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» Mining Quantitative Association Rules in Protein Sequences
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ROCAI
2004
Springer
14 years 27 days ago
Learning Mixtures of Localized Rules by Maximizing the Area Under the ROC Curve
We introduce a model class for statistical learning which is based on mixtures of propositional rules. In our mixture model, the weight of a rule is not uniform over the entire ins...
Tobias Sing, Niko Beerenwinkel, Thomas Lengauer
BMCBI
2008
173views more  BMCBI 2008»
13 years 7 months ago
Improved machine learning method for analysis of gas phase chemistry of peptides
Background: Accurate peptide identification is important to high-throughput proteomics analyses that use mass spectrometry. Search programs compare fragmentation spectra (MS/MS) o...
Allison Gehrke, Shaojun Sun, Lukasz A. Kurgan, Nat...
BMCBI
2004
144views more  BMCBI 2004»
13 years 7 months ago
GOtcha: a new method for prediction of protein function assessed by the annotation of seven genomes
Background: The function of a novel gene product is typically predicted by transitive assignment of annotation from similar sequences. We describe a novel method, GOtcha, for pred...
David M. A. Martin, Matthew Berriman, Geoffrey J. ...
BMCBI
2006
195views more  BMCBI 2006»
13 years 7 months ago
Hubs of knowledge: using the functional link structure in Biozon to mine for biologically significant entities
Background: Existing biological databases support a variety of queries such as keyword or definition search. However, they do not provide any measure of relevance for the instance...
Paul Shafer, Timothy Isganitis, Golan Yona
BMCBI
2006
152views more  BMCBI 2006»
13 years 7 months ago
Predicting deleterious nsSNPs: an analysis of sequence and structural attributes
Background: There has been an explosion in the number of single nucleotide polymorphisms (SNPs) within public databases. In this study we focused on non-synonymous protein coding ...
Richard J. B. Dobson, Patricia B. Munroe, Mark J. ...