Andrea Sboner

Summary

Affiliation: Yale University
Country: USA

Publications

  1. pmc Molecular sampling of prostate cancer: a dilemma for predicting disease progression
    Andrea Sboner
    Department of Pathology and Laboratory Medicine, Weill Cornell Medical Center, New York, NY, USA
    BMC Med Genomics 3:8. 2010
  2. pmc FusionSeq: a modular framework for finding gene fusions by analyzing paired-end RNA-sequencing data
    Andrea Sboner
    Program in Computational Biology and Bioinformatics, Yale University, 300 George Street, New Haven, CT 06511, USA
    Genome Biol 11:R104. 2010
  3. pmc VAT: a computational framework to functionally annotate variants in personal genomes within a cloud-computing environment
    Lukas Habegger
    Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
    Bioinformatics 28:2267-9. 2012
  4. pmc RSEQtools: a modular framework to analyze RNA-Seq data using compact, anonymized data summaries
    Lukas Habegger
    Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA
    Bioinformatics 27:281-3. 2011
  5. pmc IQSeq: integrated isoform quantification analysis based on next-generation sequencing
    Jiang Du
    Department of Computer Science, Yale University, New Haven, Connecticut, United States of America
    PLoS ONE 7:e29175. 2012
  6. pmc Genomics and privacy: implications of the new reality of closed data for the field
    Dov Greenbaum
    Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut, USA
    PLoS Comput Biol 7:e1002278. 2011
  7. pmc The real cost of sequencing: higher than you think!
    Andrea Sboner
    Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
    Genome Biol 12:125. 2011
  8. pmc Integrative analysis of the Caenorhabditis elegans genome by the modENCODE project
    Mark B Gerstein
    Program in Computational Biology and Bioinformatics, Yale University, Bass 432, 266 Whitney Avenue, New Haven, CT 06520, USA
    Science 330:1775-87. 2010
  9. pmc Comparison and calibration of transcriptome data from RNA-Seq and tiling arrays
    Ashish Agarwal
    Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
    BMC Genomics 11:383. 2010

Detail Information

Publications9

  1. pmc Molecular sampling of prostate cancer: a dilemma for predicting disease progression
    Andrea Sboner
    Department of Pathology and Laboratory Medicine, Weill Cornell Medical Center, New York, NY, USA
    BMC Med Genomics 3:8. 2010
    ..Hence, we sought to develop a molecular panel for prostate cancer progression by reasoning that molecular profiles might further improve current clinical models...
  2. pmc FusionSeq: a modular framework for finding gene fusions by analyzing paired-end RNA-sequencing data
    Andrea Sboner
    Program in Computational Biology and Bioinformatics, Yale University, 300 George Street, New Haven, CT 06511, USA
    Genome Biol 11:R104. 2010
    ..It also has a module to identify exact sequences at breakpoint junctions. FusionSeq detected known and novel fusions in a specially sequenced calibration data set, including eight cancers with and without known rearrangements...
  3. pmc VAT: a computational framework to functionally annotate variants in personal genomes within a cloud-computing environment
    Lukas Habegger
    Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
    Bioinformatics 28:2267-9. 2012
    ..Finally, in order to enable on-demand access and to minimize unnecessary transfers of large data files, VAT can be run as a virtual machine in a cloud-computing environment...
  4. pmc RSEQtools: a modular framework to analyze RNA-Seq data using compact, anonymized data summaries
    Lukas Habegger
    Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA
    Bioinformatics 27:281-3. 2011
    ..Availability and implementation: RSEQtools is implemented in C and the source code is available at http://rseqtools.gersteinlab.org/...
  5. pmc IQSeq: integrated isoform quantification analysis based on next-generation sequencing
    Jiang Du
    Department of Computer Science, Yale University, New Haven, Connecticut, United States of America
    PLoS ONE 7:e29175. 2012
    ..This allows one to have a modular, "plugin-able" read-generation function to support the particularities of the many evolving sequencing technologies...
  6. pmc Genomics and privacy: implications of the new reality of closed data for the field
    Dov Greenbaum
    Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut, USA
    PLoS Comput Biol 7:e1002278. 2011
    ..However, teaching personal genomics with identifiable subjects in the university setting will, in turn, create additional privacy issues and social conundrums...
  7. pmc The real cost of sequencing: higher than you think!
    Andrea Sboner
    Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
    Genome Biol 12:125. 2011
    ..Advances in sequencing technology have led to a sharp decrease in the cost of 'data generation'. But is this sufficient to ensure cost-effective and efficient 'knowledge generation'?..
  8. pmc Integrative analysis of the Caenorhabditis elegans genome by the modENCODE project
    Mark B Gerstein
    Program in Computational Biology and Bioinformatics, Yale University, Bass 432, 266 Whitney Avenue, New Haven, CT 06520, USA
    Science 330:1775-87. 2010
    ..Integrating data types, we built statistical models relating chromatin, transcription factor binding, and gene expression. Overall, our analyses ascribed putative functions to most of the conserved genome...
  9. pmc Comparison and calibration of transcriptome data from RNA-Seq and tiling arrays
    Ashish Agarwal
    Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
    BMC Genomics 11:383. 2010
    ..Understanding the relative merits of these technologies will help researchers select the appropriate technology for their needs...