In the last decade, recurrent neural networks (RNNs) have attracted more efforts in inferring genetic regulatory networks (GRNs), using time series gene expression data from micro...
Rui Xu, Ganesh K. Venayagamoorthy, Donald C. Wunsc...
New feature selection algorithms for linear threshold functions are described which combine backward elimination with an adaptive regularization method. This makes them particular...
Background: Analyzing differential-gene-expression data in the context of protein-interaction networks (PINs) yields information on the functional cellular status. PINs can be for...
Alexander Platzer, Paul Perco, Arno Lukas, Bernd M...
Background: Structural and functional research often requires the computation of sets of protein structures based on certain properties of the proteins, such as sequence features,...
Background: In class prediction problems using microarray data, gene selection is essential to improve the prediction accuracy and to identify potential marker genes for a disease...