David R Gilbert

Summary

Affiliation: University of Glasgow
Country: UK

Publications

  1. ncbi Computational methodologies for modelling, analysis and simulation of signalling networks
    David Gilbert
    Bioinformatics Research Centre, A416, Davidson Building University of Glasgow, Glasgow G12 8QQ, Scotland, UK
    Brief Bioinform 7:339-53. 2006
  2. pmc Predicting protein function by machine learning on amino acid sequences--a critical evaluation
    Ali Al-Shahib
    Biomedical Informatics Signals and Systems Research Laboratory, Department of Electronic, Electrical and Computer Engineering, The University of Birmingham, Birmingham, UK
    BMC Genomics 8:78. 2007
  3. pmc Automatic generation of 3D motifs for classification of protein binding sites
    Jean Christophe Nebel
    Faculty of Computing, Information Systems and Mathematics, Kingston University, Kingston upon Thames, KT1 2EE, UK
    BMC Bioinformatics 8:321. 2007
  4. ncbi A lock-and-key model for protein-protein interactions
    Julie L Morrison
    Bioinformatics Research Centre, Department of Computing Science, University of Glasgow G12 8QQ, UK
    Bioinformatics 22:2012-9. 2006
  5. pmc Computational modelling of the receptor-tyrosine-kinase-activated MAPK pathway
    Richard J Orton
    Bioinformatics Research Centre, Department of Computing Science, University of Glasgow, Glasgow G12 8QQ, Scotland, UK
    Biochem J 392:249-61. 2005
  6. pmc GeneRank: using search engine technology for the analysis of microarray experiments
    Julie L Morrison
    Bioinformatics Research Centre, University of Glasgow, Glasgow, UK
    BMC Bioinformatics 6:233. 2005

Detail Information

Publications6

  1. ncbi Computational methodologies for modelling, analysis and simulation of signalling networks
    David Gilbert
    Bioinformatics Research Centre, A416, Davidson Building University of Glasgow, Glasgow G12 8QQ, Scotland, UK
    Brief Bioinform 7:339-53. 2006
    ..An advantage offered by many of these alternative techniques, which have their origins in computing science, is the ability to perform sophisticated model analysis which can better relate predicted behaviour and observations...
  2. pmc Predicting protein function by machine learning on amino acid sequences--a critical evaluation
    Ali Al-Shahib
    Biomedical Informatics Signals and Systems Research Laboratory, Department of Electronic, Electrical and Computer Engineering, The University of Birmingham, Birmingham, UK
    BMC Genomics 8:78. 2007
    ..Until now, however, it has been unclear if this ability would be transferable to proteins of unknown function, which may show distinct biases compared to experimentally more tractable proteins...
  3. pmc Automatic generation of 3D motifs for classification of protein binding sites
    Jean Christophe Nebel
    Faculty of Computing, Information Systems and Mathematics, Kingston University, Kingston upon Thames, KT1 2EE, UK
    BMC Bioinformatics 8:321. 2007
    ..In this paper, we report a method to automatically generate 3D motifs of protein structure binding sites based on consensus atom positions and evaluate it on a set of adenine based ligands...
  4. ncbi A lock-and-key model for protein-protein interactions
    Julie L Morrison
    Bioinformatics Research Centre, Department of Computing Science, University of Glasgow G12 8QQ, UK
    Bioinformatics 22:2012-9. 2006
    ....
  5. pmc Computational modelling of the receptor-tyrosine-kinase-activated MAPK pathway
    Richard J Orton
    Bioinformatics Research Centre, Department of Computing Science, University of Glasgow, Glasgow G12 8QQ, Scotland, UK
    Biochem J 392:249-61. 2005
    ..Focusing on the MAPK pathway, we introduce the features and functions of the pathway itself before comparing the available models and describing what new biological insights they have led to...
  6. pmc GeneRank: using search engine technology for the analysis of microarray experiments
    Julie L Morrison
    Bioinformatics Research Centre, University of Glasgow, Glasgow, UK
    BMC Bioinformatics 6:233. 2005
    ..Here we evaluate a method--based on the PageRank algorithm employed by the popular search engine Google--that tries to automate some of this procedure to generate prioritized gene lists by exploiting biological background information...