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ICANN
2001
Springer
14 years 3 days ago
Online Symbolic-Sequence Prediction with Discrete-Time Recurrent Neural Networks
This paper studies the use of discrete-time recurrent neural networks for predicting the next symbol in a sequence. The focus is on online prediction, a task much harder than the c...
Juan Antonio Pérez-Ortiz, Jorge Calera-Rubi...
UAI
2000
13 years 9 months ago
Variational Relevance Vector Machines
The Support Vector Machine (SVM) of Vapnik [9] has become widely established as one of the leading approaches to pattern recognition and machine learning. It expresses predictions...
Christopher M. Bishop, Michael E. Tipping
BMCBI
2006
105views more  BMCBI 2006»
13 years 7 months ago
CRNPRED: highly accurate prediction of one-dimensional protein structures by large-scale critical random networks
Background: One-dimensional protein structures such as secondary structures or contact numbers are useful for three-dimensional structure prediction and helpful for intuitive unde...
Akira R. Kinjo, Ken Nishikawa
BMCBI
2007
129views more  BMCBI 2007»
13 years 7 months ago
Exploring inconsistencies in genome-wide protein function annotations: a machine learning approach
Background: Incorrectly annotated sequence data are becoming more commonplace as databases increasingly rely on automated techniques for annotation. Hence, there is an urgent need...
Carson M. Andorf, Drena Dobbs, Vasant Honavar
IJBRA
2007
80views more  IJBRA 2007»
13 years 7 months ago
On predicting secondary structure transition
A function of a protein is dependent on its structure; therefore, predicting a protein structure from an amino acid sequence is an active area of research. Optimally predicting a ...
Raja Loganantharaj, Vivek Philip