The most intriguing problems in genetics epidemiology are to predict genetic disease susceptibility and to associate single nucleotide polymorphisms (SNPs) with diseases. In such these studies, it is necessary to resolve the ambiguities in genetic data. The primary obstacle for ambiguity resolution is that the physical methods for separating two haplotypes from an individual genotype (phasing) are too expensive. Although computational haplotype inference is a well-explored problem, high error rates continue to deteriorate association accuracy. Secondly, it is essential to use a small subset of informative SNPs (tag SNPs) accurately representing the rest of the SNPs (tagging). Tagging can achieve budget savings by genotyping only a limited number of SNPs and computationally inferring all other SNPs. Recent successes in high throughput genotyping technologies drastically increase the length of available SNP sequences. This elevates importance of informative SNP selection for compaction of huge genetic data in order to make feasible fine genotype analysis. Finally, even if complete and accurate data is available, it is unclear if common statistical methods can determine the susceptibility of complex diseases. The dissertation explores above computational problems with a variety of methods, including linear algebra, graph theory, linear programming, and greedy methods. The contributions include (1)significant speed-up of popular phasing tools without compromising their quality, (2)stat-of-the-art tagging tools applied to disease association, and (3)graph-based method for disease tagging and predicting disease susceptibility.

Nucleic acids, as one of the most important macromolecules in living systems, play critical roles in storing, transferring, regulating genetic information, directing proteins synthesis, and catalysis. Understanding the structure of nucleic acid can bring us valuable information for mechanistic study and for drug discovery as well. Among all experimental methods, X-ray crystallography is the most powerful tool in structural biology study to reveal the 3D structure of macromolecules, which has provided over 80% of the highly detailed structural information to date. However, this great technology comes with two disturbing features, crystallization and phasing. The covalent selenium modification of nucleic acids has been proven to be a powerful tool to address both issues in nucleic acid crystallography. First part of this dissertation focuses on the development of novel selenium-modified nucleic acids (SeNA) for crystallization and phasing of B-form DNA containing structures. The novel 2’-SeMeANA modification is the first and currently the only selenium modification, which is fully compatible with X-ray crystallographic study of B-form DNA. Since selenium derivatization at 2’-arabino position dose not affect the B-type 2’-endo sugar conformation, this strategy is suitable for incorporating selenium into DNA for structural studies of B-DNA, DNA-protein complexes, and DNA-drug complexes. Specific base pairing is essential to many biological processes, including replication, transcription, and translation. It is crucial to NA (nucleic acid) sequence-based diagnostic and therapeutic applications as well. By utilizing the unique steric and electronic property of selenium, we designed, synthesized the novel 2-Se-U RNA modification, and demonstrated its highly specific base-pairing property by both biophysical and crystallographic methods. Our studies of 2-Se-U-containing RNAs suggest that this single-atom replacement can largely improve base pairing fidelity against U/G wobble pair, without significant impact on U/A pair.

This work consists of a set of eight vector graphics animations exploring phasing loops, intended to be displayed on televisions and monitors, for home use or exhibition in art galleries as Generative Cinema installations. By combining animated loops with different durations it is possible to generate complex images created by simpler basic elements through a phasing effect. After the first loop, the animation gradually desynchronizes. The different combinations resulting from the layering of desynchronized loops generate image variation until the loops return to unison and restart the cycle. The duration of the phasing cycles of six of the eight pieces reach orders of magnitude over 10^19 frames, which, at a rate of 24 frames per second, is equivalent to the estimated age of the universe (14 billion years). The imagery of the resulting pieces is based on research on properties and structural elements of analog and digital electronic media. This work combines different elements that are present in works from avant-garde movements such as Structural Film, the graphic aspect from Absolute Film, John Cage’s and Andy Warhol’s approaches to the element of time (duration), and the explorations by video artist Nam-June Paik. The generative aspect of this work references minimalist composers and visual artist and composer Brian Eno. This thesis documents the research with analog and digital technologies, and the development of this installation.

