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JCB
2006
185views more  JCB 2006»
14 years 11 months ago
A Probabilistic Methodology for Integrating Knowledge and Experiments on Biological Networks
Biological systems are traditionally studied by focusing on a specific subsystem, building an intuitive model for it, and refining the model using results from carefully designed ...
Irit Gat-Viks, Amos Tanay, Daniela Raijman, Ron Sh...
JMLR
2006
169views more  JMLR 2006»
14 years 11 months ago
Bayesian Network Learning with Parameter Constraints
The task of learning models for many real-world problems requires incorporating domain knowledge into learning algorithms, to enable accurate learning from a realistic volume of t...
Radu Stefan Niculescu, Tom M. Mitchell, R. Bharat ...
JCB
2007
144views more  JCB 2007»
14 years 11 months ago
Statistical Estimation of Statistical Mechanical Models: Helix-Coil Theory and Peptide Helicity Prediction
Analysis of biopolymer sequences and structures generally adopts one of two approaches: use of detailed biophysical theoretical models of the system with experimentally-determined...
Scott C. Schmidler, Joseph E. Lucas, Terrence G. O...
BMCBI
2004
208views more  BMCBI 2004»
14 years 11 months ago
Using 3D Hidden Markov Models that explicitly represent spatial coordinates to model and compare protein structures
Background: Hidden Markov Models (HMMs) have proven very useful in computational biology for such applications as sequence pattern matching, gene-finding, and structure prediction...
Vadim Alexandrov, Mark Gerstein
DIS
2010
Springer
14 years 10 months ago
Discovery of Conservation Laws via Matrix Search
Abstract. One of the main goals of Discovery Science is the development and analysis of methods for automatic knowledge discovery in the natural sciences. A central area of natural...
Oliver Schulte, Mark S. Drew