Document Detail

Reverse smoothing: a model-free data smoothing algorithm.
MedLine Citation:
PMID:  15043925     Owner:  NLM     Status:  MEDLINE    
Biophysical chemistry experiments, such as sedimentation-equilibrium analyses, require computational techniques to reduce the effects of random errors of the measurement process. The existing approaches have primarily relied on assumption of polynomial models and least-squares approximation. Such models by constraining the data to remove random fluctuations may distort the data and cause loss of information. The better the removal of random errors the greater is the likely introduction of systematic errors through the constraining fit itself. An alternative technique, reverse smoothing, is suggested that makes use of a more model-free approach of exponential smoothing of the first derivative. Exponential smoothing approaches have been generally unsatisfactory because they introduce significant data lag. The approaches given here compensates for the lag defect and appears promising for the smoothing of many experimental data sequences, including the macromolecular concentration data generated by sedimentation-equilibria experiments. Test results on simulated sedimentation-equilibrium data indicate that a 4-fold reduction in error may be typical over standard analyses techniques.
Dennis E Roark
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Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  Biophysical chemistry     Volume:  108     ISSN:  0301-4622     ISO Abbreviation:  Biophys. Chem.     Publication Date:  2004 Mar 
Date Detail:
Created Date:  2004-03-26     Completed Date:  2004-09-09     Revised Date:  2008-11-21    
Medline Journal Info:
Nlm Unique ID:  0403171     Medline TA:  Biophys Chem     Country:  Netherlands    
Other Details:
Languages:  eng     Pagination:  121-6     Citation Subset:  IM    
Department of Computer Science and Mathematics, University of Sioux Falls, 1101 W. 22nd Street, Sioux Falls, SD 57105, USA.
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MeSH Terms
Biophysical Phenomena
Data Interpretation, Statistical*
Least-Squares Analysis
Macromolecular Substances
Models, Statistical
Models, Theoretical
Reg. No./Substance:
0/Macromolecular Substances

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