Modelling biomolecules through atomistic graphs: theory, implementation, and applications

Describing biological molecules through computational models enjoys ever-growing popularity. Never before has access to computational resources been easier for scientists across the natural sciences. The need for accurate, efficient, and robust modelling tools is therefore irrefutable. This, in turn, calls for highly interdisciplinary research, which the thesis presented here is a product of. Through the successful marriage of techniques from mathematical graph theory, theoretical insights from chemistry and biology, and the tools of modern computer science, we are able to computationally construct accurate depictions of biomolecules as atomistic graphs, in which individual atoms become nodes and chemical bonds/interactions are represented by weighted edges. When combined with methods from graph theory and network science, this approach has previously been shown to successfully reveal various properties of proteins, such as dynamics, rigidity, multi-scale organisation, allostery, and protein-protein interactions, and is well poised to set new standards in terms of computational feasibility, multi-scale resolution (from atoms to domains) and time-scales (from nanoseconds to milliseconds). Therefore, building on previous work in our research group spanning over 15 years and to further encourage and facilitate research into this growing field, this thesis's main contribution is to provide a formalised foundation for the construction of atomistic graphs. The most crucial aspect of constructing atomistic graphs of large biomolecules compared to small molecules is the necessity to include a variety of different types of bonds and interactions, because larger biomolecules attain their unique structural layout mainly through weaker interactions, e.g. hydrogen bonds, the hydrophobic effect or π-π interactions. Whilst most interaction types are well-studied and have readily available methodology which can be used to construct atomistic graphs, this is not the case for hydrophobic interactions. To fill this gap, the work presented herein includes novel methodology for encoding the hydrophobic effect in atomistic graphs, that accounts for the many-body effect and non-additivity. Then, a standalone software package for constructing atomistic graphs from structural data is presented. Herein lies the heart of this thesis: the combination of a variety of methodologies for a range of bond/interaction types, as well as an implementation that is deterministic, easy-to-use and efficient. Finally, some promising avenues for utilising atomistic graphs in combination with graph theoretical tools such as Markov Stability as well as other approaches such as Multilayer Networks to study various properties of biomolecules are presented.Open Acces

Reversion scheme for droplet parameters with rainbow refractometry based on Debye theory

This paper was presented at the 3rd Micro and Nano Flows Conference (MNF2011), which was held at the Makedonia Palace Hotel, Thessaloniki in Greece. The conference was organised by Brunel University and supported by the Italian Union of Thermofluiddynamics, Aristotle University of Thessaloniki, University of Thessaly, IPEM, the Process Intensification Network, the Institution of Mechanical Engineers, the Heat Transfer Society, HEXAG - the Heat Exchange Action Group, and the Energy Institute.Rainbow refractometry is a non-intrusive technology for determining the refractive index and diameter of droplet simultaneously. Most of the present schemes for the refractive index and diameter of droplet are based on empirical formulas with Airy theory. However, the anti-noise capability and the generality of the empirical method are weak. In the paper, an objective function was designed to quantify the deviation between the low frequency component of the captured rainbow and the simulated rainbow with Debye (p=2) theory. Further, a novel inversion scheme for single droplet based on Debye (p=2) theory and the objective function was proposed. Experiments were carried out to evaluate the performance of the scheme. Results indicate that the relative error of the radius is less than 8%, the absolute error of the refractive index is better than 5×10-4.Research Award Program for Outstanding Young Teachers in Southeast University (No.3203001202) and QingLan Project (No.1103000126)

High-frequency antiplane wave propagation in ultra-thin films with nanostructures

AbstractUltrasonic wave propagation is one of powerful and popular methods for measuring mechanical properties of solids even at nano scales. The extraction of material constants from the measured wave data may not be accurate and reliable when waves of short wavelengths are used. The objective of this paper is to study the high-frequency antiplane wave propagation in ultra-thin films at nanoscale. A developed continuum microstructure theory will be used to capture the effect of nanostructures in ultra-thin films. This continuum theory is developed from assumed displacement fields for nanostructures. Local kinematic variables are introduced to express these local displacements and are subjected to internal continuity conditions. The accuracy of the theory is verified by comparing the results with those of the lattice model for the antiplane problem in an infinite elastic medium. Specifically, dispersion curves and corresponding displacement fields for antiplane wave propagation in the ultra-thin films are studied. The inadequacy of the conventional continuum theory is discussed

