Biomedical Image Processing and Classification

Biomedical image processing is an interdisciplinary field involving a variety of disciplines, e.g., electronics, computer science, physics, mathematics, physiology, and medicine. Several imaging techniques have been developed, providing many approaches to the study of the human body. Biomedical image processing is finding an increasing number of important applications in, for example, the study of the internal structure or function of an organ and the diagnosis or treatment of a disease. If associated with classification methods, it can support the development of computer-aided diagnosis (CAD) systems, which could help medical doctors in refining their clinical picture

Investigating the spatial distribution of diabetes in Africa using both classical and Bayesian approaches.

Master of Science in Statistics. University of KwaZulu-Natal, Durban, 2017.Abstract available in PDF file

A morphometric analysis of the Culicoides pulicaris species complex

Imperial Users onl

Computational prediction and analysis of macromolecular interactions

Protein interactions regulate gene expression, cell signaling, catalysis, and many other functions across all of molecular biology. We must understand them quantitatively, and experimental methods have provided the data that form the basis of our current understanding. They remain our most accurate tools. However, their low efficiency and high cost leave room for predictive, computational approaches that can provide faster and more detailed answers to biological problems. A rigid-body simulation can quickly and effectively calculate the predicted interaction energy between two molecular structures in proximity. The fast Fourier-transform-based mapping algorithm FTMap predicts small molecule binding 'hot spots' on a protein's surface and can provide likely orientations of specific ligands of interest that may occupy those hot spots. This process now allows unique ligands to be used by this algorithm while permitting additional small molecular cofactors to remain in their bound conformation. By keeping the cofactors bound, FTMap can reduce false positives where the algorithm identifies a true, but incorrect, ligand pocket where the known cofactor already binds. A related algorithm, ClusPro, can evaluate interaction energies for billions of docked conformations of macromolecular structures. The work reported in this thesis can predict protein-polysaccharide interactions and the software now contains a publicly available feature for predicting protein-heparin interactions. In addition, a new approach for determining regions of predicted activity on a protein's surface allows prediction of a protein-protein interface. This new tool can also identify the interface in encounter complexes formed by the process of protein association—more closely resembling the biological nature of the interaction than the former, calculated, binary, bound and unbound states

Using collections to explore the evolution of plant associated lifestyles in the Ascomycota

The Ascomycota form the largest phylum in the fungal kingdom and show a wide diversity of lifestyles, some involving beneficial or harmful associations with plants. Distinguishing between fungal endophytes – species which live asymptomatically in plant tissues – and plant pathogens is of major significance to economic and ecological issues relating to plant health. Evolutionary genomics methods can provide insight into the genetic determinants of these lifestyles, and collections can act as an invaluable source of material to enable such analyses. As endophytes are comparatively poorly studied, comparing plant associated lifestyles in the Ascomycota first requires novel endophyte discovery. In this thesis, I have demonstrated the unexplored promise of Kew’s Millennium Seed Bank for isolating viable fungal endophytes and, in the process, highlighted the potential issues of overlooking the seed microbiome in the seed banking practice. I then performed whole genome sequencing, assembly and annotation of novel endophytic Fusarium strains for a case-study exploring lifestyle evolution in the genus. The distribution of lifestyles across the phylogeny; similarity of gene repertoires; and patterns of codon optimisation suggested that Fusarium taxa have a shared capacity for pathogenicity/endophytism. Exploring to what extent these results are common to different lineages of the Ascomycota requires the generation of new genomic resources for endophytes at large. Consequently, I sequenced, assembled and annotated genomes for a further 15 endophyte strains from CABI’s collections, which spanned 8 families and 5 orders and additionally represent the first assembly for the genus and/or species for 7 of the strains. Together, this thesis demonstrates the value of existing plant and fungal collections for producing material and data to explore the pathogenic-mutualistic spectrum in plant associated ascomycetes

Non-spurious correlations between genetic and linguistic diversities in the context of human evolution

