Fuzzy methods for analysis of microarrays and networks

Bioinformatics involves analyses of biological data such as DNA sequences, microarrays and protein-protein interaction (PPI) networks. Its two main objectives are the identification of genes or proteins and the prediction of their functions. Biological data often contain uncertain and imprecise information. Fuzzy theory provides useful tools to deal with this type of information, hence has played an important role in analyses of biological data. In this thesis, we aim to develop some new fuzzy techniques and apply them on DNA microarrays and PPI networks. We will focus on three problems: (1) clustering of microarrays; (2) identification of disease-associated genes in microarrays; and (3) identification of protein complexes in PPI networks. The first part of the thesis aims to detect, by the fuzzy C-means (FCM) method, clustering structures in DNA microarrays corrupted by noise. Because of the presence of noise, some clustering structures found in random data may not have any biological significance. In this part, we propose to combine the FCM with the empirical mode decomposition (EMD) for clustering microarray data. The purpose of EMD is to reduce, preferably to remove, the effect of noise, resulting in what is known as denoised data. We call this method the fuzzy C-means method with empirical mode decomposition (FCM-EMD). We applied this method on yeast and serum microarrays, and the silhouette values are used for assessment of the quality of clustering. The results indicate that the clustering structures of denoised data are more reasonable, implying that genes have tighter association with their clusters. Furthermore we found that the estimation of the fuzzy parameter m, which is a difficult step, can be avoided to some extent by analysing denoised microarray data. The second part aims to identify disease-associated genes from DNA microarray data which are generated under different conditions, e.g., patients and normal people. We developed a type-2 fuzzy membership (FM) function for identification of diseaseassociated genes. This approach is applied to diabetes and lung cancer data, and a comparison with the original FM test was carried out. Among the ten best-ranked genes of diabetes identified by the type-2 FM test, seven genes have been confirmed as diabetes-associated genes according to gene description information in Gene Bank and the published literature. An additional gene is further identified. Among the ten best-ranked genes identified in lung cancer data, seven are confirmed that they are associated with lung cancer or its treatment. The type-2 FM-d values are significantly different, which makes the identifications more convincing than the original FM test. The third part of the thesis aims to identify protein complexes in large interaction networks. Identification of protein complexes is crucial to understand the principles of cellular organisation and to predict protein functions. In this part, we proposed a novel method which combines the fuzzy clustering method and interaction probability to identify the overlapping and non-overlapping community structures in PPI networks, then to detect protein complexes in these sub-networks. Our method is based on both the fuzzy relation model and the graph model. We applied the method on several PPI networks and compared with a popular protein complex identification method, the clique percolation method. For the same data, we detected more protein complexes. We also applied our method on two social networks. The results showed our method works well for detecting sub-networks and give a reasonable understanding of these communities.

Modeling of protein signaling networks in clinical proteomics

Molecular interactions that underlie pathophysiological states are being elucidated using techniques that profile proteomicend points in cellular systems. Within the field of cancer research, protein interaction networks play pivotal roles in the establishment and maintenance of the hallmarks of malignancy, including cell division, invasion, and migration. Multiple complementary tools enable a multifaceted view of how signal protein pathway alterations contribute to pathophysiological states.One pivotal technique is signal pathway profiling of patient tissue specimens. This microanalysis technology provides a proteomic snapshot at one point in time of cells directly procured from the native context of a tumor micro environment. To study the adaptive patterns of signal pathway events over time, before and after experimental therapy, it is necessary to obtain biopsies from patients before, during, and after therapy. A complementary approach is the profiling of cultured cell lines with and without treatment. Cultured cell models provide the opportunity to study short-term signal changes occurring over minutes to hours. Through this type of system, the effects of particular pharmacological agents may be used to test the effects of signal pathway inhibition or activation on multiple endpoints within a pathway. The complexity of the data generated has necessitated the development of mathematical models for optimal interpretation of interrelated signaling pathways. In combination,clinical proteomic biopsy profiling, tissue culture proteomic profiling, and mathematical modeling synergistically enable a deeper understanding of how protein associations lead to disease states and present new insights into the design of therapeutic regimens.

The evolutionary value of recombination is constrained by genome modularity

Genetic recombination is a fundamental evolutionary mechanism promoting biological adaptation. Using engineered recombinants of the small single-stranded DNA plant virus, Maize streak virus (MSV), we experimentally demonstrate that fragments of genetic material only function optimally if they reside within genomes similar to those in which they evolved. The degree of similarity necessary for optimal functionality is correlated with the complexity of intragenomic interaction networks within which genome fragments must function. There is a striking correlation between our experimental results and the types of MSV recombinants that are detectable in nature, indicating that obligatory maintenance of intragenome interaction networks strongly constrains the evolutionary value of recombination for this virus and probably for genomes in general.

Simulation and visualization of self-assembled nanodevice networks synthesized via plasma–surface interaction

Using advanced visualization techniques, a comprehensive visualization of all the stages of the self-organized growth of internetworked nanostructures on plasma-exposed surface has been made. Atomistic kinetic Monte Carlo simulation for the initial stage of deposition, with 3-D visualization of the whole system and half-tone visualization of the density field of the adsorbed atoms, makes it possible to implement a multiscale predictive modeling of the development of the nanoscale system.

Developing within-company information and communication technologies (ICT) innovation diffusion networks : a study of three Australian major contractors

The innovation diffusion and knowledge management literature strongly supports the importance of communities of practice (COP) for enabling knowledge about how to use and adopt innovation initiatives. One of the most powerful tools for innovation diffusion is word-of-mouth wisdom from committed individuals who mentor and support each other. Close proximity for face-to-face interaction is highly effective, however, many organisations are geographically dispersed with projects being virtual linked sub-organisations using ICT to communicate. ICT has also introduced a useful facilitating technology for developing knowledge networks. This paper presents findings from a research program concentrating on ICT innovation diffusion in the Australian construction industry. One way in which ICT diffusion is taking place was found to be through within-company communities of practice. We undertook in-depth unstructured interviews with three of the major 10 to 15 contractors in Australia to discuss their ICT diffusion strategies. We discovered that in all three cases,within company networked communities of practice was a central strategy. Further, effective diffusion of ICT groupware tools can be critical in developing COP where they are geographically dispersed.

Networks in the shadow of markets and hierarchies : calling the shots in the visual effects industry

The nature and organisation of creative industries and the creative economy has received increased attention in recent academic and policy literatures (Florida 2002; Grabher 2002; Scott 2006a). Constituted as one variant on new economy narratives, creativity, alongside knowledge, has been presented as a key competitive asset, Such industries – ranging from advertising, to film and new media – are seen as not merely expanding their scale and scope, but as leading edge proponents of a more general trend towards new forms of organization and economic coordination (Davis and Scase 2000). The idea of network forms (and the consequent displacement of markets and hierarchies) has been at the heart of attempts to differentiate the field economically and spatially. Across both the discussion of production models and work/employment relations is the assertion of the enhanced importance of trust and non-market relations in coordinating structures and practices. This reflects an influential view in sociological, management, geography and other literatures that social life is ‘intrinsically networked’ (Sunley 2008: 12) and that we can confidently use the term ‘network society’ to describe contemporary structures and practices (Castells 1996). Our paper is sceptical of the conceptual and empirical foundations of such arguments. We draw on a number of theoretical resources, including institutional theory, global value chain analysis and labour process theory (see Smith and McKinlay 2009) to explore how a more realistic and grounded analysis of the nature of and limits to networks can be articulated. Given space constraints, we cannot address all the dimensions of network arguments or evidence. Our focus is on inter and intra-firm relations and draws on research into a particular creative industry – visual effects – that is a relatively new though increasingly important global production network. Through this examination a different model of the creative industries and creative work emerges – one in which market rules and patterns of hierarchical interaction structure the behaviour of economic actors and remain a central focus of analysis. The next section outlines and unpacks in more detail arguments concerning the role and significance of networks, markets and hierarchies in production models and work organisation in creative industries and the ‘creative economy’.

Theoretical investigation of mechanisms of formation and interaction of nanoparticles

