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» Ensemble Machine Methods for DNA Binding
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ICMLA
2008
9 years 3 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
ICMLA
2007
9 years 3 months ago
SVMotif: A Machine Learning Motif Algorithm
We describe SVMotif, a support vector machine-based learning algorithm for identification of cellular DNA transcription factor (TF) motifs extrapolated from known TF-gene interact...
Mark A. Kon, Yue Fan, Dustin T. Holloway, Charles ...
APBC
2003
128views Bioinformatics» more  APBC 2003»
9 years 3 months ago
Machine Learning in DNA Microarray Analysis for Cancer Classification
The development of microarray technology has supplied a large volume of data to many fields. In particular, it has been applied to prediction and diagnosis of cancer, so that it e...
Sung-Bae Cho, Hong-Hee Won
IJCNN
2006
IEEE
9 years 8 months ago
Comparing Kernels for Predicting Protein Binding Sites from Amino Acid Sequence
— The ability to identify protein binding sites and to detect specific amino acid residues that contribute to the specificity and affinity of protein interactions has importan...
Feihong Wu
JCB
2006
138views more  JCB 2006»
9 years 2 months ago
Recognition and Classification of Histones Using Support Vector Machine
Histones are DNA-binding proteins found in the chromatin of all eukaryotic cells. They are highly conserved and can be grouped into five major classes: H1/H5, H2A, H2B, H3, and H4...
Manoj Bhasin, Ellis L. Reinherz, Pedro A. Reche
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