Regularization Techniques for Inverse Problems in Molecular Biology

  • Stephen W. Provencher
  • Robert H. Vogel
Part of the Progress in Scientific Computing book series (PSC, volume 2)


In molecular biology, as in most natural sciences, the number of indirect experiments involving ill-posed inverse problems is rapidly increasing. Three of the most important types of inverse problems involve either (a) severely ill-posed linear problems (e.g., Laplace transforms in relaxation or correlation experiments); (b) very large, and perhaps nonlinear, problems (e.g., estimation of three-dimensional structure from x-ray diffraction or electron microscopy); or (c) parameter estimation involving computationally complex models (e.g., multicomponent subnanosecond fluorescence decay strongly convoluted with the instrument response or excitation function).


Tilt Angle Spherical Harmonic Computer Assisted Tomography Limited Angular Range Prior Statistical Knowledge 
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Copyright information

© Birkhäuser Boston 1983

Authors and Affiliations

  • Stephen W. Provencher
  • Robert H. Vogel

There are no affiliations available

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