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» Learning Methods for DNA Binding in Computational Biology
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86
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GECCO
2006
Springer
172views Optimization» more  GECCO 2006»
15 years 1 months ago
Multi-objective optimisation of the protein-ligand docking problem in drug discovery
The pharmaceutical industry is facing an ever-increasing demand to discover novel drugs that are more effective and safer than existing ones. The industry faces huge problem in im...
A. Oduguwa, A. Tiwari, S. Fiorentino, R. Roy
GECCO
2008
Springer
135views Optimization» more  GECCO 2008»
14 years 10 months ago
Evolving sequence patterns for prediction of sub-cellular locations of eukaryotic proteins
A genetic algorithm (GA) is utilised to discover known and novel PROSITE-like sequence templates that can be used to classify the sub-cellular location of eukaryotic proteins. Whi...
Greg Paperin
89
Voted
BMCBI
2006
161views more  BMCBI 2006»
14 years 9 months ago
A novel approach to phylogenetic tree construction using stochastic optimization and clustering
Background: The problem of inferring the evolutionary history and constructing the phylogenetic tree with high performance has become one of the major problems in computational bi...
Ling Qin, Yixin Chen, Yi Pan, Ling Chen
ALMOB
2008
127views more  ALMOB 2008»
14 years 9 months ago
HuMiTar: A sequence-based method for prediction of human microRNA targets
Background: MicroRNAs (miRs) are small noncoding RNAs that bind to complementary/partially complementary sites in the 3' untranslated regions of target genes to regulate prot...
Jishou Ruan, Hanzhe Chen, Lukasz A. Kurgan, Ke Che...
71
Voted
ICML
2010
IEEE
14 years 10 months ago
On Sparse Nonparametric Conditional Covariance Selection
We develop a penalized kernel smoothing method for the problem of selecting nonzero elements of the conditional precision matrix, known as conditional covariance selection. This p...
Mladen Kolar, Ankur P. Parikh, Eric P. Xing