Next-generation sequencing is revolutionising in genetics, where base-by base information for the whole genome is available for a large sample of individuals. This type of data is becoming commonly used and will continue to be in the near future. One of the first questions arising is the identification of novel variants and subsequently genotype calling of the individuals in the sample. However, given the cost of sequencing, so far most projects are sequencing individuals in low to medium coverage. In this thesis, we present two distinct methods for SNP and genotype calling from low-coverage sequencing data, TreeCall and MVNcall, that combine sequencing and Linkage Disequilibrium (LD) information. We begin by describing the pipeline for next-generation sequencing analysis and existing methods for SNP and genotype calling using low-coverage sequencing information. Subsequently, we present the two novel LD-based methods for SNP and genotype calling. The two methods developed assume a study design where the individuals are both genotyped and sequenced at low-coverage. The genotypes are used to construct a haplotype scaffold, where the LD information is extracted, either by the construction of genealogical trees (TreeCall), or the approximation of a windows of contiguous SNPs of the scaffold by a multivariate normal distribution (MVNcall). Both methods have been applied on real datasets from the 1000 Genomes project and compared to other LD-based methods applied on the same datasets, mainly in terms of genotype calling and phasing. Whereas TreeCall gives lower genotype concordance rates than the other methods, MVNcall provides the highest genotype concordance rates for a dataset with a small sample size (Lowcoverage pilot of the 1000 Genomes project). Applying the MVNcall on a larger dataset (Phase 1 of the 1000 Genomes project), it achieves an overall genotype discordance rate of 0.58%, whereas SNPTools achieves an overall genotype discordance rate of 0.57%, Thunder 0.56%, and BEAGLE 0.61% (comparison based on Axiom chip). The main advantage of MVNcall is in terms of phasing accuracy, where by using a haplotype scaffold, and especially in the case where the haplotype scaffold is phased using pedigree information, it provides accurate haplotypes. MVNcall is also extended to incorporate trio information for genotype calling. Experiment on a deeply sequenced trio leads to an accurate set of haplotypes of the trio with switch error rates as low as ~0.28 for the parents and ~0.12 for the offspring.

Master of Landscape Architecture / Department of Landscape Architecture/Regional & Community Planning / Laurence A. Clement / The City of Manhattan, Kansas (“the City”) is planning a landscape improvement project for a 0.3-mile portion of one of its non-vehicular rights-of-way (“the Trail”). The focus of the City’s project is to resolve safety issues that have arisen due to a lack of nighttime lighting. While the City’s plan is to implement lighting, this plan would not comprehensively address the Trail users’ and stakeholders’ needs. This study asks, “What design alternatives can be generated to address lighting, safety, and other user and stakeholder concerns for the Trail?” This study employs a literature review, a site inventory and analysis, and a pair of surveys to facilitate the synthesis of a series of design alternatives. The literature review analyzes urban design theory and environmental psychology research to develop a series of design considerations. The site inventory and analysis documents the Trail’s existing conditions through photography, drafting, inventory, observation, and dérive. User and stakeholder surveys were also conducted to gauge existing usage patterns and perceptions of the Trail. From the findings of these methods, a series of environmental designs were developed which respond to users’ experience and stakeholders’ needs as they use and consider the Trail. These designs range on a spectrum of intervention from “minimal” to “high.” It was determined that there are two key regions of the Trail which need immediate attention: an area of thick overgrowth (“the Tunnel”) and an area of ponding and erosion (“the Low Water Crossing”). Additional design considerations were also revealed and addressed by the design alternatives. These designs where then presented to a group of stakeholders who determined that rather than implementing one intervention level, a phasing strategy to implement all intervention levels would be of particular interest. This study also reveals the potential need for a future study about the Trail which would allow stakeholders to analyze the effects of specific, constructed design interventions.

