Energetics of Protein-DNA Interactions

Protein-DNA interactions are vital for many processes in living cells, especially transcriptional regulation and DNA modification. To further our understanding of these important processes on the microscopic level, it is necessary that theoretical models describe the macromolecular interaction energetics accurately. While several methods have been proposed, there has not been a careful comparison of how well the different methods are able to predict biologically important quantities such as the correct DNA binding sequence, total binding free energy, and free energy changes caused by DNA mutation. In addition to carrying out the comparison, we present two important theoretical models developed initially in protein folding that have not yet been tried on protein-DNA interactions. In the process, we find that the results of these knowledge-based potentials show a strong dependence on the interaction distance and the derivation method. Finally, we present a knowledge-based potential that gives comparable or superior results to the best of the other methods, including the molecular mechanics force field AMBER99

Shape basis interpretation for monocular deformable 3D reconstruction

© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.In this paper, we propose a novel interpretable shape model to encode object non-rigidity. We first use the initial frames of a monocular video to recover a rest shape, used later to compute a dissimilarity measure based on a distance matrix measurement. Spectral analysis is then applied to this matrix to obtain a reduced shape basis, that in contrast to existing approaches, can be physically interpreted. In turn, these pre-computed shape bases are used to linearly span the deformation of a wide variety of objects. We introduce the low-rank basis into a sequential approach to recover both camera motion and non-rigid shape from the monocular video, by simply optimizing the weights of the linear combination using bundle adjustment. Since the number of parameters to optimize per frame is relatively small, specially when physical priors are considered, our approach is fast and can potentially run in real time. Validation is done in a wide variety of real-world objects, undergoing both inextensible and extensible deformations. Our approach achieves remarkable robustness to artifacts such as noisy and missing measurements and shows an improved performance to competing methods.Peer ReviewedPostprint (author's final draft

Mining Heterogeneous Multivariate Time-Series for Learning Meaningful Patterns: Application to Home Health Telecare

For the last years, time-series mining has become a challenging issue for researchers. An important application lies in most monitoring purposes, which require analyzing large sets of time-series for learning usual patterns. Any deviation from this learned profile is then considered as an unexpected situation. Moreover, complex applications may involve the temporal study of several heterogeneous parameters. In that paper, we propose a method for mining heterogeneous multivariate time-series for learning meaningful patterns. The proposed approach allows for mixed time-series -- containing both pattern and non-pattern data -- such as for imprecise matches, outliers, stretching and global translating of patterns instances in time. We present the early results of our approach in the context of monitoring the health status of a person at home. The purpose is to build a behavioral profile of a person by analyzing the time variations of several quantitative or qualitative parameters recorded through a provision of sensors installed in the home

Distances and ages of globular clusters using Hipparcos parallaxes of local subdwarfs

We discuss the impact of Population II and Globular Cluster (GCs) stars on the derivation of the age of the Universe, and on the study of the formation and early evolution of galaxies, our own in particular. The long-standing problem of the actual distance scale to Population II stars and GCs is addressed, and a variety of different methods commonly used to derive distances to Population II stars are briefly reviewed. Emphasis is given to the discussion of distances and ages for GCs derived using Hipparcos parallaxes of local subdwarfs. Results obtained by different authors are slightly different, depending on different assumptions about metallicity scale, reddenings, and corrections for undetected binaries. These and other uncertainties present in the method are discussed. Finally, we outline progress expected in the near future.Comment: Invited review article to appear in: `Post-Hipparcos Cosmic Candles', A. Heck & F. Caputo (Eds), Kluwer Academic Publ., Dordrecht, in press. 22 pages including 3 tables and 2 postscript figures, uses Kluwer's crckapb.sty LaTeX style file, enclose

Alignment-free Genomic Analysis via a Big Data Spark Platform

Motivation: Alignment-free distance and similarity functions (AF functions, for short) are a well established alternative to two and multiple sequence alignments for many genomic, metagenomic and epigenomic tasks. Due to data-intensive applications, the computation of AF functions is a Big Data problem, with the recent Literature indicating that the development of fast and scalable algorithms computing AF functions is a high-priority task. Somewhat surprisingly, despite the increasing popularity of Big Data technologies in Computational Biology, the development of a Big Data platform for those tasks has not been pursued, possibly due to its complexity. Results: We fill this important gap by introducing FADE, the first extensible, efficient and scalable Spark platform for Alignment-free genomic analysis. It supports natively eighteen of the best performing AF functions coming out of a recent hallmark benchmarking study. FADE development and potential impact comprises novel aspects of interest. Namely, (a) a considerable effort of distributed algorithms, the most tangible result being a much faster execution time of reference methods like MASH and FSWM; (b) a software design that makes FADE user-friendly and easily extendable by Spark non-specialists; (c) its ability to support data- and compute-intensive tasks. About this, we provide a novel and much needed analysis of how informative and robust AF functions are, in terms of the statistical significance of their output. Our findings naturally extend the ones of the highly regarded benchmarking study, since the functions that can really be used are reduced to a handful of the eighteen included in FADE

Bayesian analysis of ages, masses, and distances to cool stars with non-LTE spectroscopic parameters

