Andrew Kernytsky

Summary

Affiliation: Columbia University
Country: USA

Publications

  1. ncbi Static benchmarking of membrane helix predictions
    Andrew Kernytsky
    CUBIC, Department of Biochemistry and Molecular Biophysics, Columbia University, 650 West 168th Street BB217, New York, NY 10032, USA
    Nucleic Acids Res 31:3642-4. 2003
  2. ncbi Using genetic algorithms to select most predictive protein features
    Andrew Kernytsky
    Department of Biochemistry and Molecular Biophysics, Columbia University, New York 10032, New York, USA
    Proteins 75:75-88. 2009
  3. ncbi Transmembrane helix predictions revisited
    Chien Peter Chen
    Department of Biochemistry and Molecular Biophysics, Columbia University, New York, New York 10032, USA
    Protein Sci 11:2774-91. 2002
  4. ncbi Membrane protein prediction methods
    Marco Punta
    Department of Biochemistry and Molecular Biophysics, Columbia University, 1130 St Nicholas Ave, New York, NY 10032, USA
    Methods 41:460-74. 2007
  5. 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

Collaborators

Detail Information

Publications5

  1. ncbi Static benchmarking of membrane helix predictions
    Andrew Kernytsky
    CUBIC, Department of Biochemistry and Molecular Biophysics, Columbia University, 650 West 168th Street BB217, New York, NY 10032, USA
    Nucleic Acids Res 31:3642-4. 2003
    ..An additional feature is that developers can directly investigate any hydrophobicity scale for its potential in predicting membrane helices...
  2. ncbi Using genetic algorithms to select most predictive protein features
    Andrew Kernytsky
    Department of Biochemistry and Molecular Biophysics, Columbia University, New York 10032, New York, USA
    Proteins 75:75-88. 2009
    ..The final framework manages to effectively sample a feature space that is far too large for exhaustive enumeration. We demonstrate the power of the concept by applying it to prediction of protein enzymatic activity...
  3. ncbi Transmembrane helix predictions revisited
    Chien Peter Chen
    Department of Biochemistry and Molecular Biophysics, Columbia University, New York, New York 10032, USA
    Protein Sci 11:2774-91. 2002
    ..Overall, by establishing a standardized methodology for transmembrane helix prediction evaluation, we have resolved differences among previous works and presented novel trends that may impact the analysis of entire proteomes...
  4. ncbi Membrane protein prediction methods
    Marco Punta
    Department of Biochemistry and Molecular Biophysics, Columbia University, 1130 St Nicholas Ave, New York, NY 10032, USA
    Methods 41:460-74. 2007
    ....
  5. 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...