Structuring heterogeneous biological information using fuzzy clustering of k-partite graphs

<p>Abstract</p> <p>Background</p> <p>Extensive and automated data integration in bioinformatics facilitates the construction of large, complex biological networks. However, the challenge lies in the interpretation of these networks. While most research focuses on the unipartite or bipartite case, we address the more general but common situation of <it>k</it>-partite graphs. These graphs contain <it>k </it>different node types and links are only allowed between nodes of different types. In order to reveal their structural organization and describe the contained information in a more coarse-grained fashion, we ask how to detect clusters within each node type.</p> <p>Results</p> <p>Since entities in biological networks regularly have more than one function and hence participate in more than one cluster, we developed a <it>k</it>-partite graph partitioning algorithm that allows for overlapping (fuzzy) clusters. It determines for each node a degree of membership to each cluster. Moreover, the algorithm estimates a weighted <it>k</it>-partite graph that connects the extracted clusters. Our method is fast and efficient, mimicking the multiplicative update rules commonly employed in algorithms for non-negative matrix factorization. It facilitates the decomposition of networks on a chosen scale and therefore allows for analysis and interpretation of structures on various resolution levels. Applying our algorithm to a tripartite disease-gene-protein complex network, we were able to structure this graph on a large scale into clusters that are functionally correlated and biologically meaningful. Locally, smaller clusters enabled reclassification or annotation of the clusters' elements. We exemplified this for the transcription factor MECP2.</p> <p>Conclusions</p> <p>In order to cope with the overwhelming amount of information available from biomedical literature, we need to tackle the challenge of finding structures in large networks with nodes of multiple types. To this end, we presented a novel fuzzy <it>k</it>-partite graph partitioning algorithm that allows the decomposition of these objects in a comprehensive fashion. We validated our approach both on artificial and real-world data. It is readily applicable to any further problem.</p

Photochemical incorporation of silver quantum dots in monodisperse silica colloids for photonic crystal applications

We developed a novel method to fabricate nanocomposite monodisperse SiO2 spheres (∼ 100 nm) containing homogeneously dispersed Ag quantum dots (2∼5 nm). The inclusion morphology is controlled through the timing of the photochemical reduction of silver ions during hydrolysis of tetraethoxysilane in a microemulsion. Depending on the timing, Ag quantum dots can be directed to different annuli within the SiO2 spheres, as well as onto the SiO2 sphere surfaces. The embedded Ag quantum dots show a plasmon resonance absorption band at 438 nm. These Ag@SiO2 particles have significant surface charge and readily self-assemble into crystalline colloidal array (CCA) photonic crystals which Bragg-diffract light in the visible region. The magnitude of the plasmon resonance absorption depends on the CCA Bragg diffraction condition. The negative dielectric constant of the silver nanoparticles may be decreasing the silica-silver nanodot composite refractive index below that of the water medium. We may be observing an analogue of the Borrmann effect previously observed in X-ray scattering, where the incident and diffracted electric field standing wave becomes localized in regions of small CCA crystal absorption

Study of the Zn-containing DD-carboxypeptidase of Streptomyces albus G by small-angle X-ray scattering in solution.

Study of the Zn2+-containing D-alanyl-D-alanine-cleaving carboxypeptidase of Streptomyces albus G by small-angle X-ray scattering in solution yielded the following molecular parameters: radius of gyration R = 1.82 +/- 0.05 nm; largest diameter D = 5.9 +/- 0.2 nm; relative molecular mass Mr = 17000 +/- 2000; volume V approximately equal to 35 +/- 2 nm3; degree of hydration: 0.25 +/- 0.02 g water/g protein. By reference to theoretical scattering curves of rigid triaxial homogeneous bodies, a model which fits all experimental data is an elliptical cylinder. Such a model is compatible with that observed in the crystal structure. At those high concentrations necessary to form inactive enzyme-ligand associations the non-competitive beta-lactam inhibitors, cephalothin and cephalosporin C, drastically altered the scattering behaviour of the protein