Classifying genes into clusters depending on their expression profiles is one of the most important analyses of microarray data. Since temporal gene expression profiles of microarray data are the condense of the information on dynamic functional property of genes, the application of clustering analysis to time-course data makes it possible to divide them into functional classes much more precisely. Conventional clusterin
<p>The expression data were loaded onto STEM platform and distinct temporal expression profiles were...
The next generation sequencing technology (RNA-seq) provides absolute quantifi-cation of gene expres...
BACKGROUND: Time-course microarray experiments can produce useful data which can help in understandi...
Microarray technology has produced a huge body of time-course gene expression data and will continue...
High-throughput time-course studies collect measurements from samples across time. Inparticular, lon...
High-throughput time-course studies collect measurements from samples across time. Inparticular, lon...
Functional gene research is an important issue in Post-genomic era. Microarray is used to generate l...
This work performs a data driven comparative study of clustering methods used in the analysis of gen...
The development of microarray technology has enabled simultaneous expression measurements from tens ...
BACKGROUND. Many microarray experiments produce temporal profiles in different biological conditions...
This thesis examines methods used to cluster time-course gene expression array data. In the past dec...
Summarization: Statistical evaluation of temporal gene expression profiles plays an important role i...
Clustering techniques are important for gene expression data analysis. However, efficient computatio...
Clustering time course gene expression data allows one to explore functional co-regulation of genes ...
Microarray experiments are information rich; however, extensive data mining is required to identify ...
<p>The expression data were loaded onto STEM platform and distinct temporal expression profiles were...
The next generation sequencing technology (RNA-seq) provides absolute quantifi-cation of gene expres...
BACKGROUND: Time-course microarray experiments can produce useful data which can help in understandi...
Microarray technology has produced a huge body of time-course gene expression data and will continue...
High-throughput time-course studies collect measurements from samples across time. Inparticular, lon...
High-throughput time-course studies collect measurements from samples across time. Inparticular, lon...
Functional gene research is an important issue in Post-genomic era. Microarray is used to generate l...
This work performs a data driven comparative study of clustering methods used in the analysis of gen...
The development of microarray technology has enabled simultaneous expression measurements from tens ...
BACKGROUND. Many microarray experiments produce temporal profiles in different biological conditions...
This thesis examines methods used to cluster time-course gene expression array data. In the past dec...
Summarization: Statistical evaluation of temporal gene expression profiles plays an important role i...
Clustering techniques are important for gene expression data analysis. However, efficient computatio...
Clustering time course gene expression data allows one to explore functional co-regulation of genes ...
Microarray experiments are information rich; however, extensive data mining is required to identify ...
<p>The expression data were loaded onto STEM platform and distinct temporal expression profiles were...
The next generation sequencing technology (RNA-seq) provides absolute quantifi-cation of gene expres...
BACKGROUND: Time-course microarray experiments can produce useful data which can help in understandi...