Liam J McGuffin

Summary

Affiliation: University of Reading
Country: UK

Publications

  1. ncbi Intrinsic disorder prediction from the analysis of multiple protein fold recognition models
    Liam J McGuffin
    School of Biological Sciences, University of Reading, Whiteknights, Reading RG6 6AS, UK
    Bioinformatics 24:1798-804. 2008
  2. ncbi FunFOLD: an improved automated method for the prediction of ligand binding residues using 3D models of proteins
    Daniel B Roche
    School of Biological Sciences, University of Reading, Whiteknights, Reading, UK
    BMC Bioinformatics 12:160. 2011
  3. ncbi The IntFOLD server: an integrated web resource for protein fold recognition, 3D model quality assessment, intrinsic disorder prediction, domain prediction and ligand binding site prediction
    Daniel B Roche
    School of Biological Sciences, University of Reading, Whiteknights, Reading RG6 6AS, UK
    Nucleic Acids Res 39:W171-6. 2011
  4. ncbi Automated tertiary structure prediction with accurate local model quality assessment using the intfold-ts method
    Liam J McGuffin
    School of Biological Sciences, University of Reading, Whiteknights, Reading RG6 6AS, United Kingdom
    Proteins 79:137-46. 2011
  5. ncbi Rapid model quality assessment for protein structure predictions using the comparison of multiple models without structural alignments
    Liam J McGuffin
    School of Biological Sciences, University of Reading, Whiteknights, Reading RG6 6AS, UK
    Bioinformatics 26:182-8. 2010
  6. ncbi Benchmarking consensus model quality assessment for protein fold recognition
    Liam J McGuffin
    The School of Biological Sciences, University of Reading, Whiteknights, Reading RG6 6AS, UK
    BMC Bioinformatics 8:345. 2007
  7. ncbi Prediction of global and local model quality in CASP8 using the ModFOLD server
    Liam J McGuffin
    School of Biological Sciences, University of Reading Whiteknights, Reading RG6 6AS, United Kingdom
    Proteins 77:185-90. 2009
  8. ncbi The binding site distance test score: a robust method for the assessment of predicted protein binding sites
    Daniel B Roche
    School of Biological Sciences, University of Reading, Whiteknights, Reading RG6 6AS, UK
    Bioinformatics 26:2920-1. 2010
  9. ncbi High throughput profile-profile based fold recognition for the entire human proteome
    Liam J McGuffin
    The Biocentre, University of Reading, Whiteknights, PO Box 221, Reading RG6 6AS, UK
    BMC Bioinformatics 7:288. 2006
  10. ncbi The ModFOLD server for the quality assessment of protein structural models
    Liam J McGuffin
    School of Biological Sciences, University of Reading, Whiteknights, Reading RG6 6AS, UK
    Bioinformatics 24:586-7. 2008

Collaborators

  • David T Jones
  • Russell L Marsden
  • Daniel B Roche
  • Stuart J Tetchner
  • Kevin Bryson
  • Jonathan J Ward
  • Chris S Pettitt
  • Jaspreet Singh Sodhi
  • Maria T Buenavista
  • Jaspreet S Sodhi
  • Lorenz Wernisch
  • Bernard F Buxton

