Large-scale regulatory network analysis from microarray data: modified Bayesian network learning and association rule mining

2007 ◽  
Vol 43 (4) ◽  
pp. 1207-1225 ◽  
Author(s):  
Zan Huang ◽  
Jiexun Li ◽  
Hua Su ◽  
George S. Watts ◽  
Hsinchun Chen
Keyword(s):  
Network Analysis ◽  
Bayesian Network ◽  
Microarray Data ◽  
Association Rule ◽  
Regulatory Network ◽  
Association Rule Mining ◽  
Large Scale ◽  
Rule Mining ◽  
Network Learning

A Fault Diagnosis Method Based on Constrained Frequent Pattern Trees

2010 ◽  
Vol 39 ◽  
pp. 449-454
Author(s):  
Jiang Hui Cai ◽  
Wen Jun Meng ◽  
Zhi Mei Chen
Keyword(s):  
Fault Diagnosis ◽  
Association Rule ◽  
Association Rule Mining ◽  
Large Scale ◽  
Predicate Logic ◽  
Frequent Pattern ◽  
Rule Mining ◽  
First Order ◽  
Broad Term ◽  
Diagnosis Method

Data mining is a broad term used to describe various methods for discovering patterns in data. A kind of pattern often considered is association rules, probabilistic rules stating that objects satisfying description A also satisfy description B with certain support and confidence. In this study, we first make use of the first-order predicate logic to represent knowledge derived from celestial spectra data. Next, we propose a concept of constrained frequent pattern trees (CFP) along with an algorithm used to construct CFPs, aiming to improve the efficiency and pertinence of association rule mining. The running results show that it is feasible and valuable to apply this method to mining the association rule and the improved algorithm can decrease related computation quantity in large scale and improve the efficiency of the algorithm. Finally, the simulation results of knowledge acquisition for fault diagnosis also show the validity of CFP algorithm.

scholarly journals Investigating Prescriptions and Mechanisms of Acupuncture for Chronic Stable Angina Pectoris: An Association Rule Mining and Network Analysis Study

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Jie Yu ◽  
Yongliang Jiang ◽  
Mingqi Tu ◽  
Binjun Liao ◽  
Jianqiao Fang
Keyword(s):  
Network Analysis ◽  
Angina Pectoris ◽  
Stable Angina ◽  
Association Rule ◽  
Association Rule Mining ◽  
Acupuncture Treatment ◽  
Chronic Stable Angina ◽  
Controlled Trials ◽  
Stable Angina Pectoris ◽  
Rule Mining

Chronic stable angina pectoris (CSAP) is a worldwide cardiovascular disease that severely affects people’s quality of life and causes serious cardiovascular accidents. Although acupuncture had been confirmed as a potential adjunctive treatment for CSAP, the basic rules and mechanisms of acupoints were little understood. We conducted a systematic search of the China Biology Medicine (CBM), VIP database, Wangfang database, China National Knowledge Infrastructure (CNKI), PubMed, Cochrane Library, Embase, and Web of Science to identify eligible clinical controlled trials (CCTs) and randomized controlled trials (RCTs), from their inception to 18th February 2020. The acupoint prescriptions in the treatment of CSAP were extracted and analyzed based on the association rule mining (ARM) and network analysis. In addition, potential mechanisms of acupuncture for treating CSAP were summarized by data mining. A total of 27 eligible trials were included. Analysis of acupoint prescriptions covered 36 conventional acupoints and 1 experience acupoint, distributing in 10 meridians. The top three frequently used acupoints were PC6, LU9, and ST36. The top three frequently used meridians were the pericardial meridian, lung meridian, and heart meridian. The most frequently used acupoint combinations were LU9 combined with PC6. Besides, network analysis indicated that the core acupoints included PC6, BL15, ST40, and RN17. Moreover, potential mechanisms of acupuncture for treating CSAP involved the regulation of autonomic nerve function, the content of matrix metalloproteinase-9 (MMP-9), volume and the equivalent block of coronary artery calcified plaque (CACP), endothelin (ET), and nitric oxide (NO), neutrophil-lymphocyte ratio (NLR), the content of C-reactive protein (CRP), and tumor necrosis factor-α (TNF-α). In conclusion, our findings concerning acupoint prescriptions and potential mechanisms in the acupuncture treatment of CSAP could provide an optimized acupuncture treatment plan for clinical treatment of CSAP and promote further mechanism research and network research of CSAP.

Research on Association Rule Mining Algorithm Based on Distributed Data

2014 ◽  
Vol 998-999 ◽  
pp. 899-902 ◽  
Author(s):  
Cheng Luo ◽  
Ying Chen
Keyword(s):  
Data Mining ◽  
Association Rule ◽  
Association Rule Mining ◽  
Large Scale ◽  
Frequent Itemsets ◽  
Network Communication ◽  
Data Mining Algorithm ◽  
Distributed Data ◽  
Rule Mining ◽  
Mining Algorithm

Existing data miming algorithms have mostly implemented data mining under centralized environment, but the large-scale database exists in the distributed form. According to the existing problem of the distributed data mining algorithm FDM and its improved algorithms, which exist the problem that the frequent itemsets are lost and network communication cost too much. This paper proposes a association rule mining algorithm based on distributed data (ARADD). The mapping marks the array mechanism is included in the ARADD algorithm, which can not only keep the integrity of the frequent itemsets, but also reduces the cost of network communication. The efficiency of algorithm is proved in the experiment.

An extended association rule mining strategy for gene relationship discovery from microarray data

2012 ◽  
Vol 84 (2) ◽  
pp. 384-396 ◽  
Author(s):  
Bin Peng ◽  
Dianwen Zhu ◽  
Xiaowei Yang ◽  
Ling Liu ◽  
Wenquan Huang ◽  
...  
Keyword(s):  
Microarray Data ◽  
Association Rule ◽  
Association Rule Mining ◽  
Rule Mining

scholarly journals Human Resource Allocation Based on Fuzzy Data Mining Algorithm

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
You Wu ◽  
Zheng Wang ◽  
Shengqi Wang
Keyword(s):  
Data Mining ◽  
Human Resource ◽  
Business Process ◽  
Association Rule ◽  
Association Rule Mining ◽  
Large Scale ◽  
Data Mining Algorithm ◽  
Rule Mining ◽  
Mining Algorithm ◽  
Database Technology

Data mining is currently a frontier research topic in the field of information and database technology. It is recognized as one of the most promising key technologies. Data mining involves multiple technologies, such as mathematical statistics, fuzzy theory, neural networks, and artificial intelligence, with relatively high technical content. The realization is also difficult. In this article, we have studied the basic concepts, processes, and algorithms of association rule mining technology. Aiming at large-scale database applications, in order to improve the efficiency of data mining, we proposed an incremental association rule mining algorithm based on clustering, that is, using fast clustering. First, the feasibility of realizing performance appraisal data mining is studied; then, the business process needed to realize the information system is analyzed, the business process-related links and the corresponding data input interface are designed, and then the data process to realize the data processing is designed, including data foundation and database model. Aiming at the high efficiency of large-scale database mining, database development tools are used to implement the specific system settings and program design of this algorithm. Incorporated into the human resource management system of colleges and universities, they carried out successful association broadcasting, realized visualization, and finally discovered valuable information.

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