Microarray data mining using landmark gene-guided clustering |
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| Authors: | Pankaj Chopra Jaewoo Kang Jiong Yang HyungJun Cho Heenam Stanley Kim Min-Goo Lee |
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| Institution: | (1) Dept. of ComputerScience, NorthCarolina StateUniverstiy, Raleigh, NC27606, USA;(2) Dept. of Computer Science and Engineering, Korea University, Seoul, Korea;(3) Dept. of Biostatistics, College of Medicine, Korea University, Seoul, Korea;(4) Case Western Reserve University, Cleveland, OH-44106, USA;(5) Dept. of Statistics, Korea University, Seoul, Korea;(6) Bioinformatics and Functional Genomics Laboratory, Graduate School of Medicine, Korea University, Seoul, Korea;(7) Department of Physiology, College of Medicine, Korea University, Seoul, Korea |
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| Abstract: | Background Clustering is a popular data exploration technique widely used in microarray data analysis. Most conventional clustering algorithms,
however, generate only one set of clusters independent of the biological context of the analysis. This is often inadequate
to explore data from different biological perspectives and gain new insights. We propose a new clustering model that can generate
multiple versions of different clusters from a single dataset, each of which highlights a different aspect of the given dataset. |
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