17,358 research outputs found

    Prediction of protein-protein interactions using one-class classification methods and integrating diverse data

    Get PDF
    This research addresses the problem of prediction of protein-protein interactions (PPI) when integrating diverse kinds of biological information. This task has been commonly viewed as a binary classification problem (whether any two proteins do or do not interact) and several different machine learning techniques have been employed to solve this task. However the nature of the data creates two major problems which can affect results. These are firstly imbalanced class problems due to the number of positive examples (pairs of proteins which really interact) being much smaller than the number of negative ones. Secondly the selection of negative examples can be based on some unreliable assumptions which could introduce some bias in the classification results. Here we propose the use of one-class classification (OCC) methods to deal with the task of prediction of PPI. OCC methods utilise examples of just one class to generate a predictive model which consequently is independent of the kind of negative examples selected; additionally these approaches are known to cope with imbalanced class problems. We have designed and carried out a performance evaluation study of several OCC methods for this task, and have found that the Parzen density estimation approach outperforms the rest. We also undertook a comparative performance evaluation between the Parzen OCC method and several conventional learning techniques, considering different scenarios, for example varying the number of negative examples used for training purposes. We found that the Parzen OCC method in general performs competitively with traditional approaches and in many situations outperforms them. Finally we evaluated the ability of the Parzen OCC approach to predict new potential PPI targets, and validated these results by searching for biological evidence in the literature

    Thermodynamic quantum critical behavior of the Kondo necklace model

    Full text link
    We obtain the phase diagram and thermodynamic behavior of the Kondo necklace model for arbitrary dimensions dd using a representation for the localized and conduction electrons in terms of local Kondo singlet and triplet operators. A decoupling scheme on the double time Green's functions yields the dispersion relation for the excitations of the system. We show that in d3d\geq 3 there is an antiferromagnetically ordered state at finite temperatures terminating at a quantum critical point (QCP). In 2-d, long range magnetic order occurs only at T=0. The line of Neel transitions for d>2d>2 varies with the distance to the quantum critical point QCP g|g| as, TNgψT_N \propto |g|^{\psi} where the shift exponent ψ=1/(d1)\psi=1/(d-1). In the paramagnetic side of the phase diagram, the spin gap behaves as Δg\Delta\approx \sqrt{|g|} for d3d \ge 3 consistent with the value z=1z=1 found for the dynamical critical exponent. We also find in this region a power law temperature dependence in the specific heat for kBTΔk_BT\gg\Delta and along the non-Fermi liquid trajectory. For kBTΔk_BT \ll\Delta, in the so-called Kondo spin liquid phase, the thermodynamic behavior is dominated by an exponential temperature dependence.Comment: Submitted to PR

    Synchronization of Excitatory Neurons with Strongly Heterogeneous Phase Responses

    Full text link
    In many real-world oscillator systems, the phase response curves are highly heterogeneous. However, dynamics of heterogeneous oscillator networks has not been seriously addressed. We propose a theoretical framework to analyze such a system by dealing explicitly with the heterogeneous phase response curves. We develop a novel method to solve the self-consistent equations for order parameters by using formal complex-valued phase variables, and apply our theory to networks of in vitro cortical neurons. We find a novel state transition that is not observed in previous oscillator network models.Comment: 4 pages, 3 figure

    Experimentally Attainable Optimal Pulse Shapes Obtained with the Aid of Genetic Algorithms

    Full text link
    We propose a methodology to design optimal pulses for achieving quantum optimal control on molecular systems. Our approach constrains pulse shapes to linear combinations of a fixed number of experimentally relevant pulse functions. Quantum optimal control is obtained by maximizing a multi-target fitness function with genetic algorithms. As a first application of the methodology we generated an optimal pulse that successfully maximized the yield on a selected dissociation channel of a diatomic molecule. Our pulse is obtained as a linear combination of linearly chirped pulse functions. Data recorded along the evolution of the genetic algorithm contained important information regarding the interplay between radiative and diabatic processes. We performed a principal component analysis on these data to retrieve the most relevant processes along the optimal path. Our proposed methodology could be useful for performing quantum optimal control on more complex systems by employing a wider variety of pulse shape functions.Comment: 7 pages, 6 figure

    Bose-Einstein condensation in antiferromagnets close to the saturation field

    Full text link
    At zero temperature and strong applied magnetic fields the ground sate of an anisotropic antiferromagnet is a saturated paramagnet with fully aligned spins. We study the quantum phase transition as the field is reduced below an upper critical Hc2H_{c2} and the system enters a XY-antiferromagnetic phase. Using a bond operator representation we consider a model spin-1 Heisenberg antiferromagnetic with single-ion anisotropy in hyper-cubic lattices under strong magnetic fields. We show that the transition at Hc2H_{c2} can be interpreted as a Bose-Einstein condensation (BEC) of magnons. The theoretical results are used to analyze our magnetization versus field data in the organic compound NiCl2NiCl_2-4SC(NH2)24SC(NH_2)_2 (DTN) at very low temperatures. This is the ideal BEC system to study this transition since Hc2H_{c2} is sufficiently low to be reached with static magnetic fields (as opposed to pulsed fields). The scaling of the magnetization as a function of field and temperature close to Hc2H_{c2} shows excellent agreement with the theoretical predictions. It allows to obtain the quantum critical exponents and confirm the BEC nature of the transition at Hc2H_{c2}.Comment: 4 pages, 1 figure. Accepted for publication in PRB
    corecore