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» Semantic Mining and Analysis of Gene Expression Data
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CSB
2005
IEEE
189views Bioinformatics» more  CSB 2005»
15 years 3 months ago
Learning Yeast Gene Functions from Heterogeneous Sources of Data Using Hybrid Weighted Bayesian Networks
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 ...
Xutao Deng, Huimin Geng, Hesham H. Ali
ICA
2007
Springer
15 years 1 months ago
Infinite Sparse Factor Analysis and Infinite Independent Components Analysis
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...
David Knowles, Zoubin Ghahramani
BMCBI
2006
107views more  BMCBI 2006»
14 years 10 months ago
Simplifying gene trees for easier comprehension
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...
ADBIS
1999
Springer
104views Database» more  ADBIS 1999»
15 years 2 months ago
Mining Various Patterns in Sequential Data in an SQL-like Manner
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...
Marek Wojciechowski
BMCBI
2007
120views more  BMCBI 2007»
14 years 10 months ago
Recognition of interferon-inducible sites, promoters, and enhancers
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...