Two-Way Clustering Analysis using Parallel Fuzzy Approach for Microarray Gene Expression Data
نویسندگان
چکیده
منابع مشابه
Coupled two-way clustering analysis of gene microarray data.
We present a coupled two-way clustering approach to gene microarray data analysis. The main idea is to identify subsets of the genes and samples, such that when one of these is used to cluster the other, stable and significant partitions emerge. The search for such subsets is a computationally complex task. We present an algorithm, based on iterative clustering, that performs such a search. Thi...
متن کاملGene microarray data analysis using parallel point-symmetry-based clustering
Identification of co-expressed genes is the central goal in microarray gene expression analysis. Point-symmetry-based clustering is an important unsupervised learning technique for recognising symmetrical convex- or non-convex-shaped clusters. To enable fast clustering of large microarray data, we propose a distributed time-efficient scalable approach for point-symmetry-based K-Means algorithm....
متن کاملInterrelated Two-way Clustering: An Unsupervised Approach for Gene Expression Data Analysis
DNA arrays can be used to measure the expression levels of thousands of genes simultaneously. Currently most research focuses on the interpretation of the meaning of the data. However, majority methods are supervised-based, less attention has been paid on unsupervised approaches which is important when domain knowledge is incomplete or hard to obtain. In this paper, we present a new framework f...
متن کاملGene Expression Data Clustering using a Fuzzy Link based Approach
There are many clustering algorithms for gene expression data in the literature that are robust against noise and outliers. The limitation with many of these algorithms is that they cannot identify the overlapping and intersecting clusters. This paper presents an algorithm for clustering gene expression data using the concepts of common neighbors and fuzzy clustering for detecting intersecting ...
متن کاملA Fuzzy Approach for Clustering Gene Expression Time Series Data
Identifying groups of genes that manifest similar expression patterns is crucial in the analysis of gene expression time series data. Choosing a similarity measure to determine the similarity or distance between profiles is an important task. Time series expression experiments are used to study a wide range of biological systems. More than 80% of all time series expression datasets are short (8...
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: International Journal of Computer Applications
سال: 2015
ISSN: 0975-8887
DOI: 10.5120/ijca2015905483