Genotype microarrays assay hundreds of thousands of genetic variants on an individual's genome. The availability of this high throughput genotyping capability has transformed the field of genetics over the past decade by enabling thousands of individuals to be rapidly assayed. This has lead to the discovery of hundreds of genetic variants that are associated with disease and other phenotypes in genome wide association studies (GWAS). These data have also brought with them a number of new statistical and computational challenges. This thesis deals with two primary analysis problems involving microarray data; genotype calling and haplotype inference. Genotype calling involves converting the noisy bivariate fluorescent signals generated by microarray data into genotype values for each genetic variant and individual. Poor quality genotype calling can lead to false positives and loss of power in GWAS so this is an important task. We introduce a new genotype calling method that is highly accurate and has the novel capability of fusing microarray data with next-generation sequencing data for greater accuracy and fewer missing values. Our new method compares favourably to other available genotype calling software. Haplotype inference (or phasing) involves deconvolving these genotypes into the two inherited parental chromosomes for an individual. The development of phasing methods has been a fertile field for statistical genetics research for well over ten years. Depending on the demography of a cohort, different phasing methods may be more appropriate than others. We review the popular offerings and introduce a new approach to try and unify two distinct problems; the phasing of extended pedigrees and the phasing of unrelated individuals. We conduct an extensive comparison of phasing methods on real and simulated data. Finally we demonstrate some preliminary results on extending methodology to sample sizes in the tens of thousands.

This thesis relates to the development of the Ambidextrous Robot Hand engineered in Brunel University. Assigned to a robotic hand, the ambidextrous feature means that two different behaviours are accessible from a single robot hand, because of its fingers architecture which permits them to bend in both ways. On one hand, the robotic device can therefore behave as a right hand whereas, on another hand, it can behave as a left hand. The main contribution of this project is its ambidextrous feature, totally unique in robotics area. Moreover, the Ambidextrous Robot Hand is actuated by pneumatic artificial muscles (PAMs), which are not commonly used to drive robot hands. The type of the actuators consequently adds more originality to the project. The primary challenge is to reach an ambidextrous behaviour using PAMs designed to actuate non-ambidextrous robot hands. Thus, a feasibility study is carried out for this purpose. Investigating a number of mechanical possibilities, an ambidextrous design is reached with features almost identical for its right and left sides. A testbench is thereafter designed to investigate this possibility even further to design ambidextrous fingers using 3D printing and an asymmetrical tendons routing engineered to reduce the number of actuators. The Ambidextrous Robot Hand is connected to a remote control interface accessible from its website, which provides video streaming as feedback, to be eventually used as an online rehabilitation device. The secondary main challenge is to implement control algorithms on a robot hand with a range twice larger than others, with an asymmetrical tendons routing and actuated by nonlinear actuators. A number of control algorithms are therefore investigated to interact with the angular displacement of the fingers and the grasping abilities of the hand. Several solutions are found out, notably the implementations of a phasing plane switch control and a sliding-mode control, both specific to the architecture of the Ambidextrous Robot Hand. The implementation of these two algorithms on a robotic hand actuated by PAMs is almost as innovative as the ambidextrous design of the mechanical structure itself.

X-ray lasers are creating unprecedented research opportunities in physics,chemistry and biology. The peak brightness of these lasers exceeds presentsynchrotrons by 1010, the coherence degeneracy parameters exceedsynchrotrons by 109, and the time resolution is 105 times better. In theduration of a single flash, the beam focused to a micron-sized spot has the samepower density as all the sunlight hitting the Earth, focused to a millimetresquare. Ultrafast coherent X-ray diffractive imaging (CXDI) with X-ray lasers exploitsthese unique properties of X-ray lasers to obtain high-resolution structures fornon-crystalline biological (and other) objects. In such an experiment, thesample is quickly vaporised, but not before sufficient scattered light can berecorded. The continuous diffraction pattern can then be phased and thestructure of a more or less undamaged sample recovered% (speed of light vs. speed of a shock wave).This thesis presents results from the first ultrafast X-ray diffractive imagingexperiments with linear accelerator-driven free-electron lasers and fromoptically-driven table-top X-ray lasers. It also explores the possibility ofinvestigating phase transitions in crystals by X-ray lasers. An important problem with ultrafast CXDI of small samples such as single proteinmolecules is that the signal from a single measurement will be small, requiringsignal enhancement by averaging over multiple equivalent samples. We present anumerical investigation of the problems, including the case where samplemolecules are not exactly identical, and propose tentative solutions. A new software package (Hawk) has been developed for data processing and imagereconstruction. Hawk is the first publicly available software package in thisarea, and it is released as an open source software with the aspiration offostering the development of this field.

