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ISMB
1996
13 years 8 months ago
Refining Neural Network Predictions for Helical Transmembrane Proteins by Dynamic Programming
For transmembrane proteins experimental determina-tion of three-dimensional structure is problematic. However, membrane proteins have important impact for molecular biology in gen...
Burkhard Rost, Rita Casadio, Piero Fariselli
ICML
2004
IEEE
14 years 7 months ago
Learning first-order rules from data with multiple parts: applications on mining chemical compound data
Inductive learning of first-order theory based on examples has serious bottleneck in the enormous hypothesis search space needed, making existing learning approaches perform poorl...
Cholwich Nattee, Sukree Sinthupinyo, Masayuki Numa...
JBCB
2010
123views more  JBCB 2010»
13 years 5 months ago
Characterizing the Space of interatomic Distance Distribution Functions Consistent with Solution Scattering Data
: Scattering of neutrons and x-rays from molecules in solution offers alternative approaches to the studying of a wide range of macromolecular structures in their solution state w...
Paritosh A. Kavathekar, Bruce A. Craig, Alan M. Fr...
POPL
2011
ACM
12 years 9 months ago
Dynamic inference of static types for ruby
There have been several efforts to bring static type inference to object-oriented dynamic languages such as Ruby, Python, and Perl. In our experience, however, such type inference...
Jong-hoon (David) An, Avik Chaudhuri, Jeffrey S. F...
CPAIOR
2009
Springer
14 years 1 months ago
Modelling Search Strategies in Rules2CP
In this abstract, we present a rule-based modelling language for constraint programming, called Rules2CP [1], and a library PKML for modelling packing problems. Unlike other modell...
François Fages, Julien Martin