School of Mathematics and Statistics - Research Publications

Permanent URI for this collection

Search Results

Now showing 1 - 10 of 1051
  • Item
    Thumbnail Image
    A semantics, energy-based approach to automate biomodel composition
    Shahidi, N ; Pan, M ; Tran, K ; Crampin, EJ ; Nickerson, DP ; Brusch, L (PUBLIC LIBRARY SCIENCE, 2022-01-01)
    Hierarchical modelling is essential to achieving complex, large-scale models. However, not all modelling schemes support hierarchical composition, and correctly mapping points of connection between models requires comprehensive knowledge of each model's components and assumptions. To address these challenges in integrating biosimulation models, we propose an approach to automatically and confidently compose biosimulation models. The approach uses bond graphs to combine aspects of physical and thermodynamics-based modelling with biological semantics. We improved on existing approaches by using semantic annotations to automate the recognition of common components. The approach is illustrated by coupling a model of the Ras-MAPK cascade to a model of the upstream activation of EGFR. Through this methodology, we aim to assist researchers and modellers in readily having access to more comprehensive biological systems models.
  • Item
    Thumbnail Image
    Are Experts Well-Calibrated? An Equivalence-Based Hypothesis Test.
    Dharmarathne, G ; Hanea, AM ; Robinson, A (MDPI AG, 2022-05-27)
    Estimates based on expert judgements of quantities of interest are commonly used to supplement or replace measurements when the latter are too expensive or impossible to obtain. Such estimates are commonly accompanied by information about the uncertainty of the estimate, such as a credible interval. To be considered well-calibrated, an expert's credible intervals should cover the true (but unknown) values a certain percentage of time, equal to the percentage specified by the expert. To assess expert calibration, so-called calibration questions may be asked in an expert elicitation exercise; these are questions with known answers used to assess and compare experts' performance. An approach that is commonly applied to assess experts' performance by using these questions is to directly compare the stated percentage cover with the actual coverage. We show that this approach has statistical drawbacks when considered in a rigorous hypothesis testing framework. We generalize the test to an equivalence testing framework and discuss the properties of this new proposal. We show that comparisons made on even a modest number of calibration questions have poor power, which suggests that the formal testing of the calibration of experts in an experimental setting may be prohibitively expensive. We contextualise the theoretical findings with a couple of applications and discuss the implications of our findings.
  • Item
    Thumbnail Image
    Simultaneous visualization of flow fields and oxygen concentrations to unravel transport and metabolic processes in biological systems.
    Ahmerkamp, S ; Jalaluddin, FM ; Cui, Y ; Brumley, DR ; Pacherres, CO ; Berg, JS ; Stocker, R ; Kuypers, MMM ; Koren, K ; Behrendt, L (Elsevier BV, 2022-05-23)
    From individual cells to whole organisms, O2 transport unfolds across micrometer- to millimeter-length scales and can change within milliseconds in response to fluid flows and organismal behavior. The spatiotemporal complexity of these processes makes the accurate assessment of O2 dynamics via currently available methods difficult or unreliable. Here, we present "sensPIV," a method to simultaneously measure O2 concentrations and flow fields. By tracking O2-sensitive microparticles in flow using imaging technologies that allow for instantaneous referencing, we measured O2 transport within (1) microfluidic devices, (2) sinking model aggregates, and (3) complex colony-forming corals. Through the use of sensPIV, we find that corals use ciliary movement to link zones of photosynthetic O2 production to zones of O2 consumption. SensPIV can potentially be extendable to study flow-organism interactions across many life-science and engineering applications.
