Non-overlapping Windows Research Articles

RF-DYMHC: detecting the yeast meiotic recombination hotspots and coldspots by random forest model using gapped dinucleotide composition features

In the yeast, meiotic recombination is initiated by double-strand DNA breaks (DSBs) which occur at relatively high frequencies in some genomic regions (hotspots) and relatively low frequencies in others (coldspots). Although observations concerning individual hot/cold spots have given clues as to the mechanism of recombination initiation, the prediction of hot/cold spots from DNA sequence information is a challenging task. In this article, we introduce a random forest (RF) prediction model to detect recombination hot/cold spots from yeast genome. The out-of-bag (OOB) estimation of the model indicated that the RF classifier achieved high prediction performance with 82.05% total accuracy and 0.638 Mattew's correlation coefficient (MCC) value. Compared with an alternative machine-learning algorithm, support vector machine (SVM), the RF method outperforms it in both sensitivity and specificity. The prediction model is implemented as a web server (RF-DYMHC) and it is freely available at http://www.bioinf.seu.edu.cn/Recombination/rf_dymhc.htm. Given a yeast genome and prediction parameters (RI-value and non-overlapping window scan size), the program reports the predicted hot/cold spots and marks them in color.

Non-extensive block entropy statistics of Cantor fractal sets

By using non-extensive block entropy statistics, we demonstrate analytically that the static structures of deterministic Cantor sets with fractal dimension d f are characterised by a non-extensive q -exponent q = 1 / ( d f - d ) , for d f < d (where d is the embedding dimensions of the fractal set). To calculate the S q entropy we use the block entropy method based on non-overlapping windows and standard exact enumeration on Cantor sets. This result indicates that fractal structures are formed via dynamical processes which operate “at the edge of chaos”.

Large-scale genomic 2D visualization reveals extensive CG-AT skew correlation in bird genomes

BackgroundBird genomes have very different compositional structure compared with other warm-blooded animals. The variation in the base skew rules in the vertebrate genomes remains puzzling, but it must relate somehow to large-scale genome evolution. Current research is inclined to relate base skew with mutations and their fixation. Here we wish to explore base skew correlations in bird genomes, to develop methods for displaying and quantifying such correlations at different scales, and to discuss possible explanations for the peculiarities of the bird genomes in skew correlation.ResultsWe have developed a method called Base Skew Double Triangle (BSDT) for exhibiting the genome-scale change of AT/CG skew as a two-dimensional square picture, showing base skews at many scales simultaneously in a single image. By this method we found that most chicken chromosomes have high AT/CG skew correlation (symmetry in 2D picture), except for some microchromosomes. No other organisms studied (18 species) show such high skew correlations. This visualized high correlation was validated by three kinds of quantitative calculations with overlapping and non-overlapping windows, all indicating that chicken and birds in general have a special genome structure. Similar features were also found in some of the mammal genomes, but clearly much weaker than in chickens. We presume that the skew correlation feature evolved near the time that birds separated from other vertebrate lineages. When we eliminated the repeat sequences from the genomes, the AT and CG skews correlation increased for some mammal genomes, but were still clearly lower than in chickens.ConclusionOur results suggest that BSDT is an expressive visualization method for AT and CG skew and enabled the discovery of the very high skew correlation in bird genomes; this peculiarity is worth further study. Computational analysis indicated that this correlation might be a compositional characteristic, present not only in chickens, but also remained or developed in some mammals during evolution. Special aspects of bird metabolism related to e.g. flight may be the reason why birds evolved or retained the skew correlation. Our analysis also indicated that repetitive DNA sequence elements need to be taken into account in studying the evolution of the correlation between AT and CG skews.

Detecting DDoS attacks against web server using time series analysis

Distributed Denial of Service (DDoS) attack is a major threat to the availability of Web service. The inherent presence of self-similarity in Web traffic motivates the applicability of time series analysis in the study of the burst feature of DDoS attack. This paper presents a method of detecting DDoS attacks against Web server by analyzing the abrupt change of time series data obtained from Web traffic. Time series data are specified in reference sliding window and test sliding window, and the abrupt change is modeled using Auto-Regressive (AR) process. By comparing two adjacent non-overlapping windows of the time series, the attack traffic could be detected at a time point. Combined with alarm correlation and location correlation, not only the presence of DDoS attack, but also its occurring time and location can be determined. The experimental results in a test environment are illustrated to justify our method.

Multifocus image fusion through pseudo-Wigner distribution

We describe a new image fusion paradigm that provides an enhanced image from a set of source images that present regions with different spatial degradation patterns. The fusion procedure is based on the use of a new defocusing pixel-level measure. Such a measure is defined through a 1-D pseudo-Wigner distribution function (PWD) applied to nonoverlapping N-pixel window slices of the original image. The process is repeated to cover the full image size. By taking a low-resolution image as a reference image, which can be defined by blurring and averaging the two source images, a pixel-level distance measure of the defocus degree can be obtained from the PWD of each image. This procedure makes it possible to choose from a focusing point of view the in-focus pixels from each one of the given source images. The method is illustrated with different pairs of images of the same scene, which are partly focused and partly defocused in different regions. The image fusion approach that we propose here can work for any source of images available, and the comparison using evaluation measures such as mean square error or percentage of correct decisions shows that our framework can outperform the current approaches for the analyzed cases. One additional advantage of the present approach is its reduced computational cost when compared with other methods based on a full 2-D implementation of the PWD.

Effects of Subthreshold Shocks on Wavelet Propagation during Atrial Fibrillation in Humans

Our objectives are: first to investigate the effects of internal cardioversion energies on the wave fronts propagation in the right atrium immediately after the energy delivery; second, to track the time course of these effects. The study is based on a measure of organization of the endoatrial electrograms obtained by a multipolar basket catheter inserted in the right atrium. We estimated the level of organization by computing the percentage of points laying on the signal baseline (i.e., number of occurrences, NO). NO values were computed on two-second long windows. Six non-overlapped windows were selected, one just before and five just after the last unsuccessful shock. Immediately after the shock most of the patients exhibited an increase in the organization patterns. This increase was more evident in those patients with rather disorganized patterns and higher energy threshold. This effect fades within a few seconds after the shock delivery. Our data confirm the idea that the electrical shock causes a widespread extinction of electrical wavefronts, which regenerates after the shock. Since an increase of organization may lead to a reduction of energy threshold, a potential application of these findings might consist in the delivery of multiple subthreshold shocks instead of a single one.

Patterns of gene duplication in Saccharomyces cerevisiae and Caenorhabditis elegans.

In this paper we present a new method for detecting block duplications in a genome. It is more stringent than previous ones in that it requires a more rigorous definition of paralogous genes and that it requires the paralogous proteins on the two blocks to be contiguous. In addition, it provides three criterion choices: (1) the same composition (i.e., having the same paralogues in the two windows), (2) the same composition and gene order, and (3) the same composition, gene order, and gene orientation. The method is completely automated, requiring no visual inspection as in previous methods. We applied it to analyze the complete genomes of S. cerevisiae and C. elegans. In yeast we detected fewer duplicated blocks than previously reported. In C. elegans, however, we detected more block duplications than previously reported, indicating that although our method has a more stringent definition of block duplication than previous ones, it may be more sensitive in detection because it considers every possible window rather than only fixed nonoverlapping windows. Our results show that block duplication is a common phenomenon in both organisms. The patterns of block duplication in the two species are, however, markedly different. The yeast shows much more extensive block duplication than the nematode, with some chromosomes having more than 40% of the duplications derived from block duplications. Moreover, in the yeast the majority of block duplications occurred between chromosomes, while in the nematode most block duplications occurred within chromosomes.

Discriminative fabric defect detection using adaptive wavelets

We propose a new method for fabric defect detection by in- corporating the design of an adaptive wavelet-based feature extractor with the design of an Euclidean distance-based detector. The proposed method characterizes the fabric image with multiscale wavelet features by using undecimated discrete wavelet transforms. Each nonoverlapping window of the fabric image is then detected as defect or nondefect with an Euclidean distance-based detector. Instead of using the standard wavelet bases, an adaptive wavelet basis is designed for the detection of fabric defects. Minimization of the detection error is achieved by incor- porating the design of the adaptive wavelet with the design of the detec- tor parameters using a discriminative feature extraction (DFE) training method. The proposed method has been evaluated on 480 defect samples from five types of defects, and 480 nondefect samples, where a 97.5% detection rate and 0.63% false alarm rate were achieved. The evaluations were also carried out on unknown types of defects, where a 93.3% detection rate and 3.97% false alarm rate were achieved in the detection of 180 defect samples and 780 nondefect samples. © 2002

Pervasive properties of the genomic signature.

BackgroundThe dinucleotide relative abundance profile can be regarded as a genomic signature because, despite diversity between species, it varies little between 50 kilobase or longer windows on a given genome. Both the causes and the functional significance of this phenomenon could be illuminated by determining if it persists on smaller scales. The profile is computed from the base step "odds ratios" that compare dinucleotide frequencies to those expected under the assumption of stochastic equilibrium (thorough shuffling). Analysis is carried out on 22 sequences, representing 19 species and comprised of about 53 million bases all together, to assess stability of the signature in windows ranging in size from 50 kilobases down to 125 bases.ResultsDinucleotide relative abundance distance from the global signature is computed locally for all non-overlapping windows on each sequence. These distances are log-normally distributed with nearly constant variance and with means that tend to zero slower than reciprocal square root of window size. The mean distance within genomes is larger for protist, plant, and human chromosomes, and smaller for archaea, bacteria, and yeast, for any window size.ConclusionsThe imprint of the global signature is locally pervasive on all scales considered in the sequences (either genomes or chromosomes) that were scanned.

An analysis of neural receptive field plasticity by point process adaptive filtering.

Neural receptive fields are plastic: with experience, neurons in many brain regions change their spiking responses to relevant stimuli. Analysis of receptive field plasticity from experimental measurements is crucial for understanding how neural systems adapt their representations of relevant biological information. Current analysis methods using histogram estimates of spike rate functions in nonoverlapping temporal windows do not track the evolution of receptive field plasticity on a fine time scale. Adaptive signal processing is an established engineering paradigm for estimating time-varying system parameters from experimental measurements. We present an adaptive filter algorithm for tracking neural receptive field plasticity based on point process models of spike train activity. We derive an instantaneous steepest descent algorithm by using as the criterion function the instantaneous log likelihood of a point process spike train model. We apply the point process adaptive filter algorithm in a study of spatial (place) receptive field properties of simulated and actual spike train data from rat CA1 hippocampal neurons. A stability analysis of the algorithm is sketched in the. The adaptive algorithm can update the place field parameter estimates on a millisecond time scale. It reliably tracked the migration, changes in scale, and changes in maximum firing rate characteristic of hippocampal place fields in a rat running on a linear track. Point process adaptive filtering offers an analytic method for studying the dynamics of neural receptive fields.

Sleep and wakefulness in somnambulism: A spectral analysis study

Objective: The sleep structure and the dynamics of EEG slow-wave activity (SWA) were investigated in 12 young adults and age- and gender-matched controls. Methods: Polysomnography was performed in subjects with well-docurnented chronic sleepwalking and in matched controls. Blinded visual scoring was performed using the international criteria from the Rechtschaffen and Kales atlas [A manual of standardized technology, techniques and scoring systems for sleep stages of human subjects. Los Angeles: UCLA Brain Information Service, Brain Research Institute, 1968.] and by determining the presence of microarousals as defined in the American Sleep Disorders Association (ASDA) atlas [Sleep 15 (1992) 173.]. An evaluation of SWA overnight was performed on total nocturnal sleep to determine if a difference existed between groups of subjects, since sleepwalking usually originates with slow-wave sleep. Investigation of the delta power in successive nonoverlapping 4-second windows in the 32 seconds just prior to EMG activity associated with a confusional arousal was also conducted. One central EEG lead was used for all analyses. Results: Somnambulistic individuals experienced more disturbed sleep than controls during the first NREM–REM sleep cycle. They had a higher number of ASDA arousals and presented lower peak of SWA during the first cycle that led to a lower SWA decline overnight. When the investigation focused on the short segment immediately preceding a confusional arousal, they presented an important increase in the relative power of low delta (0.75–2 Hz) just prior to the confusional arousal. Conclusion: Sleepwalkers undergo disturbed nocturnal sleep at the beginning of the night. The increased power of low delta just prior to the confusional arousal experienced may not be related to Stages 3–4 NREM sleep. We hypothesize that it may be translated as a cortical reaction to brain activation.

Worst Traffic Passing Virtual Frame Regulation: Analysis with Dynamic Programming

This paper studies a discrete-time queueing system in which the traffic regulation places an upper bound on the number of arrivals in each of the non-overlapping time windows (virtual frames) of a fixed length. The worst traffic passing through this traffic regulation is characterized. As a criterion for traffic comparison, this paper employs the weighted sum of queueing delays with the weighting factors decaying geometrically over the time horizon. This paper uses dynamic programming techniques and convexity argument to characterize the worst traffic.

Densities, length proportions, and other distributional features of repetitive sequences in the human genome estimated from 430 megabases of genomic sequence

The densities of repetitive elements in the human genome were calculated in each GC content class using non-overlapping windows of 50kb. The density of Alu is two to three times higher in GC-rich regions than in AT-rich regions, while the opposite is true for LINE1. In contrast, LINE2 and other elements, such as DNA transposons, are more uniformly distributed in the genome. The number of Alus in the human genome was estimated to be 1.4 million, higher than previous estimates. About 40% of the autosomes and ∼51% of the X and Y chromosomes are occupied by repetitive elements. In total, the human genome is estimated to contain more than 4 million repetitive elements. The GC contents (%) of repetitive elements and their flanking regions were also calculated. The GC contents of almost all kinds of repeats are positively correlated with the window GC contents, suggesting that a repetitive sequence is subject to the same mutation pressure as its surrounding regions, so it tends to have the same GC content as its surrounding regions. This observation supports the regional mutation hypothesis. The only two exceptions are AluYa and AluYb8, the two youngest Alu subfamilies. The GC content of AluYb8 is negatively correlated with that of its surrounding regions, while AluYa shows no correlation, suggesting different insertion patterns for these two young Alu subfamilies. This suggestion was supported by the fact that the average genetic distance between members of AluYb8 in each GC window class is positively correlated with the GC content of the window, but no correlation was found for AluYa. AluYa is more frequent in Y chromosome than in other chromosomes; the same is true for LTR retroviruses. This pattern might be correlated with the evolutionary history of Y chromosome.

A time-dependent analysis of spatial information encoding in the rat hippocampus

The place fields of rat hippocampal pyramidal cells evolve over time as the animal moves through its environment. To study the nature of this evolution we use an inhomogeneous gamma probability model and analyze the properties of place cell spike trains in non-overlapping windows. Although the locations and heights of the fields evolve over time for 27 of the 35 place cells studied, the temporal parameter was essentially unchanged. This result suggests that adaptive estimation methods may be useful to characterize the dynamics of hippocampal place cells for behavioral tasks executed in novel and non-novel environments.

Stationarity and redundancy of multichannel EEG data recorded during generalized tonic-clonic seizures.

To improve our understanding of the physiology of generalized tonic-clonic (GTC) seizures, we have investigated the stationarity and redundancy of 21-electrode EEG data recorded from ten patients during GTC seizures elicited by electroconvulsive therapy (ECT). Stationarity was examined by calculating probability density functions (pdfs) and power spectra over small equal-length non-overlapping time windows and then by studying, visually and quantitatively, the evolution of these quantities over the duration of the seizures. Our analysis shows that some seizures had no demonstrable stationarity, that most seizures had time intervals of at least a few seconds that were statistically stationary by several criteria, and that, in some seizures, there were leads which were delayed in manifesting the statistical changes associated with seizure onset evident in other leads. The redundancy analysis demonstrated for the first time posterior-to-anterior time delays in the mid-ictal region of GTC seizures. The implications of these findings are discussed for the analysis of GTC seizure EEG data, for the physiology of GTC seizures, and for ECT research.

