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BMCBI
2010
179views more  BMCBI 2010»
13 years 7 months ago
A semi-supervised learning approach to predict synthetic genetic interactions by combining functional and topological properties
Background: Genetic interaction profiles are highly informative and helpful for understanding the functional linkages between genes, and therefore have been extensively exploited ...
Zhuhong You, Zheng Yin, Kyungsook Han, De-Shuang H...
BIOSYSTEMS
2007
115views more  BIOSYSTEMS 2007»
13 years 7 months ago
Evolving fuzzy rules to model gene expression
This paper develops an algorithm that extracts explanatory rules from microarray data, which we treat as time series, using genetic programming (GP) and fuzzy logic. Reverse polis...
Ricardo Linden, Amit Bhaya
BMCBI
2010
144views more  BMCBI 2010»
13 years 7 months ago
Finding sRNA generative locales from high-throughput sequencing data with NiBLS
Background: Next-generation sequencing technologies allow researchers to obtain millions of sequence reads in a single experiment. One important use of the technology is the seque...
Daniel MacLean, Vincent Moulton, David J. Studholm...
BIOCOMP
2010
13 years 5 months ago
A Model Reduction Technique for Stochastic Biochemical Kinetics
Abstract-- Modeling the intermolecular reactions in a single cell is a critical problem in computational biology. Biochemical reaction systems often involve species in both low and...
Silvana Ilie, Ekaterina Kudashkina
CSB
2005
IEEE
189views Bioinformatics» more  CSB 2005»
14 years 1 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