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» A new genetic algorithm in proteomics: Feature selection for...
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GPEM
2007
119views more  GPEM 2007»
13 years 5 months ago
Genomic mining for complex disease traits with "random chemistry"
Our rapidly growing knowledge regarding genetic variation in the human genome offers great potential for understanding the genetic etiology of disease. This, in turn, could revolut...
Margaret J. Eppstein, Joshua L. Payne, Bill C. Whi...
BMCBI
2008
173views more  BMCBI 2008»
13 years 5 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
2010
178views more  BMCBI 2010»
13 years 5 months ago
Selecting high-dimensional mixed graphical models using minimal AIC or BIC forests
Background: Chow and Liu showed that the maximum likelihood tree for multivariate discrete distributions may be found using a maximum weight spanning tree algorithm, for example K...
David Edwards, Gabriel C. G. de Abreu, Rodrigo Lab...
BMCBI
2010
108views more  BMCBI 2010»
13 years 5 months ago
A genetic ensemble approach for gene-gene interaction identification
Background: It has now become clear that gene-gene interactions and gene-environment interactions are ubiquitous and fundamental mechanisms for the development of complex diseases...
Pengyi Yang, Joshua W. K. Ho, Albert Y. Zomaya, Bi...
GECCO
2006
Springer
186views Optimization» more  GECCO 2006»
13 years 9 months ago
Genetic programming for agricultural purposes
Nitrogen is one of the most important chemical intakes to ensure the healthy growth of agricultural crops. However, some environmental concerns emerge (soil and water pollution) w...
Clément Chion, Luis E. Da Costa, Jacques-An...