Search results for "Signal Processing"
showing 10 items of 2451 documents
Parallel Pairwise Epistasis Detection on Heterogeneous Computing Architectures
2016
This is a post-peer-review, pre-copyedit version of an article published in IEEE Transactions on Parallel and Distributed Systems. The final authenticated version is available online at: http://dx.doi.org/10.1109/TPDS.2015.2460247. [Abstract] Development of new methods to detect pairwise epistasis, such as SNP-SNP interactions, in Genome-Wide Association Studies is an important task in bioinformatics as they can help to explain genetic influences on diseases. As these studies are time consuming operations, some tools exploit the characteristics of different hardware accelerators (such as GPUs and Xeon Phi coprocessors) to reduce the runtime. Nevertheless, all these approaches are not able t…
Measuring spectrally-resolved information transfer.
2020
Information transfer, measured by transfer entropy, is a key component of distributed computation. It is therefore important to understand the pattern of information transfer in order to unravel the distributed computational algorithms of a system. Since in many natural systems distributed computation is thought to rely on rhythmic processes a frequency resolved measure of information transfer is highly desirable. Here, we present a novel algorithm, and its efficient implementation, to identify separately frequencies sending and receiving information in a network. Our approach relies on the invertible maximum overlap discrete wavelet transform (MODWT) for the creation of surrogate data in t…
The Brain, Mind and Electromagnetic Waves
2021
The functions of electromagnetic waves both as an information carrier and energy field in the impact on the human body have been discussed. Possible consequences of the effect of electromagnetic fields of different frequencies on the human brain and body have been addressed and commented on. The complex nature of electromagnetic phenomena revealed in interactions between humans and the environment, featuring the most relevant hazards, was demonstrated.
Biophysics of high density nanometer regions extracted from super-resolution single particle trajectories: application to voltage-gated calcium chann…
2019
AbstractThe cellular membrane is very heterogenous and enriched with high-density regions forming microdomains, as revealed by single particle tracking experiments. However the organization of these regions remain unexplained. We determine here the biophysical properties of these regions, when described as a basin of attraction. We develop two methods to recover the dynamics and local potential wells (field of force and boundary). The first method is based on the local density of points distribution of trajectories, which differs inside and outside the wells. The second method focuses on recovering the drift field that is convergent inside wells and uses the transient field to determine the…
Searching events in AFM force-extension curves: A wavelet approach
2016
An algorithm, based on the wavelet scalogram energy, for automatically detecting events in force-extension AFM force spectroscopy experiments is introduced. The events to be detected are characterized by a discontinuity in the signal. It is shown how the wavelet scalogram energy has different decay rates at different points depending on the degree of regularity of the signal, showing faster decay rates at regular points and slower rates at singular points (jumps). It is shown that these differences produce peaks in the scalogram energy plot at the event points. Finally, the algorithm is illustrated in a tether analysis experiment by using it for the detection of events in the AFM force-exte…
Coupling News Sentiment with Web Browsing Data Improves Prediction of Intra-Day Price Dynamics
2015
The new digital revolution of big data is deeply changing our capability of understanding society and forecasting the outcome of many social and economic systems. Unfortunately, information can be very heterogeneous in the importance, relevance, and surprise it conveys, affecting severely the predictive power of semantic and statistical methods. Here we show that the aggregation of web users' behavior can be elicited to overcome this problem in a hard to predict complex system, namely the financial market. Specifically, our in-sample analysis shows that the combined use of sentiment analysis of news and browsing activity of users of Yahoo! Finance greatly helps forecasting intra-day and dai…
Extricating New Physics Scenarios at DUNE with High Energy Beams
2017
The proposed Deep Underground Neutrino Experiment (DUNE) utilizes a wide-band on-axis tunable muon-(anti)neutrino beam with a baseline of 1300 km to search for CP violation with high precision. Given the long baseline, DUNE is also sensitive to effects due to non-standard neutrino interactions (NSI) which can interfere with the standard 3-flavor oscillation paradigm. In this Letter, we exploit the tunability of the DUNE neutrino beam over a wide-range of energies and utilize a new theoretical metric to devise an experimental strategy for separating oscillation effects due to NSI from the standard 3-flavor oscillation scenario. Using our metric, we obtain an optimal combination of beam tunes…
State transition identification in multivariate time series (STIMTS) applied to rotational jump trajectories from single molecules
2018
Time resolved data from single molecule experiments often suffer from contamination with noise due to a low signal level. Identifying a proper model to describe the data thus requires an approach with sufficient model parameters without misinterpreting the noise as relevant data. Here, we report on a generalized data evaluation process to extract states with piecewise constant signal level from simultaneously recorded multivariate data, typical for multichannel single molecule experiments. The method employs the minimum description length principle to avoid overfitting the data by using an objective function, which is based on a tradeoff between fitting accuracy and model complexity. We val…
Deviance sensitivity in the auditory cortex of freely moving rats.
2018
Deviance sensitivity is the specific response to a surprising stimulus, one that violates expectations set by the past stimulation stream. In audition, deviance sensitivity is often conflated with stimulus-specific adaptation (SSA), the decrease in responses to a common stimulus that only partially generalizes to other, rare stimuli. SSA is usually measured using oddball sequences, where a common (standard) tone and a rare (deviant) tone are randomly intermixed. However, the larger responses to a tone when deviant does not necessarily represent deviance sensitivity. Deviance sensitivity is commonly tested using a control sequence in which many different tones serve as the standard, eliminat…
Variance component analysis to assess protein quantification in biomarker discovery. Application to MALDI-TOF mass spectrometry.
2017
International audience; Controlling the technological variability on an analytical chain is critical for biomarker discovery. The sources of technological variability should be modeled, which calls for specific experimental design, signal processing, and statistical analysis. Furthermore, with unbalanced data, the various components of variability cannot be estimated with the sequential or adjusted sums of squares of usual software programs. We propose a novel approach to variance component analysis with application to the matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) technology and use this approach for protein quantification by a classical signal processing algori…