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» Modelling Yeast Pre-rRNA Processing
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CSB
2005
IEEE
189views Bioinformatics» more  CSB 2005»
13 years 11 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
FSKD
2006
Springer
127views Fuzzy Logic» more  FSKD 2006»
13 years 9 months ago
On the Society of Genome: Social Affiliation Network Analysis of Microarray Data
Abstract. To investigate the structure of the genomic interaction network built from yeast gene-expression compendium dataset of hundreds of systematic perturbations, social affili...
Jung Hun Ohn, Jihoon Kim, Ju Han Kim
PSB
2003
13 years 6 months ago
Decomposing Gene Expression into Cellular Processes
We propose a probabilistic model for cellular processes, and an algorithm for discovering them from gene expression data. A process is associated with a set of genes that particip...
Eran Segal, Alexis Battle, Daphne Koller
PSB
2004
13 years 6 months ago
Modeling Cellular Processes with Variational Bayesian Cooperative Vector Quantizer
Gene expression of a cell is controlled by sophisticated cellular processes. The capability of inferring the states of these cellular processes would provide insight into the mech...
Xinghua Lu, Milos Hauskrecht, Roger S. Day
BMCBI
2005
96views more  BMCBI 2005»
13 years 5 months ago
Overview of BioCreAtIvE task 1B: normalized gene lists
Background: Our goal in BioCreAtIve has been to assess the state of the art in text mining, with emphasis on applications that reflect real biological applications, e.g., the cura...
Lynette Hirschman, Marc E. Colosimo, Alexander A. ...