Conference proceeding
Incremental interactive mining of constrained association rules from biological annotation data with nominal features
Proceedings of the 2005 ACM symposium on applied computing, pp.123-127
SAC '05
03/13/2005
DOI: 10.1145/1066677.1066710
Abstract
Data arising from genomic and proteomic experiments is amassing at high speeds resulting in huge amounts of raw data; consequently, the need for analyzing such biological data --- the understanding of which is still lagging way behind --- has been prominently solicited in the post-genomic era we are currently witnessing. In this paper we attempt to analyze annotated genome data by applying a very central data-mining technique known as association rule mining with the aim of discovering rules capable of yielding deeper insights into this type of data. We propose a new technique capable of using domain knowledge in the form of queries in order to efficiently mine only the subset of the associations that are of interest to researcher in an incremental and interactive mode.
Details
- Title: Subtitle
- Incremental interactive mining of constrained association rules from biological annotation data with nominal features
- Creators
- Imad Rahal - North Dakota State UniversityDongmei Ren - North Dakota State UniversityAmal Perera - North Dakota State UniversityHassan Najadat - North Dakota State UniversityWilliam Perrizo - North Dakota State UniversityRiad Rahhal - University of IowaWilly Valdivia - Orion Integrated Biosciences, Fargo, ND
- Resource Type
- Conference proceeding
- Publication Details
- Proceedings of the 2005 ACM symposium on applied computing, pp.123-127
- Publisher
- ACM
- Series
- SAC '05
- DOI
- 10.1145/1066677.1066710
- Language
- English
- Date published
- 03/13/2005
- Academic Unit
- Stead Family Department of Pediatrics; Gastroenterology, Hepatology, Pancreatology, and Nutrition
- Record Identifier
- 9984354120002771
Metrics
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