Relationship between BRPS, SANS and EEG-variables in postacute patients with schizophrenia

Sample entropy (SampEn) is a nonlinear regularity index that requires the a priori selection of three parameters: the length of the sequences to be compared, m, the patterns similarity tolerance, r, and the number of samples under analysis, N. Appropriate values for m, r and N have been recommended and widely used in the literature for the application of SampEn to some physiological time series, such as heart rate, hormonal data, etc. However, no guidelines exist for the selection of that values in other cases. Therefore, an optimal parameters study should be required for the application of SampEn to not previously analyzed biomedical signals. In the present work, a thorough analysis on the optimal values for m, r and N is presented within the context of atrial fibrillation (AF) organization estimation, computed from surface electrocardiogram recordings. Recently, the evaluation of AF organization through SampEn, has revealed clinically useful information that could be used for a better treatment of this arrhythmia. The present study analyzed optimal SampEn parameter values within two different scenarios of AF organization estimation, such as the prediction of paroxysmal AF termination and the electrical cardioversion outcome in persistent AF. As a result, interesting recommendations about the selection of m, r and N, together with the relationship between N and the sampling rate (fs) were obtained. More precisely, (i) the proportion between N and fs should be higher than 1 s and fs ≥ 256 Hz, (ii) overlapping between adjacent N-length windows does not improve AF organization estimation with respect to the analysis of non-overlapping windows, and (iii) values of m and r maximizing successful classification for the analyzed AF databases should be considered within a range wider than the proposed in the literature for heart rate analysis, i.e. m = 1 and m = 2 and r between 0.1 and 0.25 times the standard deviation of the data.

Measuring Patterns in Population Fluctuations

Measuring Patterns in Population Fluctuations

BOT's based on nonuniform filter banks

Parallels between orthogonal transforms and filter banks have been drawn before. Block orthogonal transform (BOT) is a special case of orthogonal transform where a nonoverlapping window is used. We relate BOTs to filter banks. Specifically, we show that any BOT can be shown as a perfect reconstruction filter bank, and any tree-structured perfect reconstruction filter bank or any orthonormal filter bank for which no filter length exceeds its decimation factor can be shown as a BOT. We then show that all conventional BOTs map to uniform filter banks. A construction method to design a BOT from any nonuniform filter bank is presented, and finding an optimal tree structure (in the sense of transform coding gain) for a given source is also discussed. The results show that the optimal, nonuniform BOT outperforms uniform BOTs having either the same number of bands or the same size in most cases.

A Monte Carlo investigation of the dual photopeak window scatter correction method (SPECT)

Results from a Monte Carlo investigation of the dual photopeak window (DPW) scatter correction method are presented for point and extended sources of Tc-99m in both homogeneous and nonhomogeneous attenuating media. The DPW method uses the ratio of counts in two nonoverlapping energy windows within the photopeak region as input to a regression relation. A pixel-by-pixel estimate of the scatter in the summed windows is obtained and subtracted to yield an estimate of the primary. An approximately tenfold decrease in the scatter fraction and an excellent agreement with the shape of the true scatter distribution were observed. >

Moment-preserving edge detection and its application to image data compression

In contrast to the numerous edge-detection techniques that detect edges either point by point or using overlapping circular windows, an edge detector using nonoverlapping rectangular windows is proposed. The detector examines the pixels within each rectangular window of an image, and decides whether an edge element is present or not in the window. Based on the gray and mass moment-preserving principles, the step edge is estimated locally to subpixel accuracy using analytical formulas. To apply the edge detection results to image compression, the detected edge elements are then tracked and grouped based on proximity and orientation. Using the line parameters of the grouped edge elements, region boundaries are approximated in a piecewise linear manner. This reduces the amount of data required to describe region shapes and is useful for compressing some types of images. Good experimental results of compressing character and trademark images are also included to show the feasibility of the proposed approach.