Verifying pushdown multi-agent systems against strategy logics

In this paper, we investigate model checking algorithms for variants of strategy logic over pushdown multi-agent systems, modeled by pushdown game structures (PGSs). We consider various fragments of strategy logic, i.e., SL[CG], SL[DG], SL[1G] and BSIL. We show that the model checking problems on PGSs for SL[CG], SL[DG] and SL[1G] are 3EXTIME-complete, which are not harder than the problem for the subsumed logic ATL*. When BSIL is concerned, the model checking problem becomes 2EXPTIME-complete. Our algorithms are automata-theoretic and based on the saturation technique, which are amenable to implementations

On the satisfiability of indexed linear temporal logics

Indexed Linear Temporal Logics (ILTL) are an extension of standard Linear Temporal Logics (LTL) with quantifications over index variables which range over a set of process identifiers. ILTL has been widely used in specifying and verifying properties of parameterised systems, e.g., in parameterised model checking of concurrent processes. However there is still a lack of theoretical investigations on properties of ILTL, compared to the well-studied LTL. In this paper, we start to narrow this gap, focusing on the satisfiability problem, i.e., to decide whether a model exists for a given formula. This problem is in general undecidable. Various fragments of ILTL have been considered in the literature typically in parameterised model checking, e.g., ILTL formulae in prenex normal form, or containing only non-nested quantifiers, or admitting limited temporal operators. We carry out a thorough study on the decidability and complexity of the satisfiability problem for these fragments. Namely, for each fragment, we either show that it is undecidable, or otherwise provide tight complexity bounds

Electronic Voting Scheme About ElGamal Blind-signatures Based on XML

AbstractPresent an electronic voting algorithm about ElGamal blind-signature based on XML and analyze its security, accounting to the current electronic voting scheme and the ElGamal blind-signature algorithm. The program uses the specification of XML digital signature and the technology of ElGamal blind-signature algorithm and has good security and practical importance

Property rights protection and corporate R&D: Evidence from China

Following the recent literature on institutions and economic growth, we examine the effects of property rights protection on corporate R&D. Using a unique 2003 World Bank survey of over 2400 firms in 18 Chinese cities, we obtain the following findings: (1) property rights protection is positively and significantly related to corporate R&D activity (for both process and product R&D); (2) government services and helping hand are conducive to corporate R&D, while informal payments to government officials are not; and (3) government ownership of firms and direct appointment of CEOs are negatively associated with corporate R&D activities. We also find that corporate R&D is positively related to firm size, and access to finance, but negatively related to product market competition and firm age. © 2009 Elsevier B.V.postprin

An entropy-histogram approach for image similarity and face recognition

Image similarity and image recognition are modern and rapidly growing technologies because of their wide use in the field of digital image processing. It is possible to recognize the face image of a specific person by finding the similarity between the images of the same person face and this is what we will address in detail in this paper. In this paper, we designed two new measures for image similarity and image recognition simultaneously. The proposed measures are based mainly on a combination of information theory and joint histogram. Information theory has a high capability to predict the relationship between image intensity values. The joint histogram is based mainly on selecting a set of local pixel features to construct a multidimensional histogram. The proposed approach incorporates the concepts of entropy and a modified 1D version of the 2D joint histogram of the two images under test. Two entropy measures were considered, Shannon and Renyi, giving a rise to two joint histogram-based, information-theoretic similarity measures: SHS and RSM. The proposed methods have been tested against powerful Zernike-moments approach with Euclidean and Minkowski distance metrics for image recognition and well-known statistical approaches for image similarity such as structural similarity index measure (SSIM), feature similarity index measure (FSIM) and feature-based structural measure (FSM). A comparison with a recent information-theoretic measure (ISSIM) has also been considered. A measure of recognition confidence is introduced in this work based on similarity distance between the best match and the second-best match in the face database during the face recognition process. Simulation results using AT&T and FEI face databases show that the proposed approaches outperform existing image recognition methods in terms of recognition confidence. TID2008 and IVC image databases show that SHS and RSM outperform existing similarity methods in terms of similarity confidence

A multiple maximum scatter difference discriminant criterion for facial feature extraction

2007-2008 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe