Sampsa Hautaniemi

Summary

Affiliation: Massachusetts Institute of Technology
Country: USA

Publications

  1. ncbi Optimized LOWESS normalization parameter selection for DNA microarray data
    John A Berger
    Department of Electrical and Computer Engineering, University of California, Santa Barbara, CA 93106 9560, USA
    BMC Bioinformatics 5:194. 2004
  2. ncbi Therapeutic targets for HIV-1 infection in the host proteome
    Winnie S Liang
    Neurogenomics Division, Translational Genomics Research Institute, Phoenix, AZ 85004, USA
    Retrovirology 2:20. 2005
  3. ncbi Modeling of signal-response cascades using decision tree analysis
    Sampsa Hautaniemi
    Biological Engineering Division, Massachusetts Institute of Technology, Cambridge, 02139, USA
    Bioinformatics 21:2027-35. 2005
  4. ncbi Multiple reaction monitoring for robust quantitative proteomic analysis of cellular signaling networks
    Alejandro Wolf-Yadlin
    Biological Engineering Division, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
    Proc Natl Acad Sci U S A 104:5860-5. 2007
  5. ncbi Effects of HER2 overexpression on cell signaling networks governing proliferation and migration
    Alejandro Wolf-Yadlin
    Biological Engineering Division, MIT, Cambridge, MA, USA
    Mol Syst Biol 2:54. 2006
  6. ncbi Integrated mechanistic and data-driven modelling for multivariate analysis of signalling pathways
    Fei Hua
    Biological Engineering Division, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
    J R Soc Interface 3:515-26. 2006
  7. ncbi Transcriptional profiling reflects shared and unique characters for CD34+ and CD133+ cells
    Heidi Hemmoranta
    Research and Development, Finnish Red Cross Blood Service, Helsinki, Finland
    Stem Cells Dev 15:839-51. 2006
  8. ncbi A novel strategy for microarray quality control using Bayesian networks
    Sampsa Hautaniemi
    Institute of Signal Processing, Tampere University of Technology, PO Box 553, 33101 Tampere, Finland
    Bioinformatics 19:2031-8. 2003
  9. ncbi Global gene expression profile of human cord blood-derived CD133+ cells
    Taina Jaatinen
    Finnish Red Cross Blood Service, Kivihaantie 7, 00310 Helsinki, Finland
    Stem Cells 24:631-41. 2006
  10. ncbi Decision tree modeling predicts effects of inhibiting contractility signaling on cell motility
    Sourabh Kharait
    Department of Pathology, University of Pittsburgh, Pittsburgh, PA 15213, USA
    BMC Syst Biol 1:9. 2007

Collaborators

  • Yi Zhang
  • Sourabh Kharait
  • Alan Wells
  • Neil Kumar
  • Fei Hua
  • Douglas Lauffenburger
  • Alejandro Wolf-Yadlin
  • Taina Jaatinen
  • Heidi Hemmoranta
  • Forest M White
  • Jarmo Laine
  • Daniel Nicorici
  • Jukka Partanen
  • Olli Yli-Harja
  • Jari Niemi
  • Winnie S Liang
  • John A Berger
  • Hyung-Do Kim
  • Muhammad Zaman
  • Viara Grantcharova
  • Hyung Do Kim
  • Tanya M Teslovich
  • Dietrich A Stephan
  • Shabnam Dadgar
  • Cynthia de La Fuente
  • Anil Maddukuri
  • Kylene Kehn
  • Emmanuel Agbottah
  • Anne Pumfery
  • Fatah Kashanchi
  • Sanjit K Mitra
  • Jaakko Astola
  • Henrik Edgren
  • Anna Kaarina Järvinen

Detail Information

Publications10

  1. ncbi Optimized LOWESS normalization parameter selection for DNA microarray data
    John A Berger
    Department of Electrical and Computer Engineering, University of California, Santa Barbara, CA 93106 9560, USA
    BMC Bioinformatics 5:194. 2004
    ..Parameters are usually chosen arbitrarily, which may reduce the efficiency of the normalization and result in non-optimally normalized data. Thus, there is a need to explore LOWESS parameter selection in greater detail...
  2. ncbi Therapeutic targets for HIV-1 infection in the host proteome
    Winnie S Liang
    Neurogenomics Division, Translational Genomics Research Institute, Phoenix, AZ 85004, USA
    Retrovirology 2:20. 2005
    ..Therefore, to identify cellular proteins that may be up-regulated in HIV infection and play a role in infection, we analyzed the effects of Tat on cellular gene expression during various phases of the cell cycle...
  3. ncbi Modeling of signal-response cascades using decision tree analysis
    Sampsa Hautaniemi
    Biological Engineering Division, Massachusetts Institute of Technology, Cambridge, 02139, USA
    Bioinformatics 21:2027-35. 2005
    ..we conclude that decision tree methodology may facilitate elucidation of signal-response cascade relationships and generate experimentally testable predictions, which can be used as directions for future experiments...
  4. ncbi Multiple reaction monitoring for robust quantitative proteomic analysis of cellular signaling networks
    Alejandro Wolf-Yadlin
    Biological Engineering Division, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
    Proc Natl Acad Sci U S A 104:5860-5. 2007
    ..Using this approach, it should now be possible to routinely monitor the phosphorylation status of hundreds of nodes across multiple biological conditions...
  5. ncbi Effects of HER2 overexpression on cell signaling networks governing proliferation and migration
    Alejandro Wolf-Yadlin
    Biological Engineering Division, MIT, Cambridge, MA, USA
    Mol Syst Biol 2:54. 2006
    ..Combining these modeling approaches enabled association of epidermal growth factor receptor family dimerization to activation of specific phosphorylation sites, which appear to most critically regulate proliferation and/or migration...
  6. ncbi Integrated mechanistic and data-driven modelling for multivariate analysis of signalling pathways
    Fei Hua
    Biological Engineering Division, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
    J R Soc Interface 3:515-26. 2006
    ..In conclusion, our framework provides a novel approach to understand the multivariate dependencies among molecules in complex networks, and can potentially be used to identify combinatorial targets for therapeutic interventions...
  7. ncbi Transcriptional profiling reflects shared and unique characters for CD34+ and CD133+ cells
    Heidi Hemmoranta
    Research and Development, Finnish Red Cross Blood Service, Helsinki, Finland
    Stem Cells Dev 15:839-51. 2006
    ..These profiles suggest that CD34(+) and CD133(+) cells may have different roles in hematopoietic regeneration...
  8. ncbi A novel strategy for microarray quality control using Bayesian networks
    Sampsa Hautaniemi
    Institute of Signal Processing, Tampere University of Technology, PO Box 553, 33101 Tampere, Finland
    Bioinformatics 19:2031-8. 2003
    ..A typical microarray experiment consists of tens of thousands of spots on a microarray, making manual extraction of poor quality spots impossible. Thus, there is a need for a reliable and general microarray spot quality control strategy...
  9. ncbi Global gene expression profile of human cord blood-derived CD133+ cells
    Taina Jaatinen
    Finnish Red Cross Blood Service, Kivihaantie 7, 00310 Helsinki, Finland
    Stem Cells 24:631-41. 2006
    ..This study provides a gene expression profile for human CD133+ cells. It presents a set of genes that may be used to unravel the properties of the CD133+ cell population, assumed to be highly enriched in HSCs...
  10. ncbi Decision tree modeling predicts effects of inhibiting contractility signaling on cell motility
    Sourabh Kharait
    Department of Pathology, University of Pittsburgh, Pittsburgh, PA 15213, USA
    BMC Syst Biol 1:9. 2007
    ....