In this thesis an investigation into theoretical models for formation and interaction of nanoparticles is presented. The work presented includes a literature review of current models followed by a series of five chapters of original research. This thesis has been submitted in partial fulfilment of the requirements for the degree of doctor of philosophy by publication and therefore each of the five chapters consist of a peer-reviewed journal article. The thesis is then concluded with a discussion of what has been achieved during the PhD candidature, the potential applications for this research and ways in which the research could be extended in the future. In this thesis we explore stochastic models pertaining to the interaction and evolution mechanisms of nanoparticles. In particular, we explore in depth the stochastic evaporation of molecules due to thermal activation and its ultimate effect on nanoparticles sizes and concentrations. Secondly, we analyse the thermal vibrations of nanoparticles suspended in a fluid and subject to standing oscillating drag forces (as would occur in a standing sound wave) and finally on lattice surfaces in the presence of high heat gradients. We have described in this thesis a number of new models for the description of multicompartment networks joined by a multiple, stochastically evaporating, links. The primary motivation for this work is in the description of thermal fragmentation in which multiple molecules holding parts of a carbonaceous nanoparticle may evaporate. Ultimately, these models predict the rate at which the network or aggregate fragments into smaller networks/aggregates and with what aggregate size distribution. The models are highly analytic and describe the fragmentation of a link holding multiple bonds using Markov processes that best describe different physical situations and these processes have been analysed using a number of mathematical methods. The fragmentation of the network/aggregate is then predicted using combinatorial arguments. Whilst there is some scepticism in the scientific community pertaining to the proposed mechanism of thermal fragmentation,we have presented compelling evidence in this thesis supporting the currently proposed mechanism and shown that our models can accurately match experimental results. This was achieved using a realistic simulation of the fragmentation of the fractal carbonaceous aggregate structure using our models. Furthermore, in this thesis a method of manipulation using acoustic standing waves is investigated. In our investigation we analysed the effect of frequency and particle size on the ability for the particle to be manipulated by means of a standing acoustic wave. In our results, we report the existence of a critical frequency for a particular particle size. This frequency is inversely proportional to the Stokes time of the particle in the fluid. We also find that for large frequencies the subtle Brownian motion of even larger particles plays a significant role in the efficacy of the manipulation. This is due to the decreasing size of the boundary layer between acoustic nodes. Our model utilises a multiple time scale approach to calculating the long term effects of the standing acoustic field on the particles that are interacting with the sound. These effects are then combined with the effects of Brownian motion in order to obtain a complete mathematical description of the particle dynamics in such acoustic fields. Finally, in this thesis, we develop a numerical routine for the description of "thermal tweezers". Currently, the technique of thermal tweezers is predominantly theoretical however there has been a handful of successful experiments which demonstrate the effect it practise. Thermal tweezers is the name given to the way in which particles can be easily manipulated on a lattice surface by careful selection of a heat distribution over the surface. Typically, the theoretical simulations of the effect can be rather time consuming with supercomputer facilities processing data over days or even weeks. Our alternative numerical method for the simulation of particle distributions pertaining to the thermal tweezers effect use the Fokker-Planck equation to derive a quick numerical method for the calculation of the effective diffusion constant as a result of the lattice and the temperature. We then use this diffusion constant and solve the diffusion equation numerically using the finite volume method. This saves the algorithm from calculating many individual particle trajectories since it is describes the flow of the probability distribution of particles in a continuous manner. The alternative method that is outlined in this thesis can produce a larger quantity of accurate results on a household PC in a matter of hours which is much better than was previously achieveable.

How can entrepreneurial musicians use electronic social networks to diffuse their music

