Chiranjib Bhattacharyya

Summary

Country: India

Publications

  1. ncbi Robust sparse hyperplane classifiers: application to uncertain molecular profiling data
    C Bhattacharyya
    Department of EECS, University of California Berkeley, Berkeley, CA 94720, USA
    J Comput Biol 11:1073-89. 2004
  2. ncbi NETGEM: Network Embedded Temporal GEnerative Model for gene expression data
    Vinay Jethava
    Department of Computer Science and Engineering, Chalmers University ofTechnology, Goteborg, Sweden
    BMC Bioinformatics 12:327. 2011
  3. ncbi Comparison of protein structures by growing neighborhood alignments
    Sourangshu Bhattacharya
    Dept of Computer Science and Automation, Indian Institute of Science, Bangalore, India
    BMC Bioinformatics 8:77. 2007
  4. ncbi Projections for fast protein structure retrieval
    Sourangshu Bhattacharya
    Dept, of Computer Science and Automation, Indian Institute of Science, Bangalore 560012, India
    BMC Bioinformatics 7:S5. 2006
  5. ncbi A linear programming approach for estimating the structure of a sparse linear genetic network from transcript profiling data
    Sahely Bhadra
    Department of Computer Science and Automation, Indian Institute of Science, Bangalore, Karnataka, India
    Algorithms Mol Biol 4:5. 2009

Collaborators

  • Sourangshu Bhattacharya
  • Nagasuma R Chandra
  • Vinay Jethava
  • Sahely Bhadra
  • Goutham N Vemuri
  • Devdatt Dubhashi
  • I Saira Mian

Detail Information

Publications5

  1. ncbi Robust sparse hyperplane classifiers: application to uncertain molecular profiling data
    C Bhattacharyya
    Department of EECS, University of California Berkeley, Berkeley, CA 94720, USA
    J Comput Biol 11:1073-89. 2004
    ..The generalization performance of a specific implementation, designated "robust LIKNON," is better than its nominal counterpart. Finally, the strengths and limitations of robust sparse hyperplanes are discussed...
  2. ncbi NETGEM: Network Embedded Temporal GEnerative Model for gene expression data
    Vinay Jethava
    Department of Computer Science and Engineering, Chalmers University ofTechnology, Goteborg, Sweden
    BMC Bioinformatics 12:327. 2011
    ....
  3. ncbi Comparison of protein structures by growing neighborhood alignments
    Sourangshu Bhattacharya
    Dept of Computer Science and Automation, Indian Institute of Science, Bangalore, India
    BMC Bioinformatics 8:77. 2007
    ..A new method for computing equivalences having non-topological similarities from pairwise similarity score is described. A novel and fast technique for comparing sequence neighborhoods is also developed...
  4. ncbi Projections for fast protein structure retrieval
    Sourangshu Bhattacharya
    Dept, of Computer Science and Automation, Indian Institute of Science, Bangalore 560012, India
    BMC Bioinformatics 7:S5. 2006
    ..The algorithm is also capable of detecting non-topological similarities between two proteins which is not possible with most of the state of the art tools like Dali...
  5. ncbi A linear programming approach for estimating the structure of a sparse linear genetic network from transcript profiling data
    Sahely Bhadra
    Department of Computer Science and Automation, Indian Institute of Science, Bangalore, Karnataka, India
    Algorithms Mol Biol 4:5. 2009
    ..The LP-based solutions of the sparse linear regression problem described here may provide a method for learning the structure of transcription factor networks from transcript profiling and transcription factor binding motif data...