Detail Information

Publications21

  1. ncbi Intrinsic disorder prediction from the analysis of multiple protein fold recognition models
    Liam J McGuffin
    School of Biological Sciences, University of Reading, Whiteknights, Reading RG6 6AS, UK
    Bioinformatics 24:1798-804. 2008
    ..The DISOclust method is rigorously benchmarked against the top.ve methods from the CASP7 experiment. In addition, the optimal consensus of the tested methods is determined and the added value from each method is quantified...
  2. ncbi FunFOLD: an improved automated method for the prediction of ligand binding residues using 3D models of proteins
    Daniel B Roche
    School of Biological Sciences, University of Reading, Whiteknights, Reading, UK
    BMC Bioinformatics 12:160. 2011
    ..A simple web interface is also provided allowing access to non-expert users. The method has been benchmarked against the top servers and manual prediction groups tested at both CASP8 and CASP9...
  3. ncbi The IntFOLD server: an integrated web resource for protein fold recognition, 3D model quality assessment, intrinsic disorder prediction, domain prediction and ligand binding site prediction
    Daniel B Roche
    School of Biological Sciences, University of Reading, Whiteknights, Reading RG6 6AS, UK
    Nucleic Acids Res 39:W171-6. 2011
    ..Predictions from the IntFOLD server were found to be competitive in several categories in the recent CASP9 experiment. The IntFOLD server is available at the following web site: http://www.reading.ac.uk/bioinf/IntFOLD/...
  4. ncbi Automated tertiary structure prediction with accurate local model quality assessment using the intfold-ts method
    Liam J McGuffin
    School of Biological Sciences, University of Reading, Whiteknights, Reading RG6 6AS, United Kingdom
    Proteins 79:137-46. 2011
    ..This important information may help to make the 3D models that are produced by the IntFOLD-TS method more useful for guiding future experimental work. Proteins 2011; © 2011 Wiley-Liss, Inc...
  5. ncbi Rapid model quality assessment for protein structure predictions using the comparison of multiple models without structural alignments
    Liam J McGuffin
    School of Biological Sciences, University of Reading, Whiteknights, Reading RG6 6AS, UK
    Bioinformatics 26:182-8. 2010
    ..In addition, the ModFOLDclustQ scores are combined with those from our older ModFOLDclust method to form a new method, ModFOLDclust2, that aims to provide increased prediction accuracy with negligible computational overhead...
  6. ncbi Benchmarking consensus model quality assessment for protein fold recognition
    Liam J McGuffin
    The School of Biological Sciences, University of Reading, Whiteknights, Reading RG6 6AS, UK
    BMC Bioinformatics 8:345. 2007
    ..Two novel methods are also described: ModSSEA, which based on the alignment of predicted secondary structure elements and ModFOLD which combines several true MQAP methods using an artificial neural network...
  7. ncbi Prediction of global and local model quality in CASP8 using the ModFOLD server
    Liam J McGuffin
    School of Biological Sciences, University of Reading Whiteknights, Reading RG6 6AS, United Kingdom
    Proteins 77:185-90. 2009
    ..All of the MQAPs described are publicly accessible via the ModFOLD server at: http://www.reading.ac.uk/bioinf/ModFOLD/. The methods are also freely available to download from: http://www.reading.ac.uk/bioinf/downloads/...
  8. ncbi The binding site distance test score: a robust method for the assessment of predicted protein binding sites
    Daniel B Roche
    School of Biological Sciences, University of Reading, Whiteknights, Reading RG6 6AS, UK
    Bioinformatics 26:2920-1. 2010
    ..We therefore suggest that this new simple score is a potentially more robust method for future evaluations of protein-ligand binding site predictions. AVAILABILITY: http://www.reading.ac.uk/bioinf/downloads/...
  9. ncbi High throughput profile-profile based fold recognition for the entire human proteome
    Liam J McGuffin
    The Biocentre, University of Reading, Whiteknights, PO Box 221, Reading RG6 6AS, UK
    BMC Bioinformatics 7:288. 2006
    ..We use the most recent profile-profile version of our mGenTHREADER software in order to annotate the latest version of the Human proteome against the latest sequence and structure databases in as short a time as possible...
  10. ncbi The ModFOLD server for the quality assessment of protein structural models
    Liam J McGuffin
    School of Biological Sciences, University of Reading, Whiteknights, Reading RG6 6AS, UK
    Bioinformatics 24:586-7. 2008
    ..Secondly ModFOLDclust, which is a more intensive method that carries out clustering of multiple models and provides per-residue local quality assessment. AVAILABILITY: http://www.biocentre.rdg.ac.uk/bioinformatics/ModFOLD/...
  11. ncbi Protein structure prediction servers at University College London
    Kevin Bryson
    Department of Computer Science, University College London Gower Street, London WC1E 6BT, UK
    Nucleic Acids Res 33:W36-8. 2005
    ..More recent servers include DISOPRED for the prediction of protein dynamic disorder and DomPred for domain boundary prediction. These servers are available from our software home page at http://bioinf.cs.ucl.ac.uk/software.html...
  12. ncbi Improving sequence-based fold recognition by using 3D model quality assessment
    Chris S Pettitt
    Bioinformatics Unit, Department of Computer Science, University College London, Gower Street, London WC1E 6BT, UK
    Bioinformatics 21:3509-15. 2005
    ..This suggests that even the best sequence-based fold recognition methods can still be improved by taking into account the 3D structural information. CONTACT: ..
  13. ncbi Rapid protein domain assignment from amino acid sequence using predicted secondary structure
    Russell L Marsden
    Bioinformatics Unit, Department of Computer Science, University College London, UK
    Protein Sci 11:2814-24. 2002
    ..These results have been put into context in relation to the results obtained from the other prediction methods assessed...
  14. ncbi Improvement of the GenTHREADER method for genomic fold recognition
    Liam J McGuffin
    Bioinformatics Group, Department of Computer Science, University College London, Gower Street, UK
    Bioinformatics 19:874-81. 2003
    ..The neural network has also been expanded to accommodate the secondary structure element alignment (SSEA) score as an extra input and it is now trained to learn the FSSP Z-score as a measurement of similarity between two proteins...
  15. ncbi Benchmarking secondary structure prediction for fold recognition
    Liam J McGuffin
    Bioinformatics Unit, Department of Computer Science, University College London, London, United Kingdom
    Proteins 52:166-75. 2003
    ....
  16. ncbi Assembling novel protein folds from super-secondary structural fragments
    David T Jones
    Department of Computer Science, Bioinformatics Unit, University College London, London, United Kingdom
    Proteins 53:480-5. 2003
    ..Although clear progress has been made in improving FRAGFOLD since CASP4, the ranking of final models still seems to be the main problem that needs to be addressed before the next CASP experiment...
  17. ncbi The Genomic Threading Database: a comprehensive resource for structural annotations of the genomes from key organisms
    Liam J McGuffin
    Department of Computer Science, University College London, Gower Street, London WC1E 6BT, UK
    Nucleic Acids Res 32:D196-9. 2004
    ..On average in the GTD, 64% of proteins encoded within a genome are confidently assigned to known folds and 58% of the residues are aligned to structures...
  18. ncbi The genomic threading database
    Liam J McGuffin
    Department of Computer Science, University College London, Gower Street, London WC1E 6BT, UK
    Bioinformatics 20:131-2. 2004
    ..Annotations are carried out by using our modified GenTHREADER software and through implementing grid technology. AVAILABILITY: http://bioinf.cs.ucl.ac.uk/GTD..
  19. ncbi The DISOPRED server for the prediction of protein disorder
    Jonathan J Ward
    Bioinformatics Group, Department of Computer Science, University College London, Gower Street, London, WC1E 6BT, UK
    Bioinformatics 20:2138-9. 2004
    ..AVAILABILITY: The server can be accessed by non-commercial users at http://bioinf.cs.ucl.ac.uk/disopred/..
  20. ncbi Targeting novel folds for structural genomics
    Liam J McGuffin
    Institute of Cancer Genetics and Pharmacogenomics, Department of Biological Sciences, Brunel University, Uxbridge, Middlesex, United Kingdom
    Proteins 48:44-52. 2002
    ....
  21. ncbi Predicting metal-binding site residues in low-resolution structural models
    Jaspreet Singh Sodhi
    Bioinformatics Unit, Department of Computer Science, University College London, Gower Street, WC1E 6BT, UK
    J Mol Biol 342:307-20. 2004
    ..High-scoring predictions were observed for a recently solved hypothetical protein from Haemophilus influenzae, indicating a putative metal-binding site...