GOSA, a simulated annealing-based program for global optimization of nonlinear problems, also reveals transyears

Abstract

Transyears in biology have been documented thus far by the extended cosinor approach, including linearnonlinear rhythmometry. We here confirm the existence of transyears by simulated annealing, a method originally developed for a much broader use, but described and introduced herein for validating its application to time series. The method is illustrated both on an artificial test case with known components and on biological data. We provide a table comparing results by the two methods and trust that the procedure will serve the budding sciences of chronobiology (the study of mechanisms underlying biological time structure), chronomics (the mapping of time structures in and around us), and chronobioethics, using the foregoing disciplines to add to concern for illnesses of individuals also a budding focus on diseases of societies, like crime, and of nations and civilizations, like war.

Structural determinants of specific DNA-recognition by the THAP zinc finger

“…This cross-saturation transfer period was introduced prior to the classical 1 H- 15 N HSQC sequence as previously described ( 21 ). The 2D 1 H- 15 N HSQC experiments were recorded with different saturation periods up to 1.8 s. The peak intensities were extracted from the 2D 1 H- 15 N HSQC spectra using NMRView ( 19 ) and analyzed using GOSA ( 22 ).…”

“…To study the influence of the ionic strength on the non-specific binding, samples with different protein:DNA ratios ranging from 1:0 to 1:6 were initially prepared in 250 mM NaCl (100 µl of THAP zinc finger at 3 µM) and were then exchanged in buffer containing suitable NaCl concentrations (30 or 150 mM). Fluorescence anisotropy was calculated including a correction factor as previously described ( 27 ) and the data were fitted from a previously described equation ( 28 ) using a non-linear fit with GOSA software ( 22 ).…”

Procedures for numerical analysis of circadian rhythms

“…Alternatively, a combined linear -nonlinear procedure based on the cosinor method has been proposed for the resolution of neighboring components in physiological data and has been shown to successfully resolve components of 24.0 h and 24.8 h (Halberg 1980;Rummel et al 1974), as noted in Table II. The procedure of simulated annealing, originally developed for the solution of optimization problems in complex nonlinear systems (Cerny 1985;Kirkpatrick et al 1983), can also resolve the two components (Czaplicki et al 2006). Likewise, maximum entropy spectral analysis (MESA) has been shown to resolve 24.0-h and 24.8-h components in an artificial data set with 80% added random noise (Dowse & Ringo 1991), as it was with the extended linear-nonlinear cosinor (Halberg 1980;Rummel et al 1974).…”

Circadian Rhythm Analysis Using Wearable Device Data: A Novel Penalized Machine Learning Approach

“…One has to either start from an initial guess and use iterative procedures to minimize residual sum of squares or use simulated annealing alternatively to fit the model, the process of which can be exhaustive. [29][30][31] In comparison, without prior knowledge on dominant periods, the PML algorithm based on shrinkage in machine learning is still easy to implement without computational burden in extracting periodic information and the results are as effective as the cosinor model to characterize daily activity patterns using cosine curves.…”