A numerically efficient implementation of the expectation maximization algorithm for state space models

Peer reviewedPostprin

Least-squares methods for identifying biochemical regulatory networks from noisy measurements

<b>Background</b>: We consider the problem of identifying the dynamic interactions in biochemical networks from noisy experimental data. Typically, approaches for solving this problem make use of an estimation algorithm such as the well-known linear Least-Squares (LS) estimation technique. We demonstrate that when time-series measurements are corrupted by white noise and/or drift noise, more accurate and reliable identification of network interactions can be achieved by employing an estimation algorithm known as Constrained Total Least Squares (CTLS). The Total Least Squares (TLS) technique is a generalised least squares method to solve an overdetermined set of equations whose coefficients are noisy. The CTLS is a natural extension of TLS to the case where the noise components of the coefficients are correlated, as is usually the case with time-series measurements of concentrations and expression profiles in gene networks. <b>Results</b>: The superior performance of the CTLS method in identifying network interactions is demonstrated on three examples: a genetic network containing four genes, a network describing p53 activity and <i>mdm2</i> messenger RNA interactions, and a recently proposed kinetic model for interleukin (IL)-6 and (IL)-12b messenger RNA expression as a function of ATF3 and NF-κB promoter binding. For the first example, the CTLS significantly reduces the errors in the estimation of the Jacobian for the gene network. For the second, the CTLS reduces the errors from the measurements that are corrupted by white noise and the effect of neglected kinetics. For the third, it allows the correct identification, from noisy data, of the negative regulation of (IL)-6 and (IL)-12b by ATF3. <b>Conclusion</b>: The significant improvements in performance demonstrated by the CTLS method under the wide range of conditions tested here, including different levels and types of measurement noise and different numbers of data points, suggests that its application will enable more accurate and reliable identification and modelling of biochemical networks

A new list of thorium and argon spectral lines in the visible

Aims. We present a new list of thorium and argon emission lines in the visible obtained by analyzing high-resolution (R=110,000) spectra of a ThAr hollow cathode lamp. The aim of this new line list is to allow significant improvements in the quality of wavelength calibration for medium- to high-resolution astronomical spectrographs. Methods. We use a series of ThAr lamp exposures obtained with the HARPS instrument (High Accuracy Radial-velocity Planet Searcher) to detect previously unknown lines, perform a systematic search for blended lines and correct individual wavelengths by determining the systematic offset of each line relative to the average wavelength solution. Results. We give updated wavelengths for more than 8400 lines over the spectral range 3785-6915 A. The typical internal uncertainty on the line positions is estimated to be ~10 m/s (3.3 parts in 10^8 or 0.18 mA), which is a factor of 2-10 better than the widely used Los Alamos Atlas of the Thorium Spectrum (Palmer & Engleman 1983). The absolute accuracy of the global wavelength scale is the same as in the Los Alamos Atlas. Using this new line list on HARPS ThAr spectra, we are able to obtain a global wavelength calibration which is precise at the 20 cm/s level (6.7 parts in 10^10 or 0.0037 mA). Conclusions. Several research fields in astronomy requiring high-precision wavelength calibration in the visible (e.g. radial velocity planet searches, variability of fundamental constants) should benefit from using the new line list.Comment: 7 pages, 6 figures, accepted for publication in A&

Detection and Removal of Artifacts in Astronomical Images

Astronomical images from optical photometric surveys are typically contaminated with transient artifacts such as cosmic rays, satellite trails and scattered light. We have developed and tested an algorithm that removes these artifacts using a deep, artifact free, static sky coadd image built up through the median combination of point spread function (PSF) homogenized, overlapping single epoch images. Transient artifacts are detected and masked in each single epoch image through comparison with an artifact free, PSF-matched simulated image that is constructed using the PSF-corrected, model fitting catalog from the artifact free coadd image together with the position variable PSF model of the single epoch image. This approach works well not only for cleaning single epoch images with worse seeing than the PSF homogenized coadd, but also the traditionally much more challenging problem of cleaning single epoch images with better seeing. In addition to masking transient artifacts, we have developed an interpolation approach that uses the local PSF and performs well in removing artifacts whose widths are smaller than the PSF full width at half maximum, including cosmic rays, the peaks of saturated stars and bleed trails. We have tested this algorithm on Dark Energy Survey Science Verification data and present performance metrics. More generally, our algorithm can be applied to any survey which images the same part of the sky multiple times.Comment: 17 pages, 6 figures. Accepted for publication in Astronomy and Computin