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» Using Formal Concept Analysis for Microarray Data Comparison
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BMCBI
2007
133views more  BMCBI 2007»
13 years 7 months ago
Semi-supervised learning for the identification of syn-expressed genes from fused microarray and in situ image data
Background: Gene expression measurements during the development of the fly Drosophila melanogaster are routinely used to find functional modules of temporally co-expressed genes. ...
Ivan G. Costa, Roland Krause, Lennart Opitz, Alexa...
BMCBI
2010
105views more  BMCBI 2010»
13 years 7 months ago
Effects of scanning sensitivity and multiple scan algorithms on microarray data quality
Background: Maximizing the utility of DNA microarray data requires optimization of data acquisition through selection of an appropriate scanner setting. To increase the amount of ...
Andrew Williams, Errol M. Thomson
BMCBI
2008
133views more  BMCBI 2008»
13 years 7 months ago
A Web-based and Grid-enabled dChip version for the analysis of large sets of gene expression data
Background: Microarray techniques are one of the main methods used to investigate thousands of gene expression profiles for enlightening complex biological processes responsible f...
Luca Corradi, Marco Fato, Ivan Porro, Silvia Scagl...
BMCBI
2007
239views more  BMCBI 2007»
13 years 7 months ago
Pre-processing Agilent microarray data
Background: Pre-processing methods for two-sample long oligonucleotide arrays, specifically the Agilent technology, have not been extensively studied. The goal of this study is to...
Marianna Zahurak, Giovanni Parmigiani, Wayne Yu, R...
FOIKS
2010
Springer
13 years 5 months ago
Two Complementary Classification Methods for Designing a Concept Lattice from Interval Data
This paper holds on the application of two classification methods based on formal concept analysis (FCA) to interval data. The first method uses a similarity between objects while ...
Mehdi Kaytoue-Uberall, Zainab Assaghir, Nizar Mess...