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GECCO
2010
Springer
244views Optimization» more  GECCO 2010»
13 years 8 months ago
Implicit fitness and heterogeneous preferences in the genetic algorithm
This paper takes an economic approach to derive an evolutionary learning model based entirely on the endogenous employment of genetic operators in the service of self-interested a...
Justin T. H. Smith
BMCBI
2008
129views more  BMCBI 2008»
13 years 8 months ago
Prediction of the outcome of preoperative chemotherapy in breast cancer using DNA probes that provide information on both comple
Background: DNA microarray technology has emerged as a major tool for exploring cancer biology and solving clinical issues. Predicting a patient's response to chemotherapy is...
René Natowicz, Roberto Incitti, Euler Guima...
BMCBI
2006
127views more  BMCBI 2006»
13 years 8 months ago
A graph-search framework for associating gene identifiers with documents
Background: One step in the model organism database curation process is to find, for each article, the identifier of every gene discussed in the article. We consider a relaxation ...
William W. Cohen, Einat Minkov
BMCBI
2007
153views more  BMCBI 2007»
13 years 7 months ago
A new pairwise kernel for biological network inference with support vector machines
Background: Much recent work in bioinformatics has focused on the inference of various types of biological networks, representing gene regulation, metabolic processes, protein-pro...
Jean-Philippe Vert, Jian Qiu, William Stafford Nob...
ML
2008
ACM
248views Machine Learning» more  ML 2008»
13 years 7 months ago
Feature selection via sensitivity analysis of SVM probabilistic outputs
Feature selection is an important aspect of solving data-mining and machine-learning problems. This paper proposes a feature-selection method for the Support Vector Machine (SVM) l...
Kai Quan Shen, Chong Jin Ong, Xiao Ping Li, Einar ...