Discovering the complex regulatory networks that govern mRNA expression is an important but difficult problem. Many current approaches use only expression data from microarrays to...
Stephen D. Bay, Jeff Shrager, Andrew Pohorille, Pa...
Motivation: Transcriptional regulatory network (TRN) discovery from one method (e.g. microarray analysis, gene ontology, phylogenic similarity) does not seem feasible due to lack ...
Jingjun Sun, Kagan Tuncay, Alaa Abi Haidar, Lisa E...
Discovering co-expressed genes and coherent expression patterns in gene expression data is an important data analysis task in bioinformatics research and biomedical applications. ...
Clustering suffers from the curse of dimensionality, and similarity functions that use all input features with equal relevance may not be effective. We introduce an algorithm that...
Background: Network Component Analysis (NCA) has shown its effectiveness in discovering regulators and inferring transcription factor activities (TFAs) when both microarray data a...
Chen Wang, Jianhua Xuan, Li Chen, Po Zhao, Yue Wan...