For studies of Galactic evolution, the accurate characterization of stars in terms of their evolutionary stage and population membership is of fundamental importance. A standard approach relies on extracting this information from stellar evolution models but requires the effective temperature, surface gravity, and metallicity of a star obtained by independent means. In previous work, we determined accurate effective temperatures and non-LTE logg and [Fe/H] (NLTE-Opt) for a large sample of metal-poor stars, -3<[Fe/H]<-0.5, selected from the RAVE survey. As a continuation of that work, we derive here their masses, ages, and distances using a Bayesian scheme and GARSTEC stellar tracks. For comparison, we also use stellar parameters determined from the widely-used 1D LTE excitation-ionization balance of Fe (LTE-Fe). We find that the latter leads to systematically underestimated stellar ages, by 10-30%, but overestimated masses and distances. Metal-poor giants suffer from the largest fractional distance biases of 70%. Furthermore, we compare our results with those released by the RAVE collaboration for the stars in common (DR3, Zwitter et al. 2010, Seibert et al. 2011). This reveals -400 to +400 K offsets in effective temperature, -0.5 to 1.0 dex offsets in surface gravity, and 10 to 70% in distances. The systematic trends strongly resemble the correlation we find between the NLTE-Opt and LTE-Fe parameters, indicating that the RAVE DR3 data may be affected by the physical limitations of the 1D LTE synthetic spectra. Our results bear on any study, where spectrophotometric distances underlie stellar kinematics. In particular, they shed new light on the debated controversy about the Galactic halo origin raised by the SDSS/SEGUE observations.Comment: 13 pages and 15 figures. Accepted for publication in MNRA

Building the cosmic distance scale: from Hipparcos to Gaia

Hipparcos, the first ever experiment of global astrometry, was launched by ESA in 1989 and its results published in 1997 (Perryman et al., Astron. Astrophys. 323, L49, 1997; Perryman & ESA (eds), The Hipparcos and Tycho catalogues, ESA SP-1200, 1997). A new reduction was later performed using an improved satellite attitude reconstruction leading to an improved accuracy for stars brighter than 9th magnitude (van Leeuwen & Fantino, Astron. Astrophys. 439, 791, 2005; van Leeuwen, Astron. Astrophys. 474, 653, 2007). The Hipparcos Catalogue provided an extended dataset of very accurate astrometric data (positions, trigonometric parallaxes and proper motions), enlarging by two orders of magnitude the quantity and quality of distance determinations and luminosity calibrations. The availability of more than 20000 stars with a trigonometric parallax known to better than 10% opened the way to a drastic revision of our 3-D knowledge of the solar neighbourhood and to a renewal of the calibration of many distance indicators and age estimations. The prospects opened by Gaia, the next ESA cornerstone, planned for launch in June 2013 (Perryman et al., Astron. Astrophys. 369, 339, 2001), are still much more dramatic: a billion objects with systematic and quasi simultaneous astrometric, spectrophotometric and spectroscopic observations, about 150 million stars with expected distances to better than 10%, all over the Galaxy. All stellar distance indicators, in very large numbers, will be directly measured, providing a direct calibration of their luminosity and making possible detailed studies of the impacts of various effects linked to chemical element abundances, age or cluster membership. With the help of simulations of the data expected from Gaia, obtained from the mission simulator developed by DPAC, we will illustrate what Gaia can provide with some selected examples.Comment: 16 pages, 16 figures, Conference "The Fundamental Cosmic Distance scale: State of the Art and the Gaia perspective, 3-6 May 2011, INAF, Osservatorio Astronomico di Capodimonte, Naples. Accepted for publication in Astrophysics & Space Scienc

Evolutionary distances in the twilight zone -- a rational kernel approach

Phylogenetic tree reconstruction is traditionally based on multiple sequence alignments (MSAs) and heavily depends on the validity of this information bottleneck. With increasing sequence divergence, the quality of MSAs decays quickly. Alignment-free methods, on the other hand, are based on abstract string comparisons and avoid potential alignment problems. However, in general they are not biologically motivated and ignore our knowledge about the evolution of sequences. Thus, it is still a major open question how to define an evolutionary distance metric between divergent sequences that makes use of indel information and known substitution models without the need for a multiple alignment. Here we propose a new evolutionary distance metric to close this gap. It uses finite-state transducers to create a biologically motivated similarity score which models substitutions and indels, and does not depend on a multiple sequence alignment. The sequence similarity score is defined in analogy to pairwise alignments and additionally has the positive semi-definite property. We describe its derivation and show in simulation studies and real-world examples that it is more accurate in reconstructing phylogenies than competing methods. The result is a new and accurate way of determining evolutionary distances in and beyond the twilight zone of sequence alignments that is suitable for large datasets.Comment: to appear in PLoS ON

IDENTIFICATION OF COVER SONGS USING INFORMATION THEORETIC MEASURES OF SIMILARITY

13 pages, 5 figures, 4 tables. v3: Accepted version13 pages, 5 figures, 4 tables. v3: Accepted version13 pages, 5 figures, 4 tables. v3: Accepted versio