Abstract:
Circular bacterial chromosomes have highly polarized nucleotide composition in the two replichores, and this genomic strand asymmetry can be visualized using GC skew graphs. Here we propose and discuss the GC skew index (GCSI) for the quantification of genomic compositional skew, which combines a normalized measure of fast Fourier transform to capture the shape of the skew graph and Euclidean distance between the two vertices in a cumulative skew graph to represent the degree of skew. We calculated GCSI for all available bacterial genomes, and GCSI correlated well with the visibility of GC skew. This novel index is useful for estimating confi dence levels for the prediction of replication origin and terminus by methods based on GC skew and for measuring the strength of replicational selection in a genome.

Abstract:
The natural order in the space of binary sequences permits to recover the $U$-sequence. Also the scaling laws of the period-doubling cascade and the intermittency route to chaos defined in that ordered set are explained. These arise as intrinsic properties of this ordered set, and independent from any consideration about dynamical systems.

Abstract:
The new methodology enables two results. On the one hand it shows that the entropic profiles are directly related with the statistical significance of motifs, allowing the study of under and over-representation of segments. On the other hand, by spanning the parameters of the kernel function it is possible to extract important information about the scale of each conserved DNA region. The computational applications, developed in Matlab m-code, the corresponding binary executables and additional material and examples are made publicly available at http://kdbio.inesc-id.pt/~svinga/ep/ webcite.The ability to detect local conservation from a scale-independent representation of symbolic sequences is particularly relevant for biological applications where conserved motifs occur in multiple, overlapping scales, with significant future applications in the recognition of foreign genomic material and inference of motif structures.Biological sequences are the ultimate support for the description of Biological Systems. In particular, key aspects of sequence analysis are known to play a role in integrated analysis of regulatory networks: for example in motif searching and inference.Over the last decades and more recently due to the development of a considerable number of whole genome sequencing projects, several efforts have been made to mathematically model DNA sequences. In particular from the statistical side, the use of Markov based models [1] has widespread and proven to be effective in tackling the problem of data mining of biological sequences, through variable length Markov chains [2,3], interpolated Markov models [4], fractal prediction machines [5] for symbolic time series based on Chaos Game Representations [6], to name just a few. Other algorithmic approaches based on the computational side have also proven to be useful [7]. All this effort allowed establishing important relations between the results obtained (computationally and statistically) with real biologically

Abstract:
This paper proposes a chaos-based image encryption scheme where one 3D skew tent map with three control parameters is utilized to generate chaotic orbits applied to scramble the pixel positions while one coupled map lattice is employed to yield random gray value sequences to change the gray values so as to enhance the security. Experimental results have been carried out with detailed analysis to demonstrate that the proposed image encryption scheme possesses large key space to resist brute-force attack and possesses good statistical properties to frustrate statistical analysis attacks. Experiments are also performed to illustrate the robustness against malicious attacks like cropping, noising, JPEG compression.

Abstract:
Our study confirmed a significant GC-skew (C > G) in the TSS of Oryza sativa (rice) genes. The full-length cDNAs and genomic sequences from Arabidopsis and rice were compared using statistical analyses. Despite marked differences in the G+C content around the TSS in the two plants, the degrees of bias were almost identical. Although slight GC-skew peaks, including opposite skews (C < G), were detected around the TSS of genes in human and Drosophila, they were qualitatively and quantitatively different from those identified in plants. However, plant-like GC-skew in regions upstream of the translation initiation sites (TIS) in some fungi was identified following analyses of the expressed sequence tags and/or genomic sequences from other species. On the basis of our dataset, we estimated that >70 and 68% of Arabidopsis and rice genes, respectively, had a strong GC-skew (>0.33) in a 100-bp window (that is, the number of C residues was more than double the number of G residues in a +/-100-bp window around the TSS). The mean GC-skew value in the TSS of highly-expressed genes in Arabidopsis was significantly greater than that of genes with low expression levels. Many of the GC-skew peaks were preferentially located near the TSS, so we examined the potential value of GC-skew as an index for TSS identification. Our results confirm that the GC-skew can be used to assist the TSS prediction in plant genomes.The GC-skew (C > G) around the TSS is strictly conserved between monocot and eudicot plants (ie. angiosperms in general), and a similar skew has been observed in some fungi. Highly-expressed Arabidopsis genes had overall a more marked GC-skew in the TSS compared to genes with low expression levels. We therefore propose that the GC-skew around the TSS in some plants and fungi is related to transcription. It might be caused by mutations during transcription initiation or the frequent use of transcription factor-biding sites having a strand preference. In addition, GC-skew is a

