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» Learning Methods for DNA Binding in Computational Biology
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ISMB
1994
14 years 11 months ago
Neural Networks for Determining Protein Specificity and Multiple Alignment of Binding Sites
Weuse a quantitative definition of specificity to developa neural networkfor the identification of commonprotein binding sites in a collection of unaligned DNAfragments. Wedemonst...
John M. Heumann, Alan S. Lapedes, Gary D. Stormo
CSB
2003
IEEE
124views Bioinformatics» more  CSB 2003»
15 years 2 months ago
SMASHing regulatory sites in DNA by human
Regulatory sequence elements provide important clues to understanding and predicting gene expression. Although the binding sites for hundreds of transcription factors are known, t...
Mihaela Zavolan, Nicholas D. Socci, Nikolaus Rajew...
104
Voted
EC
1998
112views ECommerce» more  EC 1998»
14 years 9 months ago
DNA Computation: Theory, Practice, and Prospects
L. M. Adleman launched the field of DNA computing with a demonstration in 1994 that strands of DNA could be used to solve the Hamiltonian path problem for a simple graph. He also...
Carlo C. Maley
95
Voted
IPPS
2007
IEEE
15 years 3 months ago
Reconfigurable Architecture for Biological Sequence Comparison in Reduced Memory Space
DNA sequence alignment is a very important problem in bioinformatics. The algorithm proposed by Smith-Waterman (SW) is an exact method that obtains optimal local alignments in qua...
Azzedine Boukerche, Jan Mendonca Correa, Alba Cris...
ICMLA
2007
14 years 11 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 ...