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The application of Gaussian processes in the prediction of percutaneous absorption
(2009-09)
Objectives The aim was to assess mathematically the nature of a skin permeability dataset and to determine the utility of Gaussian processes in developing a predictive model for skin permeability, comparing it with existing ...
Decoding of Purkinje cell pauses by deep cerebellar nucleus neurons
(BioMed Central (BMC), 2009)
The recognition of parallel fibre (PF) input patterns by Purkinje cells has been suggested to underlie cerebellar learning [1,2]. A candidate mechanism for the recognition of PF patterns is the long-term depression (LTD) ...
The performance pf sparsley-connected 2D associative memory models with non-random images
(World Scientific Publishing, 2009)
A sparsely connected associative memory model is built with small-world connectivity, and trained on both random, and real-world image sets. It is found that pattern recall using real-world images can vary significantly ...
Adaptive electrical signal post-processing with varying representations in optical communication systems
(2009)
Improving bit error rates in optical communication systems is a difficult and important problem. Error detection and correction must take place at: high speed, and be extremely accurate. Also, different communication ...
Prediction of skin penetration using machine learning methods
(Institute of Electrical and Electronics Engineers (IEEE), 2008)
Improving predictions of the skin permeability coefficient is a difficult problem. It is also an important issue with the increasing use of skin patches as a means of drug delivery. In this work, we applyK-nearest-neighbour ...
Using real-valued metaclassifiers to integrate binding site predictions
(Institute of Electrical and Electronics Engineers (IEEE), 2005)
Currently the best algorithms for transcription factor binding site prediction are severely limited in accuracy. There is good reason to believe that predictions from these different classes of algorithms could be used in ...
Optimising a hierarchical neural clusterer applied to large gene sequence data sets
(Institute of Electrical and Electronics Engineers (IEEE), 2004)
Evolutionary Algorithms have been used to optimise the performance of neural network models before. This paper uses a hybrid approach by permanently attaching a Genetic Algorithm (GA) to a hierarchical clusterer to investigate ...