AIMC Topic: Signal Transduction

Clear Filters Showing 351 to 356 of 356 articles

Mining Gene Regulatory Networks by Neural Modeling of Expression Time-Series.

IEEE/ACM transactions on computational biology and bioinformatics
Discovering gene regulatory networks from data is one of the most studied topics in recent years. Neural networks can be successfully used to infer an underlying gene network by modeling expression profiles as times series. This work proposes a novel...

Fuzzy Logic as a Computational Tool for Quantitative Modelling of Biological Systems with Uncertain Kinetic Data.

IEEE/ACM transactions on computational biology and bioinformatics
Quantitative modelling of biological systems has become an indispensable computational approach in the design of novel and analysis of existing biological systems. However, kinetic data that describe the system's dynamics need to be known in order to...

An effective fuzzy kernel clustering analysis approach for gene expression data.

Bio-medical materials and engineering
Fuzzy clustering is an important tool for analyzing microarray data. A major problem in applying fuzzy clustering method to microarray gene expression data is the choice of parameters with cluster number and centers. This paper proposes a new approac...

P-Finder: Reconstruction of Signaling Networks from Protein-Protein Interactions and GO Annotations.

IEEE/ACM transactions on computational biology and bioinformatics
Because most complex genetic diseases are caused by defects of cell signaling, illuminating a signaling cascade is essential for understanding their mechanisms. We present three novel computational algorithms to reconstruct signaling networks between...

Meta-learning framework applied in bioinformatics inference system design.

International journal of data mining and bioinformatics
This paper describes a meta-learner inference system development framework which is applied and tested in the implementation of bioinformatic inference systems. These inference systems are used for the systematic classification of the best candidates...