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108views more  BMCBI 2010»
9 years 9 months ago
Preferred analysis methods for Affymetrix GeneChips. II. An expanded, balanced, wholly-defined spike-in dataset
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...
179views more  BMCBI 2005»
10 years 2 months ago
MARS: Microarray analysis, retrieval, and storage system
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...
98views more  IJCSA 2007»
10 years 2 months ago
Extracted Knowledge Interpretation in mining biological data: a survey
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...
Martine Collard, Ricardo Martínez
374views more  BMCBI 2006»
10 years 2 months ago
AMDA: an R package for the automated microarray data analysis
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...
118views more  BMCBI 2006»
10 years 2 months ago
Gene Expression Profiles Distinguish the Carcinogenic Effects of Aristolochic Acid in Target (Kidney) and Non-target (Liver) Tis
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...
108views more  BMCBI 2008»
10 years 2 months ago
SPRINT: A new parallel framework for R
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...
114views more  BMCBI 2008»
10 years 2 months ago
A visual analytics approach for understanding biclustering results from microarray data
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...
Rodrigo Santamaría, Roberto Therón, ...
171views Bioinformatics» more  JBI 2004»
10 years 4 months ago
Consensus Clustering and Functional Interpretation of Gene Expression Data
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...