Mining gene expression databases for association rules
By Chad Creighton, S. Hanash. Bioinform., 2003
454 citations recorded by the source corpus.
Subfields: Information Systems, Molecular Biology
View Paper: https://www.semanticscholar.org/paper/9bcbf19d6ed95947279d5c1e4eb8b8b8d5631da1
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Information Systems
- Philip S. Yu
- Vincent Shin-Mu Tseng
- Christian Borgelt
- Bai-En Shie
- Cheng-Wei Wu
- Cynthia Rudin
- Till Quack
- Jun-Feng Qu
In Molecular Biology
Citations in the corpus
- Efficient Algorithms for Mining High Utility Itemsets from Transactional Databases (2013, background): “Among them, frequent pattern mining is a fundamental research topic that has been applied to different kinds of databases, such as transactional databases [1], [14], [21], streaming databases [18], [27], and time series databases [9], [12], and various application domains, such as bioinformatics [8]”
- Frequent item set mining (2012, methodology): “However, they can be the method of choice for data sets with few transactions and (very) many items as they occur, for instance, in gene expression analysis 56 , 57 or text mining.”