Computational analysis of CpG site DNA methylation

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Epigenetics is the study of factors that can change DNA and passed to next generation without change to DNA sequence. DNA methylation is one of the categories of epigenetic change. DNA methylation is the attachment of methyl group (CH3) to DNA. Most of the time it occurs in the sequences that G is followed by C known as CpG sites and by addition of methyl to the cytosine residue. As science and technology progress new data are available about individual’s DNA methylation profile in different conditions. Also new features discovered that can have role in DNA methylation. The availability of new data on DNA methylation and other features of DNA provide challenge to bioinformatics and the opportunity to discover new knowledge from existing data. In this research multiple data series were used to identify classes of methylation DNA to CpG sites. These classes are a) Never methylated CpG sites,b) Always methylated CpG sites, c) Methylated CpG sites in cancer/disease samples and non-methylated in normal samples d) Methylated CpG sites in normal samples and non-methylated in cancer/disease samples. After identification of these sites and their classes, an analysis was carried out to find the features which can better classify these sites a matrix of features was generated using four applications in EMBOSS software suite. Features matrix was also generated using the gUse/WS-PGRADE portal workflow system. In order to do this each of the four applications were grid enabled and ported to BOINC platform. The gUse portal was connected to the BOINC project via 3G-bridge. Each node in the workflow created portion of matrix and then these portions were combined together to create final matrix. This final feature matrix used in a hill climbing workflow. Hill climbing node was a JAVA program ported to BOINC platform. A Hill climbing search workflow was used to search for a subset of features that are better at classifying the CpG sites using 5 different measurements and three different classification methods: support vector machine, naïve bayes and J48 decision tree. Using this approach the hill climbing search found the models which contain less than half the number of features and better classification results. It is also been demonstrated that using gUse/WS-PGRADE workflow system can provide a modular way of feature generation so adding new feature generator application can be done without changing other parts. It is also shown that using grid enabled applications can speedup both feature generation and feature subset selection. The approach used in this research for distributed workflow based feature generation is not restricted to this study and can be applied in other studies that involve feature generation. The approach also needs multiple binaries to generate portions of features. The grid enabled hill climbing search application can also be used in different context as it only requires to follow the same format of feature matrix

Proceedings of the 2018 Canadian Society for Mechanical Engineering (CSME) International Congress

Published proceedings of the 2018 Canadian Society for Mechanical Engineering (CSME) International Congress, hosted by York University, 27-30 May 2018

Individual differences in psychological adjustment to perceived abnormalities of appearance

Merged with duplicate record (10026.1/764) on 03.01.2017 by CS (TIS)This is a digitised version of a thesis that was deposited in the University Library. If you are the author please contact PEARL Admin ([email protected]) to discuss options.The aim of this programme of research was to investigate the differences between individuals in their psychological adjustment to perceived abnormalities of appearance. The first phase of the research was to refine and validate a measure of distress and dysfunction associated with having an appearance which is different from normal. Over 500 patients in plastic reconstructive surgery units were recruited as participants in a nationwide multi-centre trial. The resulting measure, the Derriford Appearance Scale 24r was shown to have good psychometric properties, and was used as a criterion measure of adjustment. A series of clinical interviews were conducted with contrasting groups of individuals identified as being either good or poor adjusters. Three analyses were carried out. The first took a grounded theory approach to the open ended section of the interviews. This produced an integrated phenomenological account of living with differences of appearance. It also demonstrated differences between the two groups - poor adjustment was associated with a more threatening and negative appraisal of situations and the self. The negative self view was more salient to the poor adjusters. The second analysis of the interview data was a hypothesis testing content analysis, designed to eliminate competing candidate hypotheses generated from the general psychology literature. From this study, it was shown that poor adjusters have a greater degree ofnegative appearance related thoughts, and a more negative appraisal of situations. They were both more pessimistic, and experienced more anticipatory anxiety. Using the interview sample, a third study was conducted, based on self-discrepancy theory. Poor adjusters were shown to place more value on their appearance, and have a greater discrepancy between their 'actual' and 'ideal appearance' selves than the good adjusters. On the basis of the interview studies, two further main empirical studies were carried out. The first tested comprehension of social cues. This did not differentiate the good and poor adjustment groups. Methodological, as well as theoretical reasons for this were proposed. The final study investigated the organisation of self-knowledge, using a sample of 70 participants recruited from a plastic and reconstructive surgery unit, and from two support groups. It was found that there were important differences between the adjustment groups. A high level of compartmentalisation of specific appearance information, greater levels of complexity of the self-concept, and an increased level of differential importance of aspects of the self concept containing specific appearance information were all related to poor adjustment. This set of findings was integrated with the earlier work, and is theoretically interpreted within a self-schema perspective. The contribution of this thesis is to develop the understanding of individual differences in adjustment from a relatively atheoretical field to a position where future research and clinical practice can progress in a theoretically integrated and meaningful way.PCFC in collaboration with Derriford Hospita

Using spontaneously generated online patient experiences to improve healthcare : A case study using Modafinil

Background Acknowledged issues with the RCT focus of EBM and recognition of the value of patient input have created a need for new methods of knowledge generation that can give the depth of qualitative studies but on a much larger scale. Almost half of the global population uses social media regularly, with increasing numbers of people using online spaces as either a first- or second-line health information and exchange resource. Estimates suggest the volume of online health related data grew by 300% between 2017 and 2020. As a data source, this unstructured freeform textual data is a form of patient generated health data, containing a mass of patient centred, contextually grounded detail about the perceptions and health concerns of those who post online. Methods for analysing it are at an early stage of development, but it is seen as having potential to add to clinical understanding, either by augmenting existing knowledge, or in aiding understanding of real-world usage of healthcare interventions and services. Objectives To explore how large-scale analysis of SGOPE can help with understanding patient perspectives of their conditions, symptoms, and self-management behaviours, assess the effectiveness of interventions, contribute to the process of knowledge and evidence creation, and consequently help healthcare systems improve outcomes in the most efficient manner. A secondary aim is to contribute to the development of methods that can be generalised across other interventions or services. Methods Using Modafinil as a case study, a multistage approach was taken. First, an exploratory study, comparing both qualitative and basic NLP techniques was undertaken on a small sample of 260 posts to identify topics, evaluate effectiveness and identify perceived causal text. An umbrella scoping review was then undertaken exploring how and for what purposes SGOPE data is currently being used within healthcare research. Findings from both then guided the main study, which used a variety of unsupervised NLP tools to explore the main dataset of over 69k posts. Individual methods were compared against each other. Results from both studies were compared and for evaluation. Results In contrast to the existing inconclusive systematic review evidence for Modafinil for anything other than narcolepsy, both studies found that Modafinil is seen as by posters as effective in treating fatigue and cognition symptoms in a wide range of conditions. Both identified the topics mentioned in the data, although more work needs to be done to develop the NLP methods to achieve a greater depth of understanding. The first study identified eight themes within the posts: reason for taking, impact of symptoms, acquisition, dosage, side-effects, comparison with other interventions, effectiveness, and quality of life outcomes. Effectiveness of Modafinil was found to be 68% positive, 12% mixed and 18% negative. Expressions of causal belief were identified. In the main study, effectiveness was measured with sentiment analysis, with all methods showing strong positive sentiment. Topic modelling identified groups of themes. Linguistic techniques extracted phrases indicating causality. Various analysis methods were compared to develop a method that could be generalised across other health topics