نتایج جستجو برای: microarray time

تعداد نتایج: 1930566  

Modares, Parastoo, Vallian Borujeni, Sadegh,

Chemoresistance is one of the main obstacles to the success of cancer treatment and one of the most important causes of death in patients. In the last decade, progress in high-throughput technologies, including microarray, sequencing, and bioinformatics has greatly resulted in cancer gene profiling and identification of biomarkers for cancer prognosis and prediction. This has greatly improved t...

2009
Oliver Stegle Katherine J. Denby David L. Wild Stuart McHattie Andrew Meade Zoubin Ghahramani Karsten M. Borgwardt

A wealth of time series of microarray measurements have become available over recent years. Several two-sample tests for detecting differential gene expression in these time series have been defined, but they can only answer the question whether a gene is differentially expressed across the whole time series, not in which intervals it is differentially expressed. In this article, we propose a G...

2006
Haoliang Jiang Shuigeng Zhou Jihong Guan Ying Zheng

Clustering is an important technique in microarray data analysis, and mining three-dimensional (3D) clusters in gene-sample-time (simply GST) microarray data is emerging as a hot research topic in this area. A 3D cluster consists of a subset of genes that are coherent on a subset of samples along a segment of time series. This kind of coherent clusters may contain information for the users to i...

Journal: :journal of medical signals and sensors 0
hamidreza saberkaria mousa shamsi mahsa joroughi faegheh golabi mohammad hossein sedaaghi

microarray data have an important role in identification and classification of the cancer tissues. having a few samples of microarrays in cancer researches is always one of the most concerns which lead to some problems in designing the classifiers. for this matter, preprocessing gene selection techniques should be utilized before classification to remove the noninformative genes from the microa...

Journal: :Bioinformatics 2006
Sebastian E. Ahnert Karen Willbrand Francis C. S. Brown Thomas M. A. Fink

MOTIVATION Following the advent of microarray technology in recent years, the challenge for biologists is to identify genes of interest from the thousands of genetic expression levels measured in each microarray experiment. In many cases the aim is to identify pattern in the data series generated by successive microarray measurements. RESULTS Here we introduce a new method of detecting patter...

Journal: :International Journal on Recent and Innovation Trends in Computing and Communication 2022

Microarray data stores the measured expression levels of thousands genes simultaneously which helps researchers to get insight into biological and prognostic information. Cancer is a deadly disease that develops over time involves uncontrolled division body cells. In cancer, many are responsible for cell growth division. But different kinds cancer caused by set genes. So be able better understa...

2008
Ruchi Ghanekar Vinodh Srinivasasainagendra Grier P. Page

1Department of Electrical and Computer Engineering, UAB School of Engineering, University of Alabama at Birmingham, 1530 Third Avenue South, Birmingham, AL 35294-4461, USA 2Department of Biostatistics, University of Alabama at Birmingham, 1665 University Blvd, Birmingham, Al 35294-0022, USA 3Statistics and Epidemiology Unit, RTI International, Oxford Building, Suite 119, 2951 Flowers Road South...

Journal: :Bioinformatics 2008
Matthias E. Futschik Hanspeter Herzel

MOTIVATION Periodic processes play fundamental roles in organisms. Prominent examples are the cell cycle and the circadian clock. Microarray array technology has enabled us to screen complete sets of transcripts for possible association with such fundamental periodic processes on a system-wide level. Frequently, quite large numbers of genes have been detected as periodically expressed. However,...

Journal: :Intell. Data Anal. 2006
Allan Tucker Peter A. C. 't Hoen Veronica Vinciotti Xiaohui Liu

The analysis of microarray data from time-series experiments requires specialised algorithms, which take the temporal ordering of the data into account. In this paper we explore a new architecture of Bayesian classifier that can be used to understand how biological mechanisms differ with respect to time. We show that this classifier improves the classification of microarray data and at the same...

2007
Matthias E. Futschik Hanspeter Herzel

Periodic processes play fundamental roles in organisms. Prominent examples are the cell cycle and the circadian clock. Microarray array technology has enabled us to screen complete sets of transcripts for possible association with such fundamental periodic processes on a system-wide level. Frequently, quite a large number of genes has been detected as periodically expressed. However, the small ...

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