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» Methods for Predicting Target Sites of Transcription Factors
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ICMLA
2008
13 years 10 months ago
Ensemble Machine Methods for DNA Binding
We introduce three ensemble machine learning methods for analysis of biological DNA binding by transcription factors (TFs). The goal is to identify both TF target genes and their ...
Yue Fan, Mark A. Kon, Charles DeLisi
BMCBI
2007
174views more  BMCBI 2007»
13 years 8 months ago
Inferring activity changes of transcription factors by binding association with sorted expression profiles
Background: The identification of transcription factors (TFs) associated with a biological process is fundamental to understanding its regulatory mechanisms. From microarray data,...
Chao Cheng, Xiting Yan, Fengzhu Sun, Lei M. Li
NAR
2010
184views more  NAR 2010»
13 years 3 months ago
RegPrecise: a database of curated genomic inferences of transcriptional regulatory interactions in prokaryotes
The RegPrecise database (http://regprecise.lbl.gov) was developed for capturing, visualization and analysis of predicted transcription factor regulons in prokaryotes that were rec...
Pavel S. Novichkov, Olga N. Laikova, Elena S. Novi...
BMCBI
2004
167views more  BMCBI 2004»
13 years 8 months ago
Feature selection for splice site prediction: A new method using EDA-based feature ranking
Background: The identification of relevant biological features in large and complex datasets is an important step towards gaining insight in the processes underlying the data. Oth...
Yvan Saeys, Sven Degroeve, Dirk Aeyels, Pierre Rou...
BMCBI
2007
167views more  BMCBI 2007»
13 years 8 months ago
A stochastic differential equation model for transcriptional regulatory networks
Background: This work explores the quantitative characteristics of the local transcriptional regulatory network based on the availability of time dependent gene expression data se...
Adriana Climescu-Haulica, Michelle D. Quirk