  • Item
    Thumbnail Image
    Traffic Patterns of the Migrating Endothelium: How Force Transmission Regulates Vascular Malformation and Functional Shunting During Angiogenic Remodelling
    Edgar, LT ; Park, H ; Crawshaw, JR ; Osborne, JM ; Eichmann, A ; Bernabeu, MO (FRONTIERS MEDIA SA, 2022-05-19)
    Angiogenesis occurs in distinct phases: initial spouting is followed by remodelling in which endothelial cells (ECs) composing blood vessels rearrange by migrating against the direction of flow. Abnormal remodelling can result in vascular malformation. Such is the case in mutation of the Alk1 receptor within the mouse retina which disrupts flow-migration coupling, creating mixed populations of ECs polarised with/against flow which aggregate into arteriovenous malformations (AVMs). The lack of live imaging options in vivo means that the collective EC dynamics that drive AVM and the consequences of mixed populations of polarity remain a mystery. Therefore, our goal is to present a novel agent-based model to provide theoretical insight into EC force transmission and collective dynamics during angiogenic remodelling. Force transmission between neighbouring agents consists of extrusive forces which maintain spacing and cohesive forces which maintain the collective. We performed migration simulations within uniformly polarised populations (against flow) and mixed polarity (with/against flow). Within uniformly polarised populations, extrusive forces stabilised the plexus by facilitating EC intercalation which ensures that cells remained evenly distributed. Excess cohesion disrupts intercalation, resulting in aggregations of cells and functional shunting. Excess cohesion between ECs prevents them from resolving diameter balances within the plexus, leading to prolonged flow reversals which exert a critical behaviour change within the system as they switch the direction of cell migration and traffic patterns at bifurcations. Introducing mixtures of cell polarity dramatically changed the role of extrusive forces within the system. At low extrusion, opposing ECs were able to move past each other; however, at high extrusion the pushing between cells resulted in migration speeds close to zero, forming traffic jams and disrupting migration. In our study, we produced vascular malformations and functional shunting with either excess cohesion between ECs or mixtures of cell polarity. At the centre of both these mechanisms are cell-cell adherens junctions, which are involved in flow sensing/polarity and must remodelling dynamically to allow rearrangements of cells during vascular patterning. Thus, our findings implicate junctional dysfunction as a new target in the treatment and prevention of vascular disease and AVMs.
  • Item
    Thumbnail Image
    Sincast: a computational framework to predict cell identities in single-cell transcriptomes using bulk atlases as references
    Deng, Y ; Choi, J ; Cao, K-AL (OXFORD UNIV PRESS, 2022-03-31)
    Characterizing the molecular identity of a cell is an essential step in single-cell RNA sequencing (scRNA-seq) data analysis. Numerous tools exist for predicting cell identity using single-cell reference atlases. However, many challenges remain, including correcting for inherent batch effects between reference and query data andinsufficient phenotype data from the reference. One solution is to project single-cell data onto established bulk reference atlases to leverage their rich phenotype information. Sincast is a computational framework to query scRNA-seq data by projection onto bulk reference atlases. Prior to projection, single-cell data are transformed to be directly comparable to bulk data, either with pseudo-bulk aggregation or graph-based imputation to address sparse single-cell expression profiles. Sincast avoids batch effect correction, and cell identity is predicted along a continuum to highlight new cell states not found in the reference atlas. In several case study scenarios, we show that Sincast projects single cells into the correct biological niches in the expression space of the bulk reference atlas. We demonstrate the effectiveness of our imputation approach that was specifically developed for querying scRNA-seq data based on bulk reference atlases. We show that Sincast is an efficient and powerful tool for single-cell profiling that will facilitate downstream analysis of scRNA-seq data.
