Incorporating biological knowledge into distance-based clustering analysis of microarray gene expression data

نویسندگان
چکیده

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Incorporating biological knowledge into distance-based clustering analysis of microarray gene expression data

MOTIVATION Because co-expressed genes are likely to share the same biological function, cluster analysis of gene expression profiles has been applied for gene function discovery. Most existing clustering methods ignore known gene functions in the process of clustering. RESULTS To take advantage of accumulating gene functional annotations, we propose incorporating known gene functions into a n...

متن کامل

Incorporating heterogeneous biological data sources in clustering gene expression data

In this paper, a similarity measure between genes with protein-protein interactions is proposed. The chip-chip data are converted into the same form of gene expression data with pearson correlation as its similarity measure. On the basis of the similarity measures of proteinprotein interaction data and chip-chip data, the combined dissimilarity measure is defined. The combined distance measure ...

متن کامل

Incorporating gene functions as priors in model-based clustering of microarray gene expression data

MOTIVATION Cluster analysis of gene expression profiles has been widely applied to clustering genes for gene function discovery. Many approaches have been proposed. The rationale is that the genes with the same biological function or involved in the same biological process are more likely to co-express, hence they are more likely to form a cluster with similar gene expression patterns. However,...

متن کامل

Incorporating prior knowledge of gene functional groups into regularized discriminant analysis of microarray data

MOTIVATION Discriminant analysis for high-dimensional and low-sample-sized data has become a hot research topic in bioinformatics, mainly motivated by its importance and challenge in applications to tumor classifications for high-dimensional microarray data. Two of the popular methods are the nearest shrunken centroids, also called predictive analysis of microarray (PAM), and shrunken centroids...

متن کامل

Clustering analysis of microarray gene expression data by splitting algorithm

Preprint submitted to Elsevier Science 29 April 2003 A clustering method based on recursive bisection is introduced for analyzing microarray gene expression data. Either or both dimensions for the genes and the samples of a given microarray dataset can be classi£ed in an unsupervised fashion. Alternatively, if certain prior knowledge of the genes or samples is available, a supervised version of...

متن کامل

ذخیره 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: Bioinformatics

سال: 2006

ISSN: 1367-4803,1460-2059

DOI: 10.1093/bioinformatics/btl065