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» Learning Methods for DNA Binding in Computational Biology
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ISMB
1994
13 years 8 months ago
Stochastic Motif Extraction Using Hidden Markov Model
In this paper, westudy the application of an ttMM(hidden Markov model) to the problem of representing protein sequencesby a stochastic motif. Astochastic protein motif represents ...
Yukiko Fujiwara, Minoru Asogawa, Akihiko Konagaya
RECOMB
2011
Springer
12 years 10 months ago
Rich Parameterization Improves RNA Structure Prediction
Motivation. Current approaches to RNA structure prediction range from physics-based methods, which rely on thousands of experimentally-measured thermodynamic parameters, to machin...
Shay Zakov, Yoav Goldberg, Michael Elhadad, Michal...
CONSTRAINTS
2008
182views more  CONSTRAINTS 2008»
13 years 7 months ago
Constraint Programming in Structural Bioinformatics
Bioinformatics aims at applying computer science methods to the wealth of data collected in a variety of experiments in life sciences (e.g. cell and molecular biology, biochemistry...
Pedro Barahona, Ludwig Krippahl
BMCBI
2008
138views more  BMCBI 2008»
13 years 7 months ago
Using neural networks and evolutionary information in decoy discrimination for protein tertiary structure prediction
Background: We present a novel method of protein fold decoy discrimination using machine learning, more specifically using neural networks. Here, decoy discrimination is represent...
Ching-Wai Tan, David T. Jones
RECOMB
2009
Springer
14 years 8 months ago
Spatial Clustering of Multivariate Genomic and Epigenomic Information
The combination of fully sequence genomes and new technologies for high density arrays and ultra-rapid sequencing enables the mapping of generegulatory and epigenetics marks on a g...
Rami Jaschek, Amos Tanay