Like-charge attraction through hydrodynamic interaction

We demonstrate that the attractive interaction measured between like-charged colloidal spheres near a wall can be accounted for by a nonequilibrium hydrodynamic effect. We present both analytical results and Brownian dynamics simulations which quantitatively capture the one-wall experiments of Larsen and Grier (Nature 385, p. 230, 1997).Comment: 10 pages, 4 figure

Radiation as a tool to remove selective marker genes from transgenic soybean plants.

Made available in DSpace on 2018-06-05T00:37:42Z (GMT). No. of bitstreams: 1 ID275331.pdf: 911597 bytes, checksum: 0e111388a7fd3d25c04408432fa297d0 (MD5) Previous issue date: 2006-11-1

Data mining with neural networks and support vector machines using the R/rminer tool

We present rminer, our open source library for the R tool that facilitates the use of data mining (DM) algorithms, such as neural Networks (NNs) and support vector machines (SVMs), in classification and regression tasks. Tutorial examples with real-world problems (i.e. satellite image analysis and prediction of car prices) were used to demonstrate the rminer capabilities and NN/SVM advantages. Additional experiments were also held to test the rminer predictive capabilities, revealing competitive performances.Fundação para a Ciência e a Tecnologia (FCT) - PTDC/EIA/64541/200

Statistical mechanics of RNA folding: a lattice approach

We propose a lattice model for RNA based on a self-interacting two-tolerant trail. Self-avoidance and elements of tertiary structure are taken into account. We investigate a simple version of the model in which the native state of RNA consists of just one hairpin. Using exact arguments and Monte Carlo simulations we determine the phase diagram for this case. We show that the denaturation transition is first order and can either occur directly or through an intermediate molten phase.Comment: 8 pages, 9 figure

Zero Temperature Properties of RNA Secondary Structures

We analyze different microscopic RNA models at zero temperature. We discuss both the most simple model, that suffers a large degeneracy of the ground state, and models in which the degeneracy has been remove, in a more or less severe manner. We calculate low-energy density of states using a coupling perturbing method, where the ground state of a modified Hamiltonian, that repels the original ground state, is determined. We evaluate scaling exponents starting from measurements of overlaps and energy differences. In the case of models without accidental degeneracy of the ground state we are able to clearly establish the existence of a glassy phase with $\theta \simeq 1/3$.Comment: 20 pages including 9 eps figure

Statistical mechanics of secondary structures formed by random RNA sequences

The formation of secondary structures by a random RNA sequence is studied as a model system for the sequence-structure problem omnipresent in biopolymers. Several toy energy models are introduced to allow detailed analytical and numerical studies. First, a two-replica calculation is performed. By mapping the two-replica problem to the denaturation of a single homogeneous RNA in 6-dimensional embedding space, we show that sequence disorder is perturbatively irrelevant, i.e., an RNA molecule with weak sequence disorder is in a molten phase where many secondary structures with comparable total energy coexist. A numerical study of various models at high temperature reproduces behaviors characteristic of the molten phase. On the other hand, a scaling argument based on the extremal statistics of rare regions can be constructed to show that the low temperature phase is unstable to sequence disorder. We performed a detailed numerical study of the low temperature phase using the droplet theory as a guide, and characterized the statistics of large-scale, low-energy excitations of the secondary structures from the ground state structure. We find the excitation energy to grow very slowly (i.e., logarithmically) with the length scale of the excitation, suggesting the existence of a marginal glass phase. The transition between the low temperature glass phase and the high temperature molten phase is also characterized numerically. It is revealed by a change in the coefficient of the logarithmic excitation energy, from being disorder dominated to entropy dominated.Comment: 24 pages, 16 figure