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ISMB
1994
15 years 1 months ago
Predicting Location and Structure Of beta-Sheet Regions Using Stochastic Tree Grammars
We describe and demonstrate the effectiveness of a method of predicting protein secondary structures, sheet regions in particular, using a class of stochastic tree grammars as rep...
Hiroshi Mamitsuka, Naoki Abe
GRC
2010
IEEE
15 years 26 days ago
Learning Multiple Latent Variables with Self-Organizing Maps
Inference of latent variables from complicated data is one important problem in data mining. The high dimensionality and high complexity of real world data often make accurate infe...
Lili Zhang, Erzsébet Merényi
BMCBI
2010
147views more  BMCBI 2010»
14 years 12 months ago
baySeq: Empirical Bayesian methods for identifying differential expression in sequence count data
Background: High throughput sequencing has become an important technology for studying expression levels in many types of genomic, and particularly transcriptomic, data. One key w...
Thomas J. Hardcastle, Krystyna A. Kelly
BC
2005
127views more  BC 2005»
14 years 11 months ago
Computational modeling and exploration of contour integration for visual saliency
Abstract Weproposeacomputationalmodelofcontourintegration for visual saliency. The model uses biologically plausible devices to simulate how the representations of elements aligned...
T. Nathan Mundhenk, Laurent Itti
SCP
1998
163views more  SCP 1998»
14 years 11 months ago
Computing with Continuous Change
A central challenge in computer science and knowledge representation is the integration of conceptual frameworks for continuous and discrete change, as exemplified by the theory ...
Vineet Gupta, Radha Jagadeesan, Vijay A. Saraswat