Integration of relational and hierarchical network information for protein function prediction

BACKGROUND:In the current climate of high-throughput computational biology, the inference of a protein's function from related measurements, such as protein-protein interaction relations, has become a canonical task. Most existing technologies pursue this task as a classification problem, on a term-by-term basis, for each term in a database, such as the Gene Ontology (GO) database, a popular rigorous vocabulary for biological functions. However, ontology structures are essentially hierarchies, with certain top to bottom annotation rules which protein function predictions should in principle follow. Currently, the most common approach to imposing these hierarchical constraints on network-based classifiers is through the use of transitive closure to predictions.RESULTS:We propose a probabilistic framework to integrate information in relational data, in the form of a protein-protein interaction network, and a hierarchically structured database of terms, in the form of the GO database, for the purpose of protein function prediction. At the heart of our framework is a factorization of local neighborhood information in the protein-protein interaction network across successive ancestral terms in the GO hierarchy. We introduce a classifier within this framework, with computationally efficient implementation, that produces GO-term predictions that naturally obey a hierarchical 'true-path' consistency from root to leaves, without the need for further post-processing.CONCLUSION:A cross-validation study, using data from the yeast Saccharomyces cerevisiae, shows our method offers substantial improvements over both standard 'guilt-by-association' (i.e., Nearest-Neighbor) and more refined Markov random field methods, whether in their original form or when post-processed to artificially impose 'true-path' consistency. Further analysis of the results indicates that these improvements are associated with increased predictive capabilities (i.e., increased positive predictive value), and that this increase is consistent uniformly with GO-term depth. Additional in silico validation on a collection of new annotations recently added to GO confirms the advantages suggested by the cross-validation study. Taken as a whole, our results show that a hierarchical approach to network-based protein function prediction, that exploits the ontological structure of protein annotation databases in a principled manner, can offer substantial advantages over the successive application of 'flat' network-based methods.

Neural Models of Motion Integration, Segmentation, and Probablistic Decision-Making

When brain mechanism carry out motion integration and segmentation processes that compute unambiguous global motion percepts from ambiguous local motion signals? Consider, for example, a deer running at variable speeds behind forest cover. The forest cover is an occluder that creates apertures through which fragments of the deer's motion signals are intermittently experienced. The brain coherently groups these fragments into a trackable percept of the deer in its trajectory. Form and motion processes are needed to accomplish this using feedforward and feedback interactions both within and across cortical processing streams. All the cortical areas V1, V2, MT, and MST are involved in these interactions. Figure-ground processes in the form stream through V2, such as the seperation of occluding boundaries of the forest cover from the boundaries of the deer, select the motion signals which determine global object motion percepts in the motion stream through MT. Sparse, but unambiguous, feauture tracking signals are amplified before they propogate across position and are intergrated with far more numerous ambiguous motion signals. Figure-ground and integration processes together determine the global percept. A neural model predicts the processing stages that embody these form and motion interactions. Model concepts and data are summarized about motion grouping across apertures in response to a wide variety of displays, and probabilistic decision making in parietal cortex in response to random dot displays.

Vaccinia virus assembly and motility

Vaccinia virus, the prototype member of the orthopoxviruses, is the largest and the most complex virus known. After replication of its genome and expression of the viral proteins, vaccinia undergoes a complicated assembly process which produces two distinct infectious forms. The first of these, the intracellular mature virus (IMV), develops from the immature virion (IV) after packaging of the genome and cleavage of the core proteins. During the transition of the IV to the IMV, a new core structure develops in the centre of the virion, concomitantly with the appearance of spike-like structures which extend between this core and the surrounding membranes of the IMV. I describe the characterization of p39 (gene A4L) which is hypothesized to be one component of these spikes. p39 is a core protein, but has strong associations with the membranes surrounding the IMV, possibly due to an interaction with p21 (A17L). Due to its location between the core and the membranes of the IMV, p39 is ideally situated to act as a matrix-like linker protein and may play a role in the formation of the core during the transition of the IV to the IMV. The IMV is subsequently wrapped by a membrane cisterna derived from the trans Golgi network, to form the intracellular enveloped virus (IEV). I show that the IEV can co-opt the actin cytoskeleton of the host cell in order to induce the formation of actin tails which extend from one side of the virion. These actin tails propel the virus particle, both intra- and intercellularly, at speeds of up to 2.8µm/min. On reaching the plasma membrane, the virus particles project out from the cell surface at the tip of virally induced microvilli. The outer membrane of the IEV is thought to fuse with the plasma membrane at the tip of these projections, thus exposing the second infectious form of vaccinia. This is thought to be the means by which the cell-associated enveloped virus is presented to neighbouring cells, thereby facilitating the direct cell-to-cell spread of virus particles.

Grid integration of wave energy & generic modelling of ocean devices for power system studies

The work presented in this thesis covers four major topics of research related to the grid integration of wave energy. More specifically, the grid impact of a wave farm on the power quality of its local network is investigated. Two estimation methods were developed regarding the flicker level Pst generated by a wave farm in relation to its rated power as well as in relation to the impedance angle ψk of the node in the grid to which it is connected. The electrical design of a typical wave farm design is also studied in terms of minimum rating for three types of costly pieces of equipment, namely the VAr compensator, the submarine cables and the overhead line. The power losses dissipated within the farm's electrical network are also evaluated. The feasibility of transforming a test site into a commercial site of greater rated power is investigated from the perspective of power quality and of cables and overhead line thermal loading. Finally, the generic modelling of ocean devices, referring here to both wave and tidal current devices, is investigated.

Hybrid integration and packaging of grating-coupled silicon photonics

This thesis covers both the packaging of silicon photonic devices with fiber inputs and outputs as well as the integration of laser light sources with these same devices. The principal challenge in both of these pursuits is coupling light into the submicrometer waveguides that are the hallmark of silicon-on-insulator (SOI) systems. Previous work on grating couplers is leveraged to design new approaches to bridge the gap between the highly-integrated domain of silicon, the Interconnected world of fiber and the active region of III-V materials. First, a novel process for the planar packaging of grating couplers with fibers is explored in detail. This technology allows the creation of easy-to-use test platforms for laser integration and also stands on its own merits as an enabling technology for next-generation silicon photonics systems. The alignment tolerances of this process are shown to be well-suited to a passive alignment process and for wafer-scale assembly. Furthermore, this technology has already been used to package demonstrators for research partners and is included in the offerings of the ePIXfab silicon photonics foundry and as a design kit for PhoeniX Software’s MaskEngineer product. After this, a process for hybridly integrating a discrete edge-emitting laser with a silicon photonic circuit using near-vertical coupling is developed and characterized. The details of the various steps of the design process are given, including mechanical, thermal, optical and electrical steps. The interrelation of these design domains is also discussed. The construction process for a demonstrator is outlined, and measurements are presented of a series of single-wavelength Fabry-Pérot lasers along with a two-section laser tunable in the telecommunications C-band. The suitability and potential of this technology for mass manufacture is demonstrated, with further opportunities for improvement detailed and discussed in the conclusion.