NDLI: Binary matrix factorization for analyzing gene expression data

Content Provider	Springer Nature Link
Author	Zhang, Zhong Yuan Li, Tao Ding, Chris Ren, Xian Wen Zhang, Xiang Sun
Copyright Year	2009
Abstract	The advent of microarray technology enables us to monitor an entire genome in a single chip using a systematic approach. Clustering, as a widely used data mining approach, has been used to discover phenotypes from the raw expression data. However traditional clustering algorithms have limitations since they can not identify the substructures of samples and features hidden behind the data. Different from clustering, biclustering is a new methodology for discovering genes that are highly related to a subset of samples. Several biclustering models/methods have been presented and used for tumor clinical diagnosis and pathological research. In this paper, we present a new biclustering model using Binary Matrix Factorization (BMF). BMF is a new variant rooted from non-negative matrix factorization (NMF). We begin by proving a new boundedness property of NMF. Two different algorithms to implement the model and their comparison are then presented. We show that the microarray data biclustering problem can be formulated as a BMF problem and can be solved effectively using our proposed algorithms. Unlike the greedy strategy-based algorithms, our proposed algorithms for BMF are more likely to find the global optima. Experimental results on synthetic and real datasets demonstrate the advantages of BMF over existing biclustering methods. Besides the attractive clustering performance, BMF can generate sparse results (i.e., the number of genes/features involved in each biclustering structure is very small related to the total number of genes/features) that are in accordance with the common practice in molecular biology.
Starting Page	28
Ending Page	52
Page Count	25
File Format	PDF
ISSN	13845810
Journal	Data Mining and Knowledge Discovery
Volume Number	20
Issue Number	1
e-ISSN	1573756X
Language	English
Publisher	Springer US
Publisher Date	2009-09-02
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Biclustering Non-negative matrix factorization Boundedness property of NMF Binary matrix Information Storage and Retrieval Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences Statistics Computing Methodologies Data Mining and Knowledge Discovery Artificial Intelligence (incl. Robotics)
Content Type	Text
Resource Type	Article
Subject	Computer Networks and Communications Information Systems Computer Science Applications

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