KDD) and data mining promise to bring new insights into a voluminous growing amount of biological data. KDD technology is complementary to laboratory experimentation and helps speed up biological research. This article contains an introduction to KDD, a review of data mining tools, and their biological applications. We discuss the domain concepts related to biological data and databases, as well as current KDD and data mining developments in biology.

Original language	English
Pages (from-to)	257-277
Number of pages	21
Journal	Knowledge Engineering Review
Volume	14
Issue number	3
DOIs	https://doi.org/10.1017/S0269888999003069
Publication status	Published - Sept 1999
Externally published	Yes

ASJC Scopus subject areas

Software
Artificial Intelligence

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10.1017/S0269888999003069

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title = "Knowledge discovery and data mining in biological databases",

abstract = "The new technologies for Knowledge Discovery from Databases (KDD) and data mining promise to bring new insights into a voluminous growing amount of biological data. KDD technology is complementary to laboratory experimentation and helps speed up biological research. This article contains an introduction to KDD, a review of data mining tools, and their biological applications. We discuss the domain concepts related to biological data and databases, as well as current KDD and data mining developments in biology.",

author = "Vladimir Brusic and John Zeleznikow",

year = "1999",

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DO - 10.1017/S0269888999003069

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VL - 14

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JO - Knowledge Engineering Review

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Knowledge discovery and data mining in biological databases

Abstract

ASJC Scopus subject areas

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