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» Rich probabilistic models for gene expression
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RECOMB
2006
Springer
14 years 8 months ago
Detecting MicroRNA Targets by Linking Sequence, MicroRNA and Gene Expression Data
MicroRNAs (miRNAs) have recently been discovered as an important class of non-coding RNA genes that play a major role in regulating gene expression, providing a means to control th...
Jim C. Huang, Quaid Morris, Brendan J. Frey
ENTCS
2006
273views more  ENTCS 2006»
13 years 7 months ago
Operator Algebras and the Operational Semantics of Probabilistic Languages
We investigate the construction of linear operators representing the semantics of probabilistic programming languages expressed via probabilistic transition systems. Finite transi...
Alessandra Di Pierro, Herbert Wiklicky
BMCBI
2007
173views more  BMCBI 2007»
13 years 7 months ago
Predicting state transitions in the transcriptome and metabolome using a linear dynamical system model
Background: Modelling of time series data should not be an approximation of input data profiles, but rather be able to detect and evaluate dynamical changes in the time series dat...
Ryoko Morioka, Shigehiko Kanaya, Masami Y. Hirai, ...
GECCO
2005
Springer
156views Optimization» more  GECCO 2005»
14 years 1 months ago
Extraction of informative genes from microarray data
Identification of those genes that might anticipate the clinical behavior of different types of cancers is challenging due to availability of a smaller number of patient samples...
Topon Kumar Paul, Hitoshi Iba
BMCBI
2010
110views more  BMCBI 2010»
13 years 7 months ago
TimeDelay-ARACNE: Reverse engineering of gene networks from time-course data by an information theoretic approach
Background: One of main aims of Molecular Biology is the gain of knowledge about how molecular components interact each other and to understand gene function regulations. Using mi...
Pietro Zoppoli, Sandro Morganella, Michele Ceccare...