title: The biological knowledge discovery by PCCF measure and PCA-F projection.
abstract: In the process of biological knowledge discovery, PCA is commonly used to complement the clustering analysis, but PCA typically gives the poor visualizations for most gene expression data sets. Here, we propose a PCCF measure, and use PCA-F to display clusters of PCCF, where PCCF and PCA-F are modeled from the modified cumulative probabilities of genes. From the analysis of simulated and experimental data sets, we demonstrate that PCCF is more appropriate and reliable for analyzing gene expression data compared to other commonly used distances or similarity measures, and PCA-F is a good visualization technique for identifying clusters of PCCF, where we aim at such data sets that the expression values of genes are collected at different time points.
authors.affiliation: Department of Mathematics, Southeast University, Nanjing 210096, PR China.|State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, PR China.
authors.forename: Xingang
authors.initials: X
authors.lastname: Jia
authors.affiliation: Department of chemistry, Nanjing Agricultural University, Nanjing 210000, PR China.
authors.forename: Guanqun
authors.initials: G
authors.lastname: Zhu
authors.affiliation: Department of Mathematics, Nanjing Forestry University, Nanjing 210037, PR China.
authors.forename: Qiuhong
authors.initials: Q
authors.lastname: Han
authors.affiliation: State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, PR China.
authors.forename: Zuhong
authors.initials: Z
authors.lastname: Lu
mesh_terms: D000818:Animals; D016000:Cluster Analysis; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D066264:Datasets as Topic; D015870:Gene Expression; D006801:Humans / Q000196:embryology / Q000378:metabolism; D051379:Mice; D025341:Principal Component Analysis; D012160:Retina / Q000254:growth & development / Q000378:metabolism; D012441:Saccharomyces cerevisiae / Q000378:metabolism; D012984:Software; D059467:Transcriptome