Analysis of gene expression data can help to find the time-lagged co-regulation of gene cluster. However, existing method just solve the problem under the condition when the data is discrete number. In this paper, we propose efficient algorithm to indentify time-lagged co-regulated gene cluster based on real number.

We apply spectral biclustering to mortality datasets in order to capture three relevant aspects: the period, the age and the cohort effects, as their knowledge is a key factor in understanding actuarial liabilities of private life insurance companies, pension funds as well as national pension systems. While standard techniques generally fail to capture the cohort effect, on the contrary, biclus...

Non-supervised machine learning methods have been used in the analysis of gene expression data obtained from microarray experiments. Recently, biclustering, a non-supervised approach that performs simultaneous clustering on the row and column dimensions of the data matrix, has been shown to be remarkably effective in a variety of applications. The goal of biclustering [1] is to find subgroups o...

Microarray technology produces large amounts of information to be manipulated by analysis methods, such as biclustering algorithms, to extract new knowledge. All-purpose multivariate data visualization tools are usually not enough for studying microarray experiments. Additionally, clustering tools do not provide means of simultaneous visualization of all the biclusters obtained. We present an i...

Qian Liu: Non-parametric machine learning methods for clustering and variable selection (Under the direction of Eric Bair) Non-parametric machine learning methods have been popular and widely used in many scientific research areas, especially when dealing with high-dimension low sample size (HDLSS) data. In particular, clustering and biclustering approaches can serve as exploratory analysis too...

This paper presents PCFG-BCL, an unsupervised algorithm that learns a probabilistic context-free grammar (PCFG) from positive samples. The algorithm acquires rules of an unknown PCFG through iterative biclustering of bigrams in the training corpus. Our analysis shows that this procedure uses a greedy approach to adding rules such that each set of rules that is added to the grammar results in th...

A Recommender system is one of the best web usage mining Application which reduces the difficulties faced by the users to meet their requirements. Web usage mining is the process of obtaining useful knowledge from the server logs. In this work, a new recommendation system is proposed to predict the user’s navigational behaviour. We are using the biclustering approach with greedy search and gene...

Identifying latent structure in high-dimensional genomic data is essential for exploring biological processes. Here, we consider recovering gene co-expression networks from gene expression data, where each network encodes relationships between genes that are co-regulated by shared biological mechanisms. To do this, we develop a Bayesian statistical model for biclustering to infer subsets of co-...