BicAT: a biclustering analysis toolbox
نویسندگان
چکیده
SUMMARY Besides classical clustering methods such as hierarchical clustering, in recent years biclustering has become a popular approach to analyze biological data sets, e.g. gene expression data. The Biclustering Analysis Toolbox (BicAT) is a software platform for clustering-based data analysis that integrates various biclustering and clustering techniques in terms of a common graphical user interface. Furthermore, BicAT provides different facilities for data preparation, inspection and postprocessing such as discretization, filtering of biclusters according to specific criteria or gene pair analysis for constructing gene interconnection graphs. The possibility to use different biclustering algorithms inside a single graphical tool allows the user to compare clustering results and choose the algorithm that best fits a specific biological scenario. The toolbox is described in the context of gene expression analysis, but is also applicable to other types of data, e.g. data from proteomics or synthetic lethal experiments. AVAILABILITY The BicAT toolbox is freely available at http://www.tik.ee.ethz.ch/sop/bicat and runs on all operating systems. The Java source code of the program and a developer's guide is provided on the website as well. Therefore, users may modify the program and add further algorithms or extensions.
منابع مشابه
Analysis and visualization of gene expression data using biclustering: A comparative study
In the last few years the gene expression microarray technology has become a central tool in the field of functional genomics in which the expression levels of thousands of genes in a biological sample are determined in a single experiment. Several clustering and biclustering methods have been introduced to analyze the gene expression data by identifying the similar patterns and grouping genes ...
متن کاملSebastian Kaiser and Friedrich Leisch A Toolbox for Bicluster Analysis
Over the last decade, bicluster methods have become more and more popular in different fields of two way data analysis and a wide variety of algorithms and analysis methods have been published. In this paper we introduce the R package biclust, which contains a collection of bicluster algorithms, preprocessing methods for two way data, and validation and visualization techniques for bicluster re...
متن کاملBayesian Biclustering of Gene Expression
Background: Biclustering of gene expression data searches for local patterns of gene expression. A bicluster (or a two-way cluster) is defined as a set of genes whose expression profiles are mutually similar within a subset of experimental conditions/samples. Although several biclustering algorithms have been studied, few are based on rigorous statistical models. Results: We developed a Bayesia...
متن کاملDNA Microarray Data Analysis: A Novel Biclustering Algorithm Approach
Biclustering algorithms refer to a distinct class of clustering algorithms that perform simultaneous row-column clustering. Biclustering problems arise in DNAmicroarray data analysis, collaborative filtering, market research, information retrieval, text mining, electoral trends, exchange analysis, and so forth. When dealing with DNA microarray experimental data for example, the goal of bicluste...
متن کاملQuery-based Biclustering using Formal Concept Analysis
Biclustering methods have proven to be critical tools in the exploratory analysis of high-dimensional data including information networks, microarray experiments, and bag of words data. However, most biclustering methods fail to answer specific questions of interest and do not incorporate prior knowledge and expertise from the user. To this end, query-based biclustering algorithms that are rece...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- Bioinformatics
دوره 22 10 شماره
صفحات -
تاریخ انتشار 2006