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JMLR
2006
169views more  JMLR 2006»
13 years 8 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 ...
BMCBI
2011
13 years 3 months ago
A Computational Framework for Proteome-Wide Pursuit and Prediction of Metalloproteins using ICP-MS and MS/MS Data
Background: Metal-containing proteins comprise a diverse and sizable category within the proteomes of organisms, ranging from proteins that use metals to catalyze reactions to pro...
W. Andrew Lancaster, Jeremy L. Praissman, Farris L...
DARE
2000
125views more  DARE 2000»
13 years 10 months ago
Developing mixed reality boundaries
Our work in the field of mixed reality has been concerned with the development of the mixed reality boundary approach. In contrast to other approaches that focus on superimposing ...
Boriana Koleva, Holger Schnädelbach, Steve Be...
CVPR
2008
IEEE
14 years 11 months ago
Small codes and large image databases for recognition
The Internet contains billions of images, freely available online. Methods for efficiently searching this incredibly rich resource are vital for a large number of applications. Th...
Antonio B. Torralba, Robert Fergus, Yair Weiss
BMCBI
2008
116views more  BMCBI 2008»
13 years 9 months ago
IgTM: An algorithm to predict transmembrane domains and topology in proteins
Background: Due to their role of receptors or transporters, membrane proteins play a key role in many important biological functions. In our work we used Grammatical Inference (GI...
Piedachu Peris, Damián López, Marcel...