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After exposure to high energy, high LET particles where the track radius is much larger than the cell nucleus, best fits to the data were achieved by a convoluted Poisson Neyman statistics.
The population genetic data were achieved by RFLP analysis of the amplified pmt fragments by PCR (Janssens unpublished).
High resolution and high reproducibility of the obtained biological data were achieved by application of an automated electrophoresis system (Shimadzu, Japan).
The best results for BS prediction in ChIP-Seq data were achieved by model combinations, e.g. SiteGA plus diChIPMunk, successfully identifying up to 90% of FoxA BS-containing loci in both the mouse and human ChIP-Seq data.
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A good match with the actual data was achieved by developing the RSM and ANFIS models.
Secondly, the residual and precise focusing of the synthetic aperture radar data is achieved by applying the range migration algorithm.
They also showed that since the Rician factor strongly depends on the environment, a better fit to the measurement data was achieved by applying a double Rayleigh distribution.
Our results show that the best correlation with the measured pressure data is achieved by the modified Eaton method with Eaton׳s exponent of about 0.5.
Our findings further demonstrate that the 'optimal' model fit to the data was achieved by shortening the odorant 'ON' period to approximately 6 s.
Modeling of the relationship between selected descriptors and solubility data was achieved by linear (multiple linear regression; MLR) and nonlinear (artificial neural network; ANN) methods.
A more detailed analysis of the data is achieved by systematically mining the network for SAR pathways, i.e. sequences of pairwise similar compounds that connect two molecules via a gradually increasing potency gradient.
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