Earticle

초록

영어

The electromagnetic anomaly observations before earthquake, have been confirmed by many cases of strong earthquakes. The analysis of earthquake magnetic anomaly is an effective approach for seismo-precursor detection. Traditional frequent mining methods for electromagnetic matrix datasets analysis often find the co-related items. However, these methods may miss the items which are differential co-related patters under different datasets. Mining these differential co-related patterns is more valuable for inferring potential knowledge. In this paper, we develop an algorithm, MSPattern, to mine maximal subspace differential co-expression patterns. MSPattern constructs a weighted undirected item-item relational graph firstly. Then all the maximal co-related patterns would be mined using item-growth method in above graph. MSPattern also utilizes several techniques for producing maximal patterns without candidate patterns maintenance. Evaluated by real electromagnetic matrix datasets and the gene expression datasets, the experimental results show our algorithm can find some potential knowledge for earthquake analysis, and MSPattern algorithm is more efficient than traditional ones. The performance of MSPattern is also evaluated by empirical p-value and gene ontology, the results show our algorithm can find statistical significant and biological differential co-expression patterns.

목차

Abstract
 1. Introduction
 2. Problem Definition
 3. Mining Maximal SDC Patterns
  3.1 Construct the Weighted Undirected Gene-gene Relational Graph
  3.2 Mining maximal SDC Patterns in Two Microarray Datasets
 4. Experimental Results
  4.1 The Performance of MSPattern Algorithm in the Observed Electromagnetic Anomaly Datasets
  4.2 Evaluating of MSPattern Algorithm in Microarray Datasets
 5. Conclusion
 References

키워드

저자

• Miao Wang [ Science and Technology on Avionics Integration Laboratory, Shanghai, China, 200233, China National Aeronautical Radio Electronics Research Institute, Shanghai, China, 200233 ]
• Zhiyong Xiong [ Science and Technology on Avionics Integration Laboratory, Shanghai, China, 200233, China National Aeronautical Radio Electronics Research Institute, Shanghai, China, 200233 ]
• Liang Xu [ China National Aeronautical Radio Electronics Research Institute, Shanghai, China, 200233 ]
• Lihua Zhang [ Science and Technology on Avionics Integration Laboratory, Shanghai, China, 200233, China National Aeronautical Radio Electronics Research Institute, Shanghai, China, 200233 ]
• Cheng Gong [ Science and Technology on Avionics Integration Laboratory, Shanghai, China, 200233, China National Aeronautical Radio Electronics Research Institute, Shanghai, China, 200233 ]
• Yi Hu [ School of Software, Northwestern Polytechnical University, Xi’an, China, 710072 ]
• Yi Lin [ School of Software, Northwestern Polytechnical University, Xi’an, China, 710072 ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Database Theory and Application

• 간기

  격월간

• pISSN

  2005-4270

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605