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 Publications
  Learning to predict a context-free language: Analysis of dynamics in recurrent hidden units
  Content, context and connectionist networks
  A comparison of sequence kernels for localization prediction of transmembrane proteins
  Context-free and context-sensitive dynamics in recurrent neural networks
  Understanding prediction systems for HLA-binding peptides and t-cell epitope identification
  Multi-stage redundancy reduction: effective utilisation of small protein data sets
  Reducing the number of support vectors to allay inefficiency of large-scale models in computational biology
  Improved Access To Sequential Motifs: A Note On The Architectural Bias Of Recurrent Networks
  Computing the reversal distance between genomes in the presence of multi-gene families via binary integer programming
  Decoupling signal recognition from sequence models of protein secretion
  Evolving spelling exercises to suit individual student needs
  Identifying novel peroxisomal proteins
  Markovian bias of neural-based architectures with feedback connections
  Predicting Nuclear Localization
  Comparing SVM sequence kernels: A protein subcellular localization theme
  Detecting and sorting targeting peptides wtih neural networks and support vector machines
  Evolving discriminative motifs for recognizing proteins imported to the peroxisome via the PTS2 pathway
  Higher order HMMs for localization prediction of transmembrance proteins
  Identifying sequence regions undergoing conformational change via predicted continuum secondary structure
  Predicting the solvent accessibility of transmembrane residues from protein sequence
  Prediction of protein continuum secondary structure with probabilistic models based on NMR solved structures
  STAR: predicting recombination sites from amino acid sequence
  Prediction of subcellular localization using sequence-biased recurrent networks
  BLOMAP: An encoding of amino acids which improves signal peptide cleavage site prediction
  Detecting residues in targeting peptides
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