Background: Concomitant with the rise in the popularity of DNA microarrays has been a surge of proposed methods for the analysis of microarray data. Fully controlled "spike-i...
Qianqian Zhu, Jeffrey C. Miecznikowski, Marc S. Ha...
Background: Microarray analysis has become a widely used technique for the study of geneexpression patterns on a genomic scale. As more and more laboratories are adopting microarr...
Michael Maurer, Robert Molidor, Alexander Sturn, J...
This paper discusses different approaches for integrating biological knowledge in gene expression analysis. Indeed we are interested in the fifth step of microarray analysis pro...
Background: Microarrays are routinely used to assess mRNA transcript levels on a genome-wide scale. Large amount of microarray datasets are now available in several databases, and...
Mattia Pelizzola, Norman Pavelka, Maria Foti, Paol...
Background: Aristolochic acid (AA) is the active component of herbal drugs derived from Aristolochia species that have been used for medicinal purposes since antiquity. AA, howeve...
Tao Chen, Lei Guo, Lu Zhang 0013, Leming M. Shi, H...
Background: Microarray analysis allows the simultaneous measurement of thousands to millions of genes or sequences across tens to thousands of different samples. The analysis of t...
Jon Hill, Matthew Hambley, Thorsten Forster, Murie...
Background: Microarray analysis is an important area of bioinformatics. In the last few years, biclustering has become one of the most popular methods for classifying data from mi...
Microarray analysis using clustering algorithms can suffer from lack of inter-method consistency in assigning related gene-expression profiles to clusters. Obtaining a consensus s...
Paul Kellam, Stephen Swift, Allan Tucker, Veronica...