Bayesian correlated clustering to integrate multiple datasets.

MOTIVATION: The integration of multiple datasets remains a key challenge in systems biology and genomic medicine. Modern high-throughput technologies generate a broad array of different data types, providing distinct-but often complementary-information. We present a Bayesian method for the unsupervised integrative modelling of multiple datasets, which we refer to as MDI (Multiple Dataset Integration). MDI can integrate information from a wide range of different datasets and data types simultaneously (including the ability to model time series data explicitly using Gaussian processes). Each dataset is modelled using a Dirichlet-multinomial allocation (DMA) mixture model, with dependencies between these models captured through parameters that describe the agreement among the datasets. RESULTS: Using a set of six artificially constructed time series datasets, we show that MDI is able to integrate a significant number of datasets simultaneously, and that it successfully captures the underlying structural similarity between the datasets. We also analyse a variety of real Saccharomyces cerevisiae datasets. In the two-dataset case, we show that MDI's performance is comparable with the present state-of-the-art. We then move beyond the capabilities of current approaches and integrate gene expression, chromatin immunoprecipitation-chip and protein-protein interaction data, to identify a set of protein complexes for which genes are co-regulated during the cell cycle. Comparisons to other unsupervised data integration techniques-as well as to non-integrative approaches-demonstrate that MDI is competitive, while also providing information that would be difficult or impossible to extract using other methods.

Detecting bipedal motion from correlated probabilistic trajectories

This paper is about detecting bipedal motion in video sequences by using point trajectories in a framework of classification. Given a number of point trajectories, we find a subset of points which are arising from feet in bipedal motion by analysing their spatio-temporal correlation in a pairwise fashion. To this end, we introduce probabilistic trajectories as our new features which associate each point over a sufficiently long time period in the presence of noise. They are extracted from directed acyclic graphs whose edges represent temporal point correspondences and are weighted with their matching probability in terms of appearance and location. The benefit of the new representation is that it practically tolerates inherent ambiguity for example due to occlusions. We then learn the correlation between the motion of two feet using the probabilistic trajectories in a decision forest classifier. The effectiveness of the algorithm is demonstrated in experiments on image sequences captured with a static camera, and extensions to deal with a moving camera are discussed. © 2013 Elsevier B.V. All rights reserved.

Current-voltage characteristics in strongly correlated double quantum dots

We have studied the current-voltage properties of a double quantum dot (DQD) connected by leads in arrangements that vary from series to symmetrical parallel configurations, in the presence of strong intradot Coulomb interaction. The influences of the connecting configurations and the difference between dot levels on the magnitude and symmetry of the total current are examined. We find that the connecting configurations of the dots can determine the number of the current paths and in turn determine the magnitude of the current, while the coupling strengths between the dots and the leads together with the difference of dot levels determine the current-voltage symmetry. The negative differential conductance observed in serial DQD can be explained in terms of the reduction of the current paths. (c) 2005 American Institute of Physics.

Correlated structural and optical investigation of terbium-doped zinc oxide nanocrystals

Tb3+-doped zinc oxide nanocrystals with a hexagonal wurzite structure were successfully prepared by reaction between Zn-O-Tb precursors and LiOH in ethanol. Good incorporation of Tb3+ in ZnO nanocrystals is proved by XRD, FTIR, PL and PLE measurements. The presence of acetate complexes to zinc atoms on particle surfaces is disclosed by FTIR results. Emission from both Tb3+ ions and surface states in ZnO matrix, as well as their correlation were observed. The luminescence mechanism is discussed. (C) 2000 Elsevier Science B.V. All rights reserved.

Photoluminescence and Raman scattering correlated study of boron-doped silicon nanowires

Boron-doped (B-doped) silicon nanowires (SiNWS) have been prepared and characterized by Raman scattering and photoluminescence (PL). B-doped SiNWS were grown by plasma enhanced chemical vapor deposition (PECVD), using diborane (B2H6) as the dopant gas. Raman spectra show a band at 480cm(-1),which is attributed to amorphous silicon. Photoluminescence at room temperature exhibits three distinct emission peaks at 1.34ev, 1.42ev, 1.47ev. Possible reason for these is suggested.

Experimental study of two-proton correlated emission from S-29 excited states

An experiment of a S-29 beam bombarding a Au-197 target at an energy of 49.2 MeV/u has been performed to study the two-proton correlated emission from S-29 excited states. Complete-kinematics measurements were carried out in the experiment. The relative momentum, opening angle, and relative energy of two protons, as well as the invariant mass of the final system, were deduced by relativistic-kinematics reconstruction. The Si-27-p-p coincident events were picked out under strict conditions and the phenomenon of p-p correlations was observed among these events. The mechanisms of two-proton emission were analyzed in a simple schematic model, in which the extreme decay modes like He-2 cluster emission, three-body phase-space decay, and two-body sequential emission were taken into account. Associated with the Monte Carlo simulations, the present results show that two protons emitted from the excited states between 9.6 MeV and 10.4 MeV exhibit the features of He-2 cluster decay with a branching ratio of 29(-11)(+10)%.

Fano effect on shot noise through a Kondo-correlated quantum dot

Transport in a semiopen Kondo- correlated quantum dot is mediated through more than one quantum state. Using the Keldysh technique and the equation of motion method, we study the shot noise S for a wide range of source- drain voltages V-sd within a model incorporating the additional states as a background continuum, demonstrating the importance of the Fano interference. In the absence of the interference, the noise is revealed to be a probe of the second moment of the local density of states, and our theory reproduces the well- known peak structure around the Kondo temperature in the S-V-sd curve. More significantly, it is found that taking account of the background transmission, the voltage dependence of the noise exhibits rich peak- dip line shapes, indicating the presence of the Fano effect. We further demonstrate that due to its two- particle nature, the noise is more sensitive to the quantum interference effect than the simple current.