Hypernetwork functional image representation

Motivated by the human way of memorizing images we introduce their functional representation, where an image is represented by a neural network. For this purpose, we construct a hypernetwork which takes an image and returns weights to the target network, which maps point from the plane (representing positions of the pixel) into its corresponding color in the image. Since the obtained representation is continuous, one can easily inspect the image at various resolutions and perform on it arbitrary continuous operations. Moreover, by inspecting interpolations we show that such representation has some properties characteristic to generative models. To evaluate the proposed mechanism experimentally, we apply it to image super-resolution problem. Despite using a single model for various scaling factors, we obtained results comparable to existing super-resolution methods

Evaluation of clustering algorithms for gene expression data

BACKGROUND: Cluster analysis is an integral part of high dimensional data analysis. In the context of large scale gene expression data, a filtered set of genes are grouped together according to their expression profiles using one of numerous clustering algorithms that exist in the statistics and machine learning literature. A closely related problem is that of selecting a clustering algorithm that is "optimal" in some sense from a rather impressive list of clustering algorithms that currently exist. RESULTS: In this paper, we propose two validation measures each with two parts: one measuring the statistical consistency (stability) of the clusters produced and the other representing their biological functional congruence. Smaller values of these indices indicate better performance for a clustering algorithm. We illustrate this approach using two case studies with publicly available gene expression data sets: one involving a SAGE data of breast cancer patients and the other involving a time course cDNA microarray data on yeast. Six well known clustering algorithms UPGMA, K-Means, Diana, Fanny, Model-Based and SOM were evaluated. CONCLUSION: No single clustering algorithm may be best suited for clustering genes into functional groups via expression profiles for all data sets. The validation measures introduced in this paper can aid in the selection of an optimal algorithm, for a given data set, from a collection of available clustering algorithms

A novel approach to the clustering of microarray data via nonparametric density estimation

<p>Abstract</p> <p>Background</p> <p>Cluster analysis is a crucial tool in several biological and medical studies dealing with microarray data. Such studies pose challenging statistical problems due to dimensionality issues, since the number of variables can be much higher than the number of observations.</p> <p>Results</p> <p>Here, we present a general framework to deal with the clustering of microarray data, based on a three-step procedure: (i) gene filtering; (ii) dimensionality reduction; (iii) clustering of observations in the reduced space. Via a nonparametric model-based clustering approach we obtain promising results both in simulated and real data.</p> <p>Conclusions</p> <p>The proposed algorithm is a simple and effective tool for the clustering of microarray data, in an unsupervised setting.</p

Special phase transformation and crystal growth pathways observed in nanoparticles†

Phase transformation and crystal growth in nanoparticles may happen via mechanisms distinct from those in bulk materials. We combine experimental studies of as-synthesized and hydrothermally coarsened titania (TiO(2)) and zinc sulfide (ZnS) with thermodynamic analysis, kinetic modeling and molecular dynamics (MD) simulations. The samples were characterized by transmission electron microscopy, X-ray diffraction, synchrotron X-ray absorption and scattering, and UV-vis spectroscopy. At low temperatures, phase transformation in titania nanoparticles occurs predominantly via interface nucleation at particle–particle contacts. Coarsening and crystal growth of titania nanoparticles can be described using the Smoluchowski equation. Oriented attachment-based crystal growth was common in both hydrothermal solutions and under dry conditions. MD simulations predict large structural perturbations within very fine particles, and are consistent with experimental results showing that ligand binding and change in aggregation state can cause phase transformation without particle coarsening. Such phenomena affect surface reactivity, thus may have important roles in geochemical cycling

Biclustering models for two-mode ordinal data

The work in this paper introduces finite mixture models that can be used to simul- taneously cluster the rows and columns of two-mode ordinal categorical response data, such as those resulting from Likert scale responses. We use the popular proportional odds parameterisation and propose models which provide insights into major patterns in the data. Model-fitting is performed using the EM algorithm and a fuzzy allocation of rows and columns to corresponding clusters is obtained. The clustering ability of the models is evaluated in a simulation study and demonstrated using two real data sets

Might Depression, Psychosocial Adversity, and Limited Social Assets Explain Vulnerability to and Resistance against Violent Radicalisation?

BACKGROUND: This study tests whether depression, psychosocial adversity, and limited social assets offer protection or suggest vulnerability to the process of radicalisation. METHODS: A population sample of 608 men and women of Pakistani or Bangladeshi origin, of Muslim heritage, and aged 18-45 were recruited by quota sampling. Radicalisation was measured by 16 questions asking about sympathies for violent protest and terrorism. Cluster analysis of the 16 items generated three groups: most sympathetic (or most vulnerable), most condemning (most resistant), and a large intermediary group that acted as a reference group. Associations were calculated with depression (PHQ9), anxiety (GAD7), poor health, and psychosocial adversity (adverse life events, perceived discrimination, unemployment). We also investigated protective factors such as the number social contacts, social capital (trust, satisfaction, feeling safe), political engagement and religiosity. RESULTS: Those showing the most sympathy for violent protest and terrorism were more likely to report depression (PHQ9 score of 5 or more; RR = 5.43, 1.35 to 21.84) and to report religion to be important (less often said religion was fairly rather than very important; RR = 0.08, 0.01 to 0.48). Resistance to radicalisation measured by condemnation of violent protest and terrorism was associated with larger number of social contacts (per contact: RR = 1.52, 1.26 to 1.83), less social capital (RR = 0.63, 0.50 to 0.80), unavailability for work due to housekeeping or disability (RR = 8.81, 1.06 to 37.46), and not being born in the UK (RR = 0.22, 0.08 to 0.65). CONCLUSIONS: Vulnerability to radicalisation is characterised by depression but resistance to radicalisation shows a different profile of health and psychosocial variables. The paradoxical role of social capital warrants further investigation