Abstract:
Among all insect genomes, honeybee displays one of the most unusual patterns with interspersed long AT and GC-rich segments. Nearly 75% of the protein-coding genes are located in the AT-rich segments of the genome, but the biological significance of the GC-rich regions is not well understood. Based on an observation that the bee miRNAs, actins and tubulins are located in the GC-rich segments, this work investigated whether other highly conserved genomic regions show similar preferences. Sequences ultraconserved between the genomes of honeybee and Nasonia, another hymenopteran insect, were determined. They showed strong preferences towards locating in the GC-rich regions of the bee genome.

Abstract:
Maximal green sequences are particular sequences of mutations which were introduced by Keller in the context of quantum dilogarithm identities and independently by Cecotti-Cordova-Vafa in the context of supersymmetric gauge theory. In this paper, we show that skew-symmetrizable 3x3 matrices with a mutation-cyclic diagram do not have any maximal green sequences. We also obtain some properties of maximal green sequences of skew-symmetrizable 3x3 matrices with mutation-acyclic diagrams.

Abstract:
A classification scheme based on the melting profile of DNA sequences simulated thermal melting profiles. This method was applied in the classification of (a) several species of mammalian - β globin and (b) α-chain class II MHC genes. Comparison of the thermal melting profile with the molecular phylogenetic trees constructed using the sequences shows that the melting temperature based approach is able to reproduce most of the major features of the sequence based evolutionary tree. Melting profile method takes into account the inherent structure and dynamics of the DNA molecule, does not require sequence alignment prior to tree construction, and provides a means to verify the results experimentally. Therefore our results show that melting profile based classification of DNA sequences could be a useful tool for sequence analysis.

Abstract:
Here we discuss a quantitative index for the measurement of GC skew strength, named the generalised GC skew index (gGCSI), which is applicable to genomes of any length, including bacterial chromosomes and plasmids. We demonstrate that gGCSI is independent of the window size and can thus be used to compare genomes with different sizes, such as bacterial chromosomes and plasmids. It can suggest the existence of different replication mechanisms in archaea and of rolling-circle replication in plasmids. Correlation of gGCSI values between plasmids and their corresponding host chromosomes suggests that within the same strain, these replicons have reproduced using the same replication machinery and thus exhibit similar strengths of replication strand skew.gGCSI can be applied to genomes of any length and thus allows comparative study of replication-related mutation and selection pressures in genomes of different lengths such as bacterial chromosomes and plasmids. Using gGCSI, we showed that replication-related mutation or selection pressure is similar for replicons with similar machinery.DNA replication makes up a significant proportion of the bacterial cell cycle, especially in fast-growing bacteria where chromosomes undergo multiple rounds of replication in order to compensate for a short generation time [1]. Therefore, bacterial chromosomes are structured by the requirement to be an efficient medium for replication [2]. Eubacterial species typically have circular chromosomes that are partitioned into two replichores by one finite set of a symmetrically located replication origin and terminus [3]. Accordingly, many genomic features exhibit characteristic replication-related organisation, including the nucleotide compositional bias, distribution of signal oligonucleotides such as Chi sites [4,5] and KOPS motifs [6,7], as well as gene positioning and strand preference [8]. Nucleotide compositional asymmetry in the leading and lagging strands has been extensively studied us

Abstract:
The existing chaos optimization algorithms were almost based on Logistic map.However,the probability density function of chaotic sequences for Logistic map is a Chebyshev-type function,which may affect the global searching capacity and computational efficiency of chaos optimization algorithm.Firstly,a new chaotic sequences-Skew Tent map is established in this paper,and is improved by its iterative optimization property.The chaotic performance of Skew Tent map is then discussed by eliminating the bad points during the chaos searching.A hybrid optimization algorithm,in which the improved chaotic map is combined with the Alopex heuristic algorithm,is also proposed by making full use of the properties of the rapid search capability of Alopex algorithm and the global optimization of improved chaotic map.The convergence speed and global optimal value of the presented algorithm are thus improved.Finally,the simulation examples show the effectiveness of the algorithm,as well as the practicability of Skew Tent map.