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FUIN
2011
358views Cryptology» more  FUIN 2011»
13 years 1 days ago
Unsupervised and Supervised Learning Approaches Together for Microarray Analysis
In this article, a novel concept is introduced by using both unsupervised and supervised learning. For unsupervised learning, the problem of fuzzy clustering in microarray data as ...
Indrajit Saha, Ujjwal Maulik, Sanghamitra Bandyopa...
BMCBI
2004
185views more  BMCBI 2004»
13 years 8 months ago
Linear fuzzy gene network models obtained from microarray data by exhaustive search
Background: Recent technological advances in high-throughput data collection allow for experimental study of increasingly complex systems on the scale of the whole cellular genome...
Bahrad A. Sokhansanj, J. Patrick Fitch, Judy N. Qu...
BMCBI
2007
176views more  BMCBI 2007»
13 years 8 months ago
The Firegoose: two-way integration of diverse data from different bioinformatics web resources with desktop applications
Background: Information resources on the World Wide Web play an indispensable role in modern biology. But integrating data from multiple sources is often encumbered by the need to...
J. Christopher Bare, Paul T. Shannon, Amy K. Schmi...
BMCBI
2008
122views more  BMCBI 2008»
13 years 8 months ago
Determining gene expression on a single pair of microarrays
Background: In microarray experiments the numbers of replicates are often limited due to factors such as cost, availability of sample or poor hybridization. There are currently fe...
Robert W. Reid, Anthony A. Fodor
BMCBI
2006
147views more  BMCBI 2006»
13 years 8 months ago
Grouping Gene Ontology terms to improve the assessment of gene set enrichment in microarray data
Background: Gene Ontology (GO) terms are often used to assess the results of microarray experiments. The most common way to do this is to perform Fisher's exact tests to find...
Alex Lewin, Ian C. Grieve