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Integrative approaches for microRNA target prediction: combining sequence information and the paired mRNA and miRNA expression profiles
miRNA target prediction expression profile integrative analysis
2016/1/25
Gene regulation is a key factor in gaining a full understanding of molecular biology. microRNA (miRNA), a novel class of non-coding RNA, has recently been found to be one crucial class of post-transac...
Prediction by Supervised Principal Components
Gene expression Microarray Regression Survival analysis
2015/8/21
In regression problems where the number of predictors greatly exceeds the number of observations, conventional regression techniques may produce unsatisfactory results. We describe a technique called ...
In regression problems where the number of predictors greatly exceeds the number of observations, conventional regression techniques may produce unsatisfactory results. We describe a technique called ...
BOOSTING ALGORITHMS:REGULARIZATION,PREDICTION AND MODEL FITTING
Generalized linear models Generalized additive models Gradient boosting Survival analysis Variable selection Software
2015/8/21
We present a statistical perspective on boosting. Special emphasis is given to estimating potentially complex parametric or nonparametric models, including generalized linear and additive models as we...
Comment:Boosting Algorithms:Regularization,Prediction and Model Fitting
Boosting Algorithms Regularization Prediction Model Fitting
2015/8/21
We congratulate the authors (hereafter BH) for an interesting take on the boosting technology, and for developing a modular computational environment in R for exploring their models. Their use of low-...
Empirical Bayes Estimates for Large-Scale Prediction Problems
microarray prediction empirical Bayes shrunken centroids
2015/8/20
Classical prediction methods such as Fisher's linear discriminant function were designed for
small-scale problems, where the number of predictors N is much smaller than the number of
observations n....
Link Prediction in Graphs with Autoregressive Features
Autoregressive Features Link Prediction Graphs
2012/11/22
In the paper, we consider the problem of link prediction in time-evolving graphs. We assume that certain graph features, such as the node degree, follow a vector autoregressive (VAR) model and we prop...
On spatial selectivity and prediction across conditions with fMRI
Machine learning fMRI feature selection regions
2012/11/22
Researchers in functional neuroimaging mostly use activation coordinates to formulate their hypotheses. Instead, we propose to use the full statistical images to define regions of interest (ROIs). Thi...