8 resultados para Two dimensions

em National Center for Biotechnology Information - NCBI


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For the past two decades, all two-dimensional systems of electrons were believed to be insulating in the limit of zero temperature. Recent experiments provide evidence for an unexpected transition to a conducting phase at very low electron densities. The nature of this phase is not understood and is currently the focus of intense theoretical and experimental attention.

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The present study explores a “hydrophobic” energy function for folding simulations of the protein lattice model. The contribution of each monomer to conformational energy is the product of its “hydrophobicity” and the number of contacts it makes, i.e., E(h⃗, c⃗) = −Σi=1N cihi = −(h⃗.c⃗) is the negative scalar product between two vectors in N-dimensional cartesian space: h⃗ = (h1, … , hN), which represents monomer hydrophobicities and is sequence-dependent; and c⃗ = (c1, … , cN), which represents the number of contacts made by each monomer and is conformation-dependent. A simple theoretical analysis shows that restrictions are imposed concomitantly on both sequences and native structures if the stability criterion for protein-like behavior is to be satisfied. Given a conformation with vector c⃗, the best sequence is a vector h⃗ on the direction upon which the projection of c⃗ − c̄⃗ is maximal, where c̄⃗ is the diagonal vector with components equal to c̄, the average number of contacts per monomer in the unfolded state. Best native conformations are suggested to be not maximally compact, as assumed in many studies, but the ones with largest variance of contacts among its monomers, i.e., with monomers tending to occupy completely buried or completely exposed positions. This inside/outside segregation is reflected on an apolar/polar distribution on the corresponding sequence. Monte Carlo simulations in two dimensions corroborate this general scheme. Sequences targeted to conformations with large contact variances folded cooperatively with thermodynamics of a two-state transition. Sequences targeted to maximally compact conformations, which have lower contact variance, were either found to have degenerate ground state or to fold with much lower cooperativity.

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Many systems in chemistry, biology, finance, and social sciences present emerging features that are not easy to guess from the elementary interactions of their microscopic individual components. In the past, the macroscopic behavior of such systems was modeled by assuming that the collective dynamics of microscopic components can be effectively described collectively by equations acting on spatially continuous density distributions. It turns out that, to the contrary, taking into account the actual individual/discrete character of the microscopic components of these systems is crucial for explaining their macroscopic behavior. In fact, we find that in conditions in which the continuum approach would predict the extinction of all of the population (respectively the vanishing of the invested capital or the concentration of a chemical substance, etc.), the microscopic granularity insures the emergence of macroscopic localized subpopulations with collective adaptive properties that allow their survival and development. In particular it is found that in two dimensions “life” (the localized proliferating phase) always prevails.

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The energy of DNA deformation plays a crucial and active role in its packaging and its function in the cell. Considerable effort has gone into developing methodologies capable of evaluating the local sequence-directed curvature and flexibility of a DNA chain. These studies thus far have focused on DNA constructs expressly tailored either with anomalous flexibility or curvature tracts. Here we demonstrate that these two structural properties can be mapped also along the chain of a “natural” DNA with any sequence on the basis of its scanning force microscope (SFM) images. To know the orientation of the sequence of the investigated DNA molecules in their SFM images, we prepared a palindromic dimer of the long DNA molecule under study. The palindromic symmetry also acted as an internal gauge of the statistical significance of the analysis carried out on the SFM images of the dimer molecules. It was found that although the curvature modulus is not efficient in separating static and dynamic contributions to the curvature of the population of molecules, the curvature taken with its direction (its sign in two dimensions) permits the direct separation of the intrinsic curvature from the flexibility contributions. The sequence-dependent flexibility seems to vary monotonically with the chain's intrinsic curvature; the chain rigidity was found to modulate as its local thermodynamic stability and does not correlate with the dinucleotide chain rigidities evaluation made from x-ray data by other authors.

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The world contains boundaries (e.g., continental edge for terrestrial taxa) that impose geometric constraints on the distribution of species ranges. Thus, contrary to traditional thinking, the expected species richness pattern in absence of ecological or physiographical factors is unlikely to be uniform. Species richness has been shown to peak in the middle of a bounded one-dimensional domain, even in the absence of ecological or physiographical factors. Because species ranges are not linear, an extension of the approach to two dimensions is necessary. Here we present a two-dimensional null model accounting for effects of geometric constraints. We use the model to examine the effects of continental edge on the distribution of terrestrial animals in Africa and compare the predictions with the observed pattern of species richness in birds endemic to the continent. Latitudinal, longitudinal, and two-dimensional patterns of species richness are predicted well from the modeled null effects alone. As expected, null effects are of high significance for wide ranging species only. Our results highlight the conceptual significance of an until recently neglected constraint from continental shape alone and support a more cautious analysis of species richness patterns at this scale.

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We present a shape-recovery technique in two dimensions and three dimensions with specific applications in modeling anatomical shapes from medical images. This algorithm models extremely corrugated structures like the brain, is topologically adaptable, and runs in O(N log N) time, where N is the total number of points in the domain. Our technique is based on a level set shape-recovery scheme recently introduced by the authors and the fast marching method for computing solutions to static Hamilton-Jacobi equations.

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We have implemented an approach for the detection of DNA alterations in cancer by means of computerized analysis of end-labeled genomic fragments, separated in two dimensions. Analysis of two-dimensional patterns of neuroblastoma tumors, prepared by first digesting DNA with the methylation-sensitive restriction enzyme Not I, yielded a multicopy fragment which was detected in some tumor patterns but not in normal controls. Cloning and sequencing of the fragment, isolated from two-dimensional gels, yielded a sequence with a strong homology to a subtelomeric sequence in chimpanzees and which was previously reported to be undetectable in humans. Fluorescence in situ hybridization indicated the occurrence of this sequence in normal tissue, for the most part in the satellite regions of acrocentric chromosomes. A product containing this sequence was obtained by telomere-anchored PCR using as a primer an oligonucleotide sequence from the cloned fragment. Our data suggest demethylation of cytosines at the cloned Not I site and in neighboring DNA in some tumors, compared with normal tissue, and suggest a greater similarity between human and chimpanzee subtelomeric sequences than was previously reported.

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The development of complex states of fluid motion is illustrated by reviewing a series of experiments, emphasizing film flows, surface waves, and thermal convection. In one dimension, cellular patterns bifurcate to states of spatiotemporal chaos. In two dimensions, even ordered patterns can be surprisingly intricate when quasiperiodic patterns are included. Spatiotemporal chaos is best characterized statistically, and methods for doing so are evolving. Transport and mixing phenomena can also lead to spatial complexity, but the degree depends on the significance of molecular or thermal diffusion.