Title :
Co-clustering: A Versatile Tool for Data Analysis in Biomedical Informatics
Author :
Yoon, Sungroh ; Benini, Luca ; De Micheli, Giovanni
fDate :
7/1/2007 12:00:00 AM
Abstract :
Co-clustering has not been much exploited in biomedical informatics, despite its success in other domains. Most of the previous applications were limited to analyzing gene expression data. We performed co-clustering analysis on other types of data and obtained promising results, as summarized in this paper.
Keywords :
biology computing; data analysis; genetics; macromolecules; molecular biophysics; statistical analysis; biomedical informatics; co-clustering analysis; data analysis; gene expression; microRNA regulatory modules; Bioinformatics; Biomedical informatics; Bipartite graph; Data analysis; Gene expression; Genomics; Humans; Performance analysis; RNA; Text mining; Acute myeloid leukemia; biomedical informatics; co-clustering; microRNA; single nucleotide polymorphism; Algorithms; Cluster Analysis; Computational Biology; Oligonucleotide Array Sequence Analysis; Pattern Recognition, Automated; Polymorphism, Single Nucleotide; Sequence Analysis, DNA; Sequence Analysis, RNA;
Journal_Title :
Information Technology in Biomedicine, IEEE Transactions on
DOI :
10.1109/TITB.2007.897575