This thesis concerns human diversity, arguing that it represents not just some form of noise, which must be filtered out in order to reach a deeper explanatory level, but the engine of human and language evolution, metaphorically put, the best gift Nature has made to us. This diversity must be understood in the context of (and must shape) human evolution, of which the Recent Out-of-Africa with Replacement model (ROA) is currently regarded, especially outside palaeoanthropology, as a true theory. It is argued, using data from palaeoanthropology, human population genetics, ancient DNA studies and primatology, that this model must be, at least, amended, and most probably, rejected, and its alternatives must be based on the concept of reticulation. The relationships between the genetic and linguistic diversities is complex, including interindividual genetic and behavioural differences (behaviour genetics) and inter-population differences due to common demographic, geographic and historic factors (spurious correlations), used to study (pre)historical processes. It is proposed that there also exist nonspurious correlations between genetic and linguistic diversities, due to genetic variants which can bias the process of language change, so that the probabilities of alternative linguistic states are altered. The particular hypothesis (formulated with Prof. D. R. Ladd) of a causal relationship between two human genes and one linguistic typological feature is supported by the statistical analysis of a vast database of 983 genetic variants and 26 linguistic features in 49 Old World populations, controlling for geography and known linguistic history. The general theory of non-spurious correlations between genetic and linguistic diversities is developed and its consequences and predictions analyzed. It will very probably profoundly impact our understanding of human diversity and will offer a firm footing for theories of language evolution and change. More specifically, through such a mechanism, gradual, accretionary models of language evolution are a natural consequence of post-ROA human evolutionary models. The unravellings of causal effects of inter-population genetic differences on linguistic states, mediated by complex processes of cultural evolution (biased iterated learning), will represent a major advance in our understanding of the relationship between cultural and genetic diversities, and will allow a better appreciation of this most fundamental and supremely valuable characteristic of humanity - its intrinsic diversity

Genotyping and phenotyping the common pea and its wild relatives

In 1868, three men, Gregor Mendel, Charles Darwin and Friedrich Miescher made significant contributions in genetic inheritance, plant domestication and DNA extraction respectively. 150 years later, this thesis aims to better understand pea domestication through genotyping and phenotyping the common pea and its wild relatives. Peas (Pisum sativum) are a cool season legume important to food security due to their ability to fix nitrogen and produce nutritious food and animal fodder. A core collection of 350 accessions of wild, landrace and cultivated material was developed from the John Innes Pisum Collection. To characterise these accessions, image analysis, a modern phenotyping method was used. Current tools require user expertise, are not cross platform, are not applicable to certain plants or phenotypes. Here, MktStall, a novel multi-organ image analysis is presented, which requires no computational expertise. Pea is a large (4.5Gb) and highly repetitive genome. Here, the first publicly accessible pea genome reference is announced. In combination with a genotyping by sequencing (GBS) approach of this core collection a genome-wide association study (GWAS) was performed using on seed weight, plant height, leaflet margin, seed shape and pod shape. The results in this thesis show statistically significant differences in plant height in cultivars and leaflet length, perimeter and area in landraces in addition to identifying statistically significant loci for leaflet teeth, seed perimeter and seed eccentricity. Furthermore, potential candidate genes have be identified with roles in carbohydrate metabolism known to cause seed wrinkledness and POWERDRESS known to increase leaf area. The combination of novel contributions results in new tools, genomic resources and additional knowledge of pea domestication which can be used in marker assisted selection and improved breeding practices for an important crop for food security

ACARORUM CATALOGUS IX. Acariformes, Acaridida, Schizoglyphoidea (Schizoglyphidae), Histiostomatoidea (Histiostomatidae, Guanolichidae), Canestrinioidea (Canestriniidae, Chetochelacaridae, Lophonotacaridae, Heterocoptidae), Hemisarcoptoidea (Chaetodactylidae, Hyadesiidae, Algophagidae, Hemisarcoptidae, Carpoglyphidae, Winterschmidtiidae)

The 9th volume of the series Acarorum Catalogus contains lists of mites of 13 families, 225 genera and 1268 species of the superfamilies Schizoglyphoidea, Histiostomatoidea, Canestrinioidea and Hemisarcoptoidea. Most of these mites live on insects or other animals (as parasites, phoretic or commensals), some inhabit rotten plant material, dung or fungi. Mites of the families Chetochelacaridae and Lophonotacaridae are specialised to live with Myriapods (Diplopoda). The peculiar aquatic or intertidal mites of the families Hyadesidae and Algophagidae are also included.Publishe