  • Item
    Thumbnail Image
    Alterations in the Gut Fungal Community in a Mouse Model of Huntington's Disease
    Kong, G ; Cao, K-AL ; Hannan, AJ ; Shapiro, RS (AMER SOC MICROBIOLOGY, 2022-04-01)
    Huntington's disease (HD) is a neurodegenerative disorder caused by a trinucleotide expansion in the HTT gene, which is expressed throughout the brain and body, including the gut epithelium and enteric nervous system. Afflicted individuals suffer from progressive impairments in motor, psychiatric, and cognitive faculties, as well as peripheral deficits, including the alteration of the gut microbiome. However, studies characterizing the gut microbiome in HD have focused entirely on the bacterial component, while the fungal community (mycobiome) has been overlooked. The gut mycobiome has gained recognition for its role in host homeostasis and maintenance of the gut epithelial barrier. We aimed to characterize the gut mycobiome profile in HD using fecal samples collected from the R6/1 transgenic mouse model (and wild-type littermate controls) from 4 to 12 weeks of age, corresponding to presymptomatic through to early disease stages. Shotgun sequencing was performed on fecal DNA samples, followed by metagenomic analyses. The HD gut mycobiome beta diversity was significantly different from that of wild-type littermates at 12 weeks of age, while no genotype differences were observed at the earlier time points. Similarly, greater alpha diversity was observed in the HD mice by 12 weeks of age. Key taxa, including Malassezia restricta, Yarrowia lipolytica, and Aspergillus species, were identified as having a negative association with HD. Furthermore, integration of the bacterial and fungal data sets at 12 weeks of age identified negative correlations between the HD-associated fungal species and Lactobacillus reuteri. These findings provide new insights into gut microbiome alterations in HD and may help identify novel therapeutic targets. IMPORTANCE Huntington's disease (HD) is a fatal neurodegenerative disorder affecting both the mind and body. We have recently discovered that gut bacteria are disrupted in HD. The present study provides the first evidence of an altered gut fungal community (mycobiome) in HD. The genomes of many thousands of gut microbes were sequenced and used to assess "metagenomics" in particular the different types of fungal species in the HD versus control gut, in a mouse model. At an early disease stage, before the onset of symptoms, the overall gut mycobiome structure (array of fungi) in HD mice was distinct from that of their wild-type littermates. Alterations of multiple key fungi species were identified as being associated with the onset of disease symptoms, some of which showed strong correlations with the gut bacterial community. This study highlights the potential role of gut fungi in HD and may facilitate the development of novel therapeutic approaches.
  • Item
    Thumbnail Image
    Host Traits and Phylogeny Contribute to Shaping Coral-Bacterial Symbioses
    Ricci, F ; Tandon, K ; Black, JR ; Cao, K-AL ; Blackall, LL ; Verbruggen, H ; Raina, J-B (AMER SOC MICROBIOLOGY, 2022-03-07)
    The success of tropical scleractinian corals depends on their ability to establish symbioses with microbial partners. Host phylogeny and traits are known to shape the coral microbiome, but to what extent they affect its composition remains unclear. Here, by using 12 coral species representing the complex and robust clades, we explored the influence of host phylogeny, skeletal architecture, and reproductive mode on the microbiome composition, and further investigated the structure of the tissue and skeleton bacterial communities. Our results show that host phylogeny and traits explained 14% of the tissue and 13% of the skeletal microbiome composition, providing evidence that these predictors contributed to shaping the holobiont in terms of presence and relative abundance of bacterial symbionts. Based on our data, we conclude that host phylogeny affects the presence of specific microbial lineages, reproductive mode predictably influences the microbiome composition, and skeletal architecture works like a filter that affects bacterial relative abundance. We show that the β-diversity of coral tissue and skeleton microbiomes differed, but we found that a large overlapping fraction of bacterial sequences were recovered from both anatomical compartments, supporting the hypothesis that the skeleton can function as a microbial reservoir. Additionally, our analysis of the microbiome structure shows that 99.6% of tissue and 99.7% of skeletal amplicon sequence variants (ASVs) were not consistently present in at least 30% of the samples, suggesting that the coral tissue and skeleton are dominated by rare bacteria. Together, these results provide novel insights into the processes driving coral-bacterial symbioses, along with an improved understanding of the scleractinian microbiome.
