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» Using sampling methods to improve binding site predictions
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RECOMB
2006
Springer
16 years 22 days ago
Improving Prediction of Zinc Binding Sites by Modeling the Linkage Between Residues Close in Sequence
Abstract. We describe and empirically evaluate machine learning methods for the prediction of zinc binding sites from protein sequences. We start by observing that a data set consi...
Sauro Menchetti, Andrea Passerini, Paolo Frasconi,...
BMCBI
2008
133views more  BMCBI 2008»
15 years 16 days ago
CORE_TF: a user-friendly interface to identify evolutionary conserved transcription factor binding sites in sets of co-regulated
Background: The identification of transcription factor binding sites is difficult since they are only a small number of nucleotides in size, resulting in large numbers of false po...
Matthew S. Hestand, Michiel van Galen, Michel P. V...
BMCBI
2010
108views more  BMCBI 2010»
15 years 16 days ago
An intuitionistic approach to scoring DNA sequences against transcription factor binding site motifs
Background: Transcription factors (TFs) control transcription by binding to specific regions of DNA called transcription factor binding sites (TFBSs). The identification of TFBSs ...
Fernando Garcia-Alcalde, Armando Blanco, Adrian J....
BIOINFORMATICS
2012
13 years 2 months ago
Epigenetic priors for identifying active transcription factor binding sites
Motivation Accurate knowledge of the genome-wide binding of transcription factors in a particular cell type or under a particular condition is necessary for understanding transcri...
Gabriel Cuellar-Partida, Fabian A. Buske, Robert C...
BMCBI
2008
128views more  BMCBI 2008»
15 years 16 days ago
Finding sequence motifs with Bayesian models incorporating positional information: an application to transcription factor bindin
Background: Biologically active sequence motifs often have positional preferences with respect to a genomic landmark. For example, many known transcription factor binding sites (T...
Nak-Kyeong Kim, Kannan Tharakaraman, Leonardo Mari...