Principal Topic: ''In less than ten years music labels will not exist anymore.'' Michael Smelli, former Global COO Sony/BMG MCA/QUT IMP Business Lab Digital Music Think Thanks 9 May 2009, Brisbane Big music labels such as EMI, Sony BMG and UMG have been responsible for promoting and producing a myriad of stars in the music industry over the last decades. However, the industry structure is under enormous threat with the emergence of a new innovative era of digital music. Recent years have seen a dramatic shift in industry power with the emergence of Napster and other file sharing sites, iTunes and other online stores, iPod and the MP3 revolution. Myspace.com and other social networking sites are connecting entrepreneurial artists with fans and creating online music communities independent of music labels. In 2008 the digital music business internationally grew by around 25% to 3.7 Billion US-Dollar. Digital platforms now account for around 20% of recorded music sales, up from 15 % in 2007 (IFPI Digital music report 2009). CD sales have fallen by 40% since their peak levels. Global digital music sales totalled an estimated US$ 3 Billion in 2007, an increase of 40% on 2006 figures. Digital sales account for an estimated 15% of global market, up from 11% in 2006 and zero in 2003. The music industry is more advanced in terms of digital revenues than any other creative or entertainment industry (except games). Its digital share is more than twice that of newspapers (7%), films (35) or books (2%). All these shifts present new possibilities for music entrepreneurs to act entrepreneurially and promote their music independently of the major music labels. Diffusion of innovations has a long tradition in both sociology (e.g. Rogers 1962, 2003) and marketing (Bass 1969, Mahajan et al., 1990). The context of the current project is theoretically interesting in two respects. First, the role of online social networks replaces traditional face-to-face word of mouth communications. Second, as music is a hedonistic product, this strongly influences the nature of interpersonal communications and their diffusion patterns. Both of these have received very little attention in the diffusion literature to date, and no studies have investigated the influence of both simultaneously. This research project is concerned with the role of social networks in this new music industry landscape, and how this may be leveraged by musicians willing to act entrepreneurially. Our key research question we intend to address is: How do online social network communities impact the nature, pattern and speed that music diffuses? Methodology/Key Propositions : We expect the nature/ character of diffusion of popular, generic music genres to be different from specialized, niche music. To date, only Moe & Fader (2002) and Lee et al. (2003) investigated diffusion patterns of music and these focus on forecast weekly sales of music CDs based on the advance purchase orders before the launch, rather than taking a detailed look at diffusion patterns. Consequently, our first research questions are concerned with understanding the nature of online communications within the context of diffusion of music and artists. Hence, we have the following research questions: RQ1: What is the nature of fan-to-fan ''word of mouth'' online communications for music? Do these vary by type of artist and genre of music? RQ2: What is the nature of artist-to-fan online communications for music? Do these vary by type of artist and genre of music? What types of communication are effective? Two outcomes from research social network theory are particularly relevant to understanding how music might diffuse through social networks. Weak tie theory (Granovetter, 1973), argues that casual or infrequent contacts within a social network (or weak ties) act as a link to unique information which is not normally contained within an entrepreneurs inner circle (or strong tie) social network. A related argument, structural hole theory (Burt, 1992), posits that it is the absence of direct links (or structural holes) between members of a social network which offers similar informational benefits. Although these two theories argue for the information benefits of casual linkages, and diversity within a social network, others acknowledge that a balanced network which consists of a mix of strong ties, weak ties is perhaps more important overall (Uzzi, 1996). It is anticipated that the network structure of the fan base for different types of artists and genres of music will vary considerably. This leads to our third research question: RQ3: How does the network structure of online social network communities impact the pattern and speed that music diffuses? The current paper is best described as theory elaboration. It will report the first exploratory phase designed to develop and elaborate relevant theory (the second phase will be a quantitative study of network structure and diffusion). We intend to develop specific research propositions or hypotheses from the above research questions. To do so we will conduct three focus group discussions of independent musicians and three focus group discussions of fans active in online music communication on social network sites. We will also conduct five case studies of bands that have successfully built fan bases through social networking sites (e.g. myspace.com, facebook.com). The idea is to identify which communication channels they employ and the characteristics of the fan interactions for different genres of music. We intend to conduct interviews with each of the artists and analyse their online interaction with their fans. Results and Implications : At the current stage, we have just begun to conduct focus group discussions. An analysis of the themes from these focus groups will enable us to further refine our research questions into testable hypotheses. Ultimately, our research will provide a better understanding of how social networks promote the diffusion of music, and how this varies for different genres of music. Hence, some music entrepreneurs will be able to promote their music more effectively. The results may be further generalised to other industries where online peer-to-peer communication is common, such as other forms of entertainment and consumer technologies.

Krill: An exploration in underwater sensor networks

While sensor networks have now become very popular on land, the underwater environment still poses some difficult problems. Communication is one of the difficult challenges under water. There are two options: optical and acoustic. We have designed an optical communication board that allows the Fleck’s to communicate optically. We have tested the resulting underwater sensor nodes in two different applications.

The relationship between culture, attitude, social networks and quality of life in midlife Australian and Taiwanese citizens

Objectives: The objectives of this study were to specifically investigate the differences in culture, attitudes and social networks between Australian and Taiwanese men and women and identify the factors that predict midlife men and women’s quality of life in both countries. Methods: A stratified random sample strategy based on probability proportional sampling (PPS) was conducted to investigate 278 Australian and 398 Taiwanese midlife men and women’s quality of life. Multiple regression modelling and classification and regression trees (CARTs) were performed to examine the potential differences on culture, attitude, social networks, social demographic factors and religion/spirituality in midlife men and women’s quality of life in both Australia and Taiwan. Results: The results of this study suggest that culture involves multiple functions and interacts with attitudes, social networks and individual factors to influence a person’s quality of life. Significant relationships were found between the interaction between cultural circumstances and a person’s internal and external factors. The research found that good social support networks and a healthy optimistic disposition may significantly enhance midlife men and women’s quality of life. Conclusion: The study indicated that there is a significant relationship between culture, attitude, social networks and quality of life in midlife Australian and Taiwanese men and women. People who had higher levels of horizontal individualism and collectivism, positive attitudes and better social support had better psychological, social, physical and environmental health, while it emerged that vertical individualists with competitive characteristics would experience a lower quality of life. This study has highlighted areas where opportunities exist to further reflect upon contemporary social health policies for Australian and Taiwanese societies and also within the global perspective, in order to provide enhanced quality care for growing midlife populations.

GYAN: A methodology for rule extraction from artificial neural networks

Artificial neural network (ANN) learning methods provide a robust and non-linear approach to approximating the target function for many classification, regression and clustering problems. ANNs have demonstrated good predictive performance in a wide variety of practical problems. However, there are strong arguments as to why ANNs are not sufficient for the general representation of knowledge. The arguments are the poor comprehensibility of the learned ANN, and the inability to represent explanation structures. The overall objective of this thesis is to address these issues by: (1) explanation of the decision process in ANNs in the form of symbolic rules (predicate rules with variables); and (2) provision of explanatory capability by mapping the general conceptual knowledge that is learned by the neural networks into a knowledge base to be used in a rule-based reasoning system. A multi-stage methodology GYAN is developed and evaluated for the task of extracting knowledge from the trained ANNs. The extracted knowledge is represented in the form of restricted first-order logic rules, and subsequently allows user interaction by interfacing with a knowledge based reasoner. The performance of GYAN is demonstrated using a number of real world and artificial data sets. The empirical results demonstrate that: (1) an equivalent symbolic interpretation is derived describing the overall behaviour of the ANN with high accuracy and fidelity, and (2) a concise explanation is given (in terms of rules, facts and predicates activated in a reasoning episode) as to why a particular instance is being classified into a certain category.

The old face of 'new' social networks : the republic of letters as a virtual community

This paper explores the idea of virtual participation through the historical example of the republic of letters in early modern Europe (circa 1500-1800). By reflecting on the construction of virtuality in a historical context, and more specifically in a pre-digital environment, this paper calls attention to accusations of technological determinism in ongoing research concerning the affordances of the Internet and related media of communication. It argues that ‘the virtual’ is not synonymous with ‘the digital’ and suggests that, in order to articulate what is novel about modern technologies, we must first understand the social interactions underpinning the relationships which are facilitated through those technologies. By analysing the construction of virtuality in a pre-digital environment, this paper thus offers a baseline from which scholars might consider what is different about the modes of interaction and communication being engaged in via modern media.

Project-based organisations : overcoming lack of trust and social networks within small and medium project teams

In sustainable development projects, as well as other types of projects, knowledge transfer is important for the organisations managing the project. Nevertheless, knowledge transfer among employees does not happen automatically and it has been found that the lack of social networks and the lack of trust among employees are the major barriers to effective knowledge transfer. Social network analysis has been recognised as a very important tool for improving knowledge transfer in the project environment. Transfer of knowledge is more effective where it depends heavily on social networks and informal dialogue. Based on the theory of social capital, social capital consists of two parts: conduits network and resource exchange network. This research studies the relationships among performance, the resource exchange network (such as the knowledge network) and the relationship network (such as strong ties network, energy network, and trust network) at the individual and project levels. The aim of this chapter is to present an approach to overcoming the lack of social networks and lack of trust to improve knowledge transfer within project-based organisations. This is to be done by identifying the optimum structure of relationship networks and knowledge networks within small and medium projects. The optimal structure of the relationship networks and knowledge networks is measured using two dimensions: intra-project and inter-project. This chapter also outlines an extensive literature review in the areas of social capital, knowledge management and project management, and presents the conceptual model of the research approach.

Designing for participation in local social ridesharing networks : grass roots prototyping of IT systems

This abstract explores the possibility of a grass roots approach to engaging people in community change initiatives by designing simple interactive exploratory prototypes for use by communities over time that support shared action. The prototype is gradually evolved in response to community use, fragments of data gathered through the prototype, and participant feedback with the goal of building participation in community change initiatives. A case study of a system to support ridesharing is discussed. The approach is compared and contrasted to a traditional IT systems procurement approach.

Interaction, privacy and profiling considerations in local mobile social software : a prototype agile ride share system

Agile ridesharing aims to utilise the capability of social networks and mobile phones to facilitate people to share vehicles and travel in real time. However the application of social networking technologies in local communities to address issues of personal transport faces significant design challenges. In this paper we describe an iterative design-based approach to exploring this problem and discuss findings from the use of an early prototype. The findings focus upon interaction, privacy and profiling. Our early results suggest that explicitly entering information such as ride data and personal profile data into formal fields for explicit computation of matches, as is done in many systems, may not be the best strategy. It might be preferable to support informal communication and negotiation with text search techniques.