Ramón Román-Roldán

Removing Noise and Preserving Details with Relaxed Median Filters

In this paper, a median based filter called relaxed median filter is proposed. The filter is obtained by relaxing the order statistic for pixel substitution. Noise attenuation properties as well as edge and line preservation are analyzed statistically. The trade-off between noise elimination and detail preservation is widely analyzed. It is shown that relaxed median filters preserve details better than the standard median filter, and remove noise better than other median type filters.

Isochore chromosome maps of eukaryotic genomes

Analytical DNA ultracentrifugation revealed that eukaryotic genomes are mosaics of isochores: long DNA segments (>>300 kb on average) relatively homogeneous in G+C. Important genome features are dependent on this isochore structure, e.g. genes are found predominantly in the GC-richest isochore classes. However, no reliable method is available to rigorously partition the genome sequence into relatively homogeneous regions of different composition, thereby revealing the isochore structure of chromosomes at the sequence level. Homogeneous regions are currently ascertained by plain statistics on moving windows of arbitrary length, or simply by eye on G+C plots. On the contrary, the entropic segmentation method is able to divide a DNA sequence into relatively homogeneous, statistically significant domains. An early version of this algorithm only produced domains having an average length far below the typical isochore size. Here we show that an improved segmentation method, specifically intended to determine the most statistically significant partition of the sequence at each scale, is able to identify the boundaries between long homogeneous genome regions displaying the typical features of isochores. The algorithm precisely locates classes II and III of the human major histocompatibility complex region, two well-characterized isochores at the sequence level, the boundary between them being the first isochore boundary experimentally characterized at the sequence level. The analysis is then extended to a collection of human large contigs. The relatively homogeneous regions we find show many of the features (G+C range, relative proportion of isochore classes, size distribution, and relationship with gene density) of the isochores identified through DNA centrifugation. Isochore chromosome maps, with many potential applications in genomics, are then drawn for all the completely sequenced eukaryotic genomes available.

A measure of quality for evaluating methods of segmentation and edge detection

A new measure of quality is proposed for evaluating the performance of available methods of image segmentation and edge detection. The technique is intended for the evaluation of low error results and features an objective assessment of discrepancy with respect to the theoretical edge, in tandem with subjective visual evaluation using both the neighbourhood and error-interaction criteria. The proposed mathematical model is extremely simple, even from the perspective of computational execution. A training of the measure has been put in practice, which uses visual evaluation of a set of error patterns by a team of observers. Encouraging results were obtained for a selection of test images, especially in relation to other recently proposed and/or currently employed quality measures. ( 2001 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.

APPLICATION OF INFORMATION THEORY TO DNA SEQUENCE ANALYSIS: A REVIEW

The analysis of DNA sequences through information theory methods is reviewed from the beginning in the 70s. The subject is addressed within a broad context, describing in some detail the cornerstone contributions in the field. The emerging interest concerning long-range correlations and the mosaic structure of DNA sequences is considered from our own point of view. A recent procedure developed by the authors is also outlined.

Isochore chromosome maps of the human genome

The human genome is a mosaic of isochores, which are long DNA segments (z.Gt;300 kbp) relatively homogeneous in G+C. Human isochores were first identified by density-gradient ultracentrifugation of bulk DNA, and differ in important features, e.g. genes are found predominantly in the GC-richest isochores. Here, we use a reliable segmentation method to partition the longest contigs in the human genome draft sequence into long homogeneous genome regions (LHGRs), thereby revealing the isochore structure of the human genome. The advantages of the isochore maps presented here are: (1) sequence heterogeneities at different scales are shown in the same plot; (2) pair-wise compositional differences between adjacent regions are all statistically significant; (3) isochore boundaries are accurately defined to single base pair resolution; and (4) both gradual and abrupt isochore boundaries are simultaneously revealed. Taking advantage of the wide sample of genome sequence analyzed, we investigate the correspondence between LHGRs and true human isochores revealed through DNA centrifugation. LHGRs show many of the typical isochore features, mainly size distribution, G+C range, and proportions of the isochore classes. The relative density of genes, Alu and long interspersed nuclear element repeats and the different types of single nucleotide polymorphisms on LHGRs also coincide with expectations in true isochores. Potential applications of isochore maps range from the improvement of gene-finding algorithms to the prediction of linkage disequilibrium levels in association studies between marker genes and complex traits. The coordinates for the LHGRs identified in all the contigs longer than 2 Mb in the human genome sequence are available at the online resource on isochore mapping: http://bioinfo2.ugr.es/isochores.

An Analysis of Edge Detection by Using the Jensen-Shannon Divergence

This work constitutes a theoretical study of the edge-detection method by means of the Jensen-Shannon divergence, as proposed by the authors. The overall aim is to establish formally the suitability of the procedure of edge detection in digital images, as a step prior to segmentation. In specific, an analysis is made not only of the properties of the divergence used, but also of the methods sensitivity to the spatial variation, as well as the detection-error risk associated with the operating conditions due to the randomness of the spatial configuration of the pixels. Although the paper deals with the procedure based on the Jensen-Shannon divergence, some problems are also related to other methods based on local detection with a sliding window, and part of the study is focused to noisy and textured images.

SEGMENT: identifying compositional domains in DNA sequences

MOTIVATION DNA sequences are formed by patches or domains of different nucleotide composition. In a few simple sequences, domains can simply be identified by eye; however, most DNA sequences show a complex compositional heterogeneity (fractal structure), which cannot be properly detected by current methods. Recently, a computationally efficient segmentation method to analyse such nonstationary sequence structures, based on the Jensen-Shannon entropic divergence, has been described. Specific algorithms implementing this method are now needed. RESULTS Here we describe a heuristic segmentation algorithm for DNA sequences, which was implemented on a Windows program (SEGMENT). The program divides a DNA sequence into compositionally homogeneous domains by iterating a local optimization procedure at a given statistical significance. Once a sequence is partitioned into domains, a global measure of sequence compositional complexity (SCC), accounting for both the sizes and compositional biases of all the domains in the sequence, is derived. SEGMENT computes SCC as a function of the significance level, which provides a multiscale view of sequence complexity.

Measurement of surface tension and contact angle using entropic edge detection

This paper presents a new method to measure the surface tension and the contact angle of a liquid. The measurement procedure comprises three steps: acquisition of the liquid drop image, image segmentation to obtain the contour of the drop and surface-tension and contact-angle calculation by the ADSA method. In the second step a new segmentation method is used based on the Jensen-Shannon divergence, an entropic measurement of coherence among distribution probabilities. The advantages of using this entropic edge-detection method are shown; it is especially suitable when the source image of the drop is affected by any kind of noise, blur or low-contrast effect. Results reveal a better performance than other methods used in this field.

A simple and species-independent coding measure

We present a coding measure which is based on the statistical properties of the stop codons, and that is able to estimate accurately the variation of coding content along an anonymous sequence. As the stop codons play the same role in all the genomes (with very few exceptions) the measure turns out to be species-independent. We show results both for prokaryotic and for eukaryotic genomes, indicating, first, the accuracy of the measure, and, second, that better prediction is achieved if the measure is applied on homogeneous, isochore-like sequences than if it is applied following the standard moving window approach. Finally, we discuss on some of the possible applications of the measure.

Entropic minimization of multiple-valued functions

An information-theoretic procedure for minimizing multiple-valued switching function is outlined. The procedure has been developed as an extension of previous works about heuristic decision making and binary switching function minimization for the sum of products expansion of the function to be minimized. To show how the proposed procedure works, a complete example for a three-variable, four-valued function is given. In addition, certain global results for four-variable, four-valued functions are shown.<<ETX>>