Multi-resolution independent component analysis for high-performance tumor classification and biomarker discovery
نویسندگان
چکیده
منابع مشابه
Tumor classification based on independent component analysis
This paper proposes a new method for tumor classification using gene expression data, which mainly contains three steps. Firstly, the original DNA microarray gene expression data are selected using t-statistics. Secondly, the selected genes are modeled by Independent Component Analysis (ICA). Finally, Support Vector Machine (SVM) is used to classify the modeling data. To show the validity of th...
متن کاملgenerative independent component analysis for EEG classification
We present an application of Independent Component Analysis (ICA) to the discrimination of mental tasks for EEG-based Brain Computer Interface systems. ICA is most commonly used with EEG for artifact identification with little work on the use of ICA for direct discrimination of different types of EEG signals. By viewing ICA as a generative model, we can use Bayes’ rule to form a classifier. Thi...
متن کاملPolarimetric SAR Image Classification with High Frequency Component Derived from Wavelet Multi Resolution Analysis: MRA
A method for polarimetric Synthetic Aperture Radar: SAR image classification with high frequency component derived from wavelet Multi-Resolution Analysis: MRA is proposed. Although it is well known that polarization signature derived from fully polarized SAR data is useful for SAR image classifications, it is still unknown how to utilize the polarization signature in the image classification. H...
متن کاملRank based Least-squares Independent Component Analysis
In this paper, we propose a nonparametric rank-based alternative to the least-squares independent component analysis algorithm developed. The basic idea is to estimate the squared-loss mutual information, which used as the objective function of the algorithm, based on its copula density version. Therefore, no marginal densities have to be estimated. We provide empirical evaluation of th...
متن کاملHigh-Order Constrasts for Independent Component Analysis
This article considers high-order measures of independence for the independent component analysis problem and discusses the class of Jacobi algorithms for their optimization. Several implementations are discussed. We compare the proposed approaches with gradient-based techniques from the algorithmic point of view and also on a set of biomedical data.
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: BMC Bioinformatics
سال: 2011
ISSN: 1471-2105
DOI: 10.1186/1471-2105-12-s1-s7