Metabolic Engineering, metabolite profiling and machine learning to investigate the phloem-mobile signal in systemic acquired resistance in tobacco

Draper, J., Darby, R.M., Beckmann, M., Maddison, A.L., Mondhe, M., Sheldrick, C., Taylor, J., Goodacre, R., and Kell, D.B. (