DNA polymerase binds to the double stranded DNA and extends the primer strand by adding deoxyribonucletide to the 3’-end. Several reactions in the polymerase active site have been reported by Kornberg in addition to the polymerization. We observed DNA polymerase I can act as a pyrophosphatase and hydrolyze deoxyribonucletide. In performing the pyrophosphatase activity, DNA polymerase I requires to interact with RNA. RNA in general, was found to activate the DNA polymerase I as pyrophosphatase. This hydrolysis causes depletion of dNTP and inhibits DNA polymeration synthesis in vitro. In this RNA-dependent catalysis, DNA polymerase I catalyzes only dNTP but not rNTP. We have also observed that many other DNA polymerases have this type of the RNA-dependent pyrophosphatase activity. Our experimental data suggest that the exonuclease active sites most likely play the critical role in this RNA-dependent dNTP hydrolysis, which might have a broader impact on biological systems. On the basis of the crystal structure of a ternary complex of RNase H (Bacillus halodurans), DNA, and RNA, we have introduced the selenium modification at the 6-position of guanine (G) by replacing the oxygen (SeG). The SeG has been incorporated into DNA (6 nt. - 6 nucleotides) by solid phase synthesis. The crystal structure and biochemical studies with the modified SeG-DNA indicate that the SeDNA can base-pair with the RNA substrate and serve as a template for the RNA hydrolysis. In the crystal structure, it has been observed that the selenium introduction causes shifting (or unwinding) of the G-C base pair by 0.3 Å. Furthermore, the Se-modification can significately enhance the phosphate backbone cleavage (over 1000 fold) of the RNA substrate, although the modifications are remotely located on the DNA bases. This enhancement in the catalytic step is probably attributed to the unwinding of the local duplex, which shifts scissile phosphate bond towards the enzyme active site. Our structural, kinetic and thermodynamic investigations suggest a novel mechanism of RNase H catalysis, which was revealed by the atom-specific selenium modification.

The accessibility of high-throughput biology data brought a great deal of attention to disease association studies. High density maps of single nucleotide polymorphism (SNP's) as well as massive genotype data with large number of individuals and number of SNP's become publicly available. By now most analysis of the new data is undertaken by the statistics community. In this dissertation, we pursue a different line of attack on genetic susceptibility to complex disease that adheres to the computer science community with an emphasis on design rather than analytical methodology. The main goal of disease association analysis is to identify gene variations contributing to the risk of and/or susceptibility to a particular disease. There are basically two main steps in susceptibility: (i) haplotyping of the population and (ii) predicting the genetic susceptibility to diseases. Although there exist many phasing methods for step (i), phasing and missing data recovery for data representing family trios is lagging behind, and most disease association studies are based on family trios. This study is devoted to the problem of assessing accumulated information targeting to predict genotype susceptibility to complex diseases with significantly high accuracy and statistical power. The dissertation proposes two new greedy and integer linear programming based solution methods for step (i). We also proposed several universal and ad hoc methods for step (ii). The quality of susceptibility prediction algorithm has been assessed using leave-one-out and leave-many-out tests and shown to be statistically significant based on randomization tests. The prediction of disease status can also be viewed as an integrated risk factor. A combinatorial prediction complexity measure has been proposed for case/control studies. The best prediction rate achieved by the proposed algorithms is 69.5% for Crohn's disease and 61.3% for autoimmune disorder, respectively, which are significantly higher than those achieved by universal prediction methods such as Support Vector Machine (SVM) and known statistic methods.