1,721,005 research outputs found
Multi-layered model of individual HIV infection progression and mechanisms of phenotypical expression
Full text linkCite as: Perrin, Dimitri (2008) Multi-layered model of individual HIV infection progression and mechanisms of phenotypical expression. PhD thesis, Dublin City University
Assessment of a tool to enhance stakeholder collaboration in an IT capstone unit
No full text<b>Introduction</b>\ud
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• Capstone (final year) projects are an essential part of IT degrees in Australia, but there are no established guidelines for their design \ud
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• Literature suggests that use of an agile software development methodology (scrum) is positively perceived by staff and students. \ud
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• How this is implemented varies widely, although assessment of product, process and progression is suggested.\ud
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• Peer and self assessment is positively perceived by most students when using agile.\ud
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• Poor communication is frequently highlighted by the literature and student feedback.\ud
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• Current literature provides few examples of how collaboration between stakeholders , between students, or with peers, can be improv
Agent-based modelling of viral infection.
Full text linkThe three phases of the macroscopic evolution of the HIV infection are well-known, but it is still difficult to understand how the cellular-level interactions come together to create this characteristic pattern and in particular why there are such differences in individual responses. An “agent-based” approach is chosen, as a means of inferring high-level behaviour from a small set of interaction rules at the cellular level. Here the emphasis is put on the cell mobility and the viral mutations
Epigenetic modelling
No full textThe field of epigenetics looks at changes in the chromosomal structure that affect gene expression without altering DNA sequence. A large-scale modelling project to better understand these mechanisms is gaining momentum.\ud
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Early advances in genetics led to the all-genetic paradigm: phenotype (an organism's characteristics/behaviour) is determined by genotype (its genetic make-up). This was later amended and expressed by the well-known formula P = G + E, encompassing the notion that the visible characteristics of a living organism (the phenotype, P) is a combination of hereditary genetic factors (the genotype, G) and environmental factors (E). However, this method fails to explain why in diseases such as schizophrenia we still observe differences between identical twins. Furthermore, the identification of environmental factors (such as smoking and air quality for lung cancer) is relatively rare. The formula also fails to explain cell differentiation from a single fertilized cell.\ud
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In the wake of early work by Waddington, more recent results have emphasized that the expression of the genotype can be altered without any change in the DNA sequence. This phenomenon has been tagged as epigenetics. To form the chromosome, DNA strands roll over nucleosomes, which are a cluster of nine proteins (histones), as detailed in Figure 1. Epigenetic mechanisms involve inherited alterations in these two structures, eg through attachment of a functional group to the amino acids (methyl, acetyl and phosphate). These 'stable alterations' arise during development and cell proliferation and persist through cell division. While information within the genetic material is not changed, instructions for its assembly and interpretation may be. Modelling this new paradigm, P = G + E + EpiG, is the object of our study
Decentralised Communication in Autonomous Agent Swarms
No full textCommunication and information diffusion are typically difficult in situations where centralised structures may become unavailable. In this context, decentralised communication based on epidemic broadcast becomes essential. It can be seen as an opportunity-based flooding for message broadcasting within a swarm of autonomous agents, where each entity tries to share the information it possesses with its neighbours. As an example of applications for such a system, we present simulation results where agents have to coordinate to map an unknown area
Cell type-dependent, infection-induced, aberrant DNA methylation in gastric cancer
No full textEpigenetic changes correspond to heritable modifications of the chromatin structure, which do not involve any alteration of the DNA sequence but nonetheless affect gene expression. These mechanisms play an important role in cell differentiation, but aberrant occurrences are also associated with a number of diseases, including cancer and neural development disorders.\ud
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In particular, aberrant DNA methylation induced by H. Pylori has been found to be a significant risk factor in gastric cancer. To investigate the sensitivity of different genes and cell types to this infection, a computational model of methylation in gastric crypts is developed.\ud
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In this article, we review existing results from physical experiments and outline their limitations, before presenting the computational model and investigating the influence of its parameters
Computational analysis of epigenetic information in human DNA sequences
No full textOver the last few years, investigations of human \ud
epigenetic profiles have identified key elements of change to be Histone Modifications, stable and heritable DNA methylation and Chromatin remodeling. These factors determine gene expression levels and characterise conditions leading to disease. In order to extract information embedded in long DNA sequences, data mining and pattern recognition tools are widely used, but efforts have been limited to date with respect to analyzing epigenetic changes, and their role as catalysts in disease onset. Useful insight, however, can be gained by investigation of associated dinucleotide distributions. The focus of this paper is to explore specific dinucleotides frequencies \ud
across defined regions within the human genome, and to \ud
identify new patterns between epigenetic mechanisms and \ud
DNA content. Signal processing methods, including Fourier \ud
and Wavelet Transformations, are employed and principal \ud
results are reported
A parallel approach to social network generation and agent-based epidemic simulation
No full textUnderstanding the dynamics of disease spread is essential in contexts such as estimating load on medical services, as well as risk assessment and interven- tion policies against large-scale epidemic outbreaks. However, most of the information is available after the outbreak itself, and preemptive assessment is far from trivial. Here, we report on an agent-based model developed to investigate such epidemic events in a stylised urban environment. For most diseases, infection of a new individual may occur from casual contact in crowds as well as from repeated interactions with social partners such as work colleagues or family members. Our model therefore accounts for these two phenomena. Given the scale of the system, efficient parallel computing is required. In this presentation, we focus on aspects related to paralllelisation for large networks generation and massively multi-agent simulations
Complexity and high-end computing in biology and medicine
No full textBiomedical systems involve a large number of entities and intricate interactions between these. Their direct analysis is, therefore, difficult, and it is often necessary to rely on computational models. These models require significant resources and parallel computing solutions. These approaches are particularly suited, given parallel aspects in the nature of biomedical systems. Model hybridisation also permits the integration and simultaneous study of multiple aspects and scales of these systems, thus providing an efficient platform for multidisciplinary research
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