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152
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KDD
2009
ACM
230views Data Mining» more  KDD 2009»
15 years 8 months ago
Grouped graphical Granger modeling methods for temporal causal modeling
We develop and evaluate an approach to causal modeling based on time series data, collectively referred to as“grouped graphical Granger modeling methods.” Graphical Granger mo...
Aurelie C. Lozano, Naoki Abe, Yan Liu, Saharon Ros...
157
Voted
BMCBI
2006
153views more  BMCBI 2006»
15 years 3 months ago
Intensity-based hierarchical Bayes method improves testing for differentially expressed genes in microarray experiments
Background: The small sample sizes often used for microarray experiments result in poor estimates of variance if each gene is considered independently. Yet accurately estimating v...
Maureen A. Sartor, Craig R. Tomlinson, Scott C. We...
132
Voted
BMCBI
2005
121views more  BMCBI 2005»
15 years 3 months ago
Automated methods of predicting the function of biological sequences using GO and BLAST
Background: With the exponential increase in genomic sequence data there is a need to develop automated approaches to deducing the biological functions of novel sequences with hig...
Craig E. Jones, Ute Baumann, Alfred L. Brown
133
Voted
BMCBI
2010
147views more  BMCBI 2010»
15 years 3 months ago
baySeq: Empirical Bayesian methods for identifying differential expression in sequence count data
Background: High throughput sequencing has become an important technology for studying expression levels in many types of genomic, and particularly transcriptomic, data. One key w...
Thomas J. Hardcastle, Krystyna A. Kelly
103
Voted
BMCBI
2005
82views more  BMCBI 2005»
15 years 3 months ago
A novel method for prokaryotic promoter prediction based on DNA stability
Background: In the post-genomic era, correct gene prediction has become one of the biggest challenges in genome annotation. Improved promoter prediction methods can be one step to...
Aditi Kanhere, Manju Bansal