Knee-clicks and visual traits indicate fighting ability in eland antelopes: multiple messages and back-up signals

Abstract Background Given the costs of signalling, why do males often advertise their fighting ability to rivals using several signals rather than just one? Multiple signalling theories have developed largely in studies of sexual signals, and less is known about their applicability to intra-sexual communication. We here investigate the evolutionary basis for the intricate agonistic signalling system in eland antelopes, paying particular attention to the evolutionary phenomenon of loud knee-clicking. Results A principal components analysis separated seven male traits into three groups. The dominant frequency of the knee-clicking sound honestly indicated body size, a main determinant of fighting ability. In contrast, the dewlap size increased with estimated age rather than body size, suggesting that, by magnifying the silhouette of older bulls disproportionately, the dewlap acts as an indicator of age-related traits such as fighting experience. Facemask darkness, frontal hairbrush size and body greyness aligned with a third underlying variable, presumed to be androgen-related aggression. A longitudinal study provided independent support of these findings. Conclusion The results show that the multiple agonistic signals in eland reflect three separate components of fighting ability: (1) body size, (2) age and (3) presumably androgen-related aggression, which is reflected in three backup signals. The study highlights how complex agonistic signalling systems can evolve through the simultaneous action of several selective forces, each of which favours multiple signals. Specifically, loud knee-clicking is discovered to be an honest signal of body size, providing an exceptional example of the potential for non-vocal acoustic communication in mammals.</p

Elastic Maps and Nets for Approximating Principal Manifolds and Their Application to Microarray Data Visualization

Principal manifolds are defined as lines or surfaces passing through ``the middle'' of data distribution. Linear principal manifolds (Principal Components Analysis) are routinely used for dimension reduction, noise filtering and data visualization. Recently, methods for constructing non-linear principal manifolds were proposed, including our elastic maps approach which is based on a physical analogy with elastic membranes. We have developed a general geometric framework for constructing ``principal objects'' of various dimensions and topologies with the simplest quadratic form of the smoothness penalty which allows very effective parallel implementations. Our approach is implemented in three programming languages (C++, Java and Delphi) with two graphical user interfaces (VidaExpert http://bioinfo.curie.fr/projects/vidaexpert and ViMiDa http://bioinfo-out.curie.fr/projects/vimida applications). In this paper we overview the method of elastic maps and present in detail one of its major applications: the visualization of microarray data in bioinformatics. We show that the method of elastic maps outperforms linear PCA in terms of data approximation, representation of between-point distance structure, preservation of local point neighborhood and representing point classes in low-dimensional spaces.Comment: 35 pages 10 figure

A “Coiled-Coil” Motif Is Important for Oligomerization and DNA Binding Properties of Human Cytomegalovirus Protein UL77

Human cytomegalovirus (HCMV) UL77 gene encodes the essential protein UL77, its function is characterized in the present study. Immunoprecipitation identified monomeric and oligomeric pUL77 in HCMV infected cells. Immunostaining of purified virions and subviral fractions showed that pUL77 is a structural protein associated with capsids. In silico analysis revealed the presence of a coiled-coil motif (CCM) at the N-terminus of pUL77. Chemical cross-linking of either wild-type pUL77 or CCM deletion mutant (pUL77ΔCCM) implicated that CCM is critical for oligomerization of pUL77. Furthermore, co-immunoprecipitations of infected and transfected cells demonstrated that pUL77 interacts with the capsid-associated DNA packaging motor components, pUL56 and pUL104, as well as the major capsid protein. The ability of pUL77 to bind dsDNA was shown by an in vitro assay. Binding to certain DNA was further confirmed by an assay using biotinylated 36-, 250-, 500-, 1000-meric dsDNA and 966-meric HCMV-specific dsDNA designed for this study. The binding efficiency (BE) was determined by image processing program defining values above 1.0 as positive. While the BE of the pUL56 binding to the 36-mer bio-pac1 containing a packaging signal was 10.0±0.63, the one for pUL77 was only 0.2±0.03. In contrast to this observation the BE of pUL77 binding to bio-500 bp or bio-1000 bp was 2.2±0.41 and 4.9±0.71, respectively. By using pUL77ΔCCM it was demonstrated that this protein could not bind to dsDNA. These data indicated that pUL77 (i) could form homodimers, (ii) CCM of pUL77 is crucial for oligomerization and (iii) could bind to dsDNA in a sequence independent manner