  • Item
    Thumbnail Image
    Co-designing and building an expert-elicited non-parametric Bayesian network model: demonstrating a methodology using a Bonamia Ostreae spread risk case study
    Hanea, AM ; Hilton, Z ; Ben, K ; Robinson, AP (WILEY, 2022-02-20)
    The development and use of probabilistic models, particularly Bayesian networks (BN), to support risk-based decision making is well established. Striking an efficient balance between satisfying model complexity and ease of development requires continuous compromise. Codesign, wherein the structural content of the model is developed hand-in-hand with the experts who will be accountable for the parameter estimates, shows promise, as do so-called nonparametric Bayesian networks (NPBNs), which provide a light-touch approach to capturing complex relationships among nodes. We describe and demonstrate the process of codesigning, building, quantifying, and validating an NPBN model for emerging risks and the consequences of potential management decisions using structured expert judgment (SEJ). We develop a case study of the local spread of a marine pathogen, namely, Bonamia ostreae. The BN was developed through a series of semistructured workshops that incorporated extensive feedback from many experts. The model was then quantified with a combination of field and expert-elicited data. The IDEA protocol for SEJ was used in its hybrid (remote and face-to-face) form to elicit information about more than 100 parameters. This article focuses on the modeling and quantification process, the methodological challenges, and the way these were addressed.
  • Item
    Thumbnail Image
    An accurate method for identifying recent recombinants from unaligned sequences
    Feng, Q ; Tiedje, KE ; Ruybal-Pesantez, S ; Tonkin-Hill, G ; Duffy, MF ; Day, KP ; Shim, H ; Chan, Y-B ; Alkan, C (OXFORD UNIV PRESS, 2022-03-28)
    MOTIVATION: Recombination is a fundamental process in molecular evolution, and the identification of recombinant sequences is thus of major interest. However, current methods for detecting recombinants are primarily designed for aligned sequences. Thus they struggle with analyses of highly diverse genes, such as the var genes of the malaria parasite Plasmodium falciparum, which are known to diversify primarily through recombination. RESULTS: We introduce an algorithm to detect recent recombinant sequences from a dataset without a full multiple alignment. Our algorithm can handle thousands of gene-length sequences without the need for a reference panel. We demonstrate the accuracy of our algorithm through extensive numerical simulations; in particular, it maintains its effectiveness in the presence of insertions and deletions. We apply our algorithm to a dataset of 17,335 DBLα types in var genes from Ghana, observing that sequences belonging to the same ups group or domain subclass recombine amongst themselves more frequently, and that non-recombinant DBLα types are more conserved than recombinant ones. AVAILABILITY: Source code is freely available at https://github.com/qianfeng2/detREC_program. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
  • Item
    Thumbnail Image
    Psychosocial Well-Being and Functional Outcomes in Youth With Type 1 Diabetes 12 years After Disease Onset
    Northam, EA ; Lin, A ; Finch, S ; Weather, GA ; Cameron, FJ (AMER DIABETES ASSOC, 2010-07-01)
    OBJECTIVE: Type 1 diabetes in youth and community controls were compared on functional outcomes. Relationships were examined between psychosocial variables at diagnosis and functional outcome 12 years later. RESEARCH DESIGN AND METHODS: Participants were subjects with type 1 diabetes (n = 110, mean age 20.7 years, SD 4.3) and control subjects (n = 76, mean age 20.8 years, SD 4.0). The measures used included the Youth Self-Report and Young Adult Self-Report and a semi-structured interview of functional outcomes. Type 1 diabetes participants also provided information about current diabetes care and metabolic control from diagnosis. RESULTS: Type 1 diabetes participants and control subjects reported similar levels of current well-being but for the youth with type 1 diabetes, the mental health referral rates over the previous 12 years were higher by 19% and school completion rates were lower by 17%. Over one-third of clinical participants were not currently receiving specialist care and this group had higher mental health service usage in the past (61 vs. 33%) and lower current psychosocial well- being. Within the type 1 diabetes group, behavior problems, high activity, and low family cohesion at diagnosis predicted lower current well-being, but were not associated with metabolic control history. Poorer metabolic control was associated with higher mental health service usage. CONCLUSIONS: Type 1 diabetes participants report similar levels of current psychosocial well-being compared with control subjects, but higher levels of psychiatric morbidity since diagnosis and lower school completion rates. Psychiatric morbidity was associated with poor metabolic control and failure to transition to tertiary adult diabetes care.