We developed a machine learning system for determining gene functions from heterogeneous sources of data sets using a Weighted Naive Bayesian Network (WNB). The knowledge of gene ...
Abstract. A nonparametric Bayesian extension of Independent Components Analysis (ICA) is proposed where observed data Y is modelled as a linear superposition, G, of a potentially i...
Background: In the genomic age, gene trees may contain large amounts of data making them hard to read and understand. Therefore, an automated simplification is important. Results:...
Paul-Ludwig Lott, Marvin Mundry, Christoph Sassenb...
Background: Modeling cancer-related regulatory modules from gene expression profiling of cancer tissues is expected to contribute to our understanding of cancer biology as well as...
Background: Complex human diseases are often caused by multiple mutations, each of which contributes only a minor effect to the disease phenotype. To study the basis for these com...
Michael R. Mehan, Juan Nunez-Iglesias, Chao Dai, M...