Background: The correlation between the expression levels of transcription factors and their target genes can be used to infer interactions within animal regulatory networks, but ...
Aim of this work is to apply a novel comprehensive machine learning tool for data mining to preprocessing and interpretation of gene expression data. Furthermore, some visualizatio...
Roberto Amato, Angelo Ciaramella, N. Deniskina, Ca...
Background: Low-level processing and normalization of microarray data are most important steps in microarray analysis, which have profound impact on downstream analysis. Multiple ...
—We present new results from Computational Neurogenetic Modeling to aid discoveries of complex gene interactions underlying oscillations in neural systems. Interactions of genes ...
Lubica Benuskova, Simei Gomes Wysoski, Nikola K. K...
Background: Clustering is an important analysis performed on microarray gene expression data since it groups genes which have similar expression patterns and enables the explorati...
Xuejun Liu, Kevin K. Lin, Bogi Andersen, Magnus Ra...