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...
Abstract. One of the most important data mining tasks is discovery of frequently occurring patterns in sequences of events. Many algorithms for finding various patterns in sequenti...
Background: Computational analysis of gene regulatory regions is important for prediction of functions of many uncharacterized genes. With this in mind, search of the target genes...
Elena A. Ananko, Yury V. Kondrakhin, Tatyana I. Me...