Collection of articles for T-61.6080
Using background measurement data
- Large scale data mining approach for gene-specific standardization of microarray gene expression data. Yoon et al., Bioinformatics, 2006.
- A summarization approach for Affymetrix GeneChip data using a reference training set from a large, biologically diverse database. Katz et al., BMC Bioinformatics, 2006. (html)
- Analyzing gene expression data in terms of gene sets: methodological issues. Goeman and Buhlmann, Bioinformatics, 2007. (html)
- Integrative missing value estimation for microarray data. Hu et al., BMC Bioinformatics, 2006. (html)
- Logistic regression with an auxiliary data source. Liao et al., ICML 2005. (pdf)
- Exploration, normalization, and genotype calls of high-density oligonucleotide SNP array data. Carvalho et al., Biostatistics, 2007.
Previous measurements as a prior
- Informative structure priors: joint learning of dynamic regulatory networks from multiple types of genomic data. Bernard et al., PSB 2005. (pdf)
- Multi-task learning for classification with Dirichlet process priors. Xue et al., JMLR 2007. (pdf)
- Inductive Transfer for Bayesian Network Structure Learning. Niculescu-Mizil and Caruana, AISTATS 2007. (pdf)
- Classification of microarray data using gene networks. Rapaport et al., BMC Bioinformatics, 2007. (html)
- Annotating gene function by combining expression data with a modular gene network. Shiga et al., Bioinformatics 2007. (html)
- Supervised reconstruction of biological networks with local models. Bleakley et al., Bioinformatics, 2007.
- Penalized Probabilistic Clustering. Lu and Leen, Neural Computation, 2007. (html)
- Incorporating prior knowledge of predictors into penalized classifiers with multiple penalty terms. Tai et al., Bioinformatics, 2007.
- Kernel-based data fusion for gene prioritization. De Bie et al., Bioinformatics, 2007.
- Too much data, but little inter-changeability: a lesson learned from mining public data on tissue specificity of gene expression. Li et al., Biology Direct, 2006. (html)