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» A Method for Similarity-Based Grouping of Biological Data
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BMCBI
2008
104views more  BMCBI 2008»
14 years 9 months ago
Missing value imputation improves clustering and interpretation of gene expression microarray data
Background: Missing values frequently pose problems in gene expression microarray experiments as they can hinder downstream analysis of the datasets. While several missing value i...
Johannes Tuikkala, Laura Elo, Olli Nevalainen, Ter...
IDEAL
2004
Springer
15 years 2 months ago
Prediction of Implicit Protein-Protein Interaction by Optimal Associative Feature Mining
Proteins are known to perform a biological function by interacting with other proteins or compounds. Since protein–protein interaction is intrinsic to most cellular processes, pr...
Jae-Hong Eom, Jeong Ho Chang, Byoung-Tak Zhang
BMCBI
2010
164views more  BMCBI 2010»
14 years 6 months ago
Merged consensus clustering to assess and improve class discovery with microarray data
Background: One of the most commonly performed tasks when analysing high throughput gene expression data is to use clustering methods to classify the data into groups. There are a...
T. Ian Simpson, J. Douglas Armstrong, Andrew P. Ja...
BMCBI
2007
105views more  BMCBI 2007»
14 years 9 months ago
Text-derived concept profiles support assessment of DNA microarray data for acute myeloid leukemia and for androgen receptor sti
Background: High-throughput experiments, such as with DNA microarrays, typically result in hundreds of genes potentially relevant to the process under study, rendering the interpr...
Rob Jelier, Guido Jenster, Lambert C. J. Dorssers,...
ISMB
1993
14 years 10 months ago
Computationally Efficient Cluster Representation in Molecular Sequence Megaclassification
Molecular sequence megaclassification is a technique for automated protein sequence analysis and annotation. Implementation of the method has been limited by the need to store and...
David J. States, Nomi L. Harris, Lawrence Hunter