Avner Schlessinger

Summary

Affiliation: Columbia University
Country: USA

Publications

  1. ncbi Epitome: database of structure-inferred antigenic epitopes
    Avner Schlessinger
    CUBIC, Department of Biochemistry and Molecular Biophysics, Columbia University, 1130 St Nicholas Avenue, Room 804, New York, NY 10032, USA
    Nucleic Acids Res 34:D777-80. 2006
  2. ncbi Natively unstructured loops differ from other loops
    Avner Schlessinger
    Department of Biochemistry and Molecular Biophysics, Columbia University, New York, New York, USA
    PLoS Comput Biol 3:e140. 2007
  3. ncbi Natively unstructured regions in proteins identified from contact predictions
    Avner Schlessinger
    Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY, USA
    Bioinformatics 23:2376-84. 2007
  4. ncbi Improved disorder prediction by combination of orthogonal approaches
    Avner Schlessinger
    CUBIC, Department of Biochemistry and Molecular Biophysics, Columbia University, New York, New York, United States of America
    PLoS ONE 4:e4433. 2009
  5. ncbi PROFbval: predict flexible and rigid residues in proteins
    Avner Schlessinger
    CUBIC, Department of Biochemistry and Molecular Biophysics, Columbia University, 650 West 168th Street BB217, New York, NY 10032, USA
    Bioinformatics 22:891-3. 2006
  6. ncbi Protein secondary structure appears to be robust under in silico evolution while protein disorder appears not to be
    Christian Schaefer
    Department of Biochemistry and Molecular Biophysics, Center for Computational Biology and Bioinformatics C2B2, Columbia University, 1130 St Nicholas Ave, New York, NY 10032, USA
    Bioinformatics 26:625-31. 2010
  7. ncbi Protein flexibility and rigidity predicted from sequence
    Avner Schlessinger
    CUBIC, Department of Biochemistry and Molecular Biophysics, Columbia University, New York, New York 10032, USA
    Proteins 61:115-26. 2005
  8. ncbi Using multiple structure alignments, fast model building, and energetic analysis in fold recognition and homology modeling
    Donald Petrey
    Howard Hughes Medical Institute, Department of Biochemistry and Molecular Biophysics, Center for Computational Biology and Bioinformatics, Columbia University New York, New York 10032, USA
    Proteins 53:430-5. 2003
  9. ncbi Towards a consensus on datasets and evaluation metrics for developing B-cell epitope prediction tools
    Jason A Greenbaum
    Immune Epitope Database and Analysis Resource IEDB, La Jolla Institute for Allergy and Immunology, La Jolla, California, USA
    J Mol Recognit 20:75-82. 2007

Collaborators

Detail Information

Publications9

  1. ncbi Epitome: database of structure-inferred antigenic epitopes
    Avner Schlessinger
    CUBIC, Department of Biochemistry and Molecular Biophysics, Columbia University, 1130 St Nicholas Avenue, Room 804, New York, NY 10032, USA
    Nucleic Acids Res 34:D777-80. 2006
    ..Interactions can be visualized using an interface to Jmol. The database is available at http://www.rostlab.org/services/epitome/...
  2. ncbi Natively unstructured loops differ from other loops
    Avner Schlessinger
    Department of Biochemistry and Molecular Biophysics, Columbia University, New York, New York, USA
    PLoS Comput Biol 3:e140. 2007
    ..The comparative analysis between NORSnet and DISOPRED2 suggested that long unstructured loops are a major part of unstructured regions in molecular networks...
  3. ncbi Natively unstructured regions in proteins identified from contact predictions
    Avner Schlessinger
    Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY, USA
    Bioinformatics 23:2376-84. 2007
    ..Low propensity for the formation of internal residue contacts has been previously used to predict natively unstructured regions...
  4. ncbi Improved disorder prediction by combination of orthogonal approaches
    Avner Schlessinger
    CUBIC, Department of Biochemistry and Molecular Biophysics, Columbia University, New York, New York, United States of America
    PLoS ONE 4:e4433. 2009
    ..In sustained cross-validation, MD not only outperforms its origins, but it also compares favorably to other state-of-the-art prediction methods in a variety of tests that we applied. Availability: http://www.rostlab.org/services/md/..
  5. ncbi PROFbval: predict flexible and rigid residues in proteins
    Avner Schlessinger
    CUBIC, Department of Biochemistry and Molecular Biophysics, Columbia University, 650 West 168th Street BB217, New York, NY 10032, USA
    Bioinformatics 22:891-3. 2006
    ..AVAILABILITY: http://www.rostlab.org/services/profbval CONTACT: profbval@rostlab.org SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online...
  6. ncbi Protein secondary structure appears to be robust under in silico evolution while protein disorder appears not to be
    Christian Schaefer
    Department of Biochemistry and Molecular Biophysics, Center for Computational Biology and Bioinformatics C2B2, Columbia University, 1130 St Nicholas Ave, New York, NY 10032, USA
    Bioinformatics 26:625-31. 2010
    ..Put differently, helices and strands appear to be maintained easily by evolution, whereas maintaining disordered regions appears difficult. Neutral mutations with respect to disorder are therefore very unlikely...
  7. ncbi Protein flexibility and rigidity predicted from sequence
    Avner Schlessinger
    CUBIC, Department of Biochemistry and Molecular Biophysics, Columbia University, New York, New York 10032, USA
    Proteins 61:115-26. 2005
    ..Our method had not been set up to address any of the tasks in those 4 case studies. Therefore, we expect that this method will assist in many attempts at inferring aspects of function...
  8. ncbi Using multiple structure alignments, fast model building, and energetic analysis in fold recognition and homology modeling
    Donald Petrey
    Howard Hughes Medical Institute, Department of Biochemistry and Molecular Biophysics, Center for Computational Biology and Bioinformatics, Columbia University New York, New York 10032, USA
    Proteins 53:430-5. 2003
    ..This interactive model building procedure has several advantages and suggests important ways in which our and other methods can be improved, examples of which are provided...
  9. ncbi Towards a consensus on datasets and evaluation metrics for developing B-cell epitope prediction tools
    Jason A Greenbaum
    Immune Epitope Database and Analysis Resource IEDB, La Jolla Institute for Allergy and Immunology, La Jolla, California, USA
    J Mol Recognit 20:75-82. 2007
    ..By developing common datasets, standardized data formats, and the means with which to consolidate information, we hope to greatly enhance the development of B-cell epitope prediction tools...