Constructing interaction network from biomedical texts is a very important and interesting work. The authors take advantage of text mining and reinforcement learning approaches to establish protein interaction network. Considering the high computatio...
Networks are ubiquitous in biology, and computational approaches have been largely investigated for their inference. In particular, supervised machine learning methods can be used to complete a partially known network by integrating various measureme...
Journal of cancer research and therapeutics
Jan 1, 2015
AIM: There are various therapeutic modalities of treatment for non-Hodgkin's lymphoma, but with certain limitations, hence, investigating the scope of combined therapeutic approach.
IEEE/ACM transactions on computational biology and bioinformatics
Jan 1, 2015
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...
IEEE/ACM transactions on computational biology and bioinformatics
Jan 1, 2015
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...
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...
IEEE/ACM transactions on computational biology and bioinformatics
Jan 1, 2015
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...
International journal of data mining and bioinformatics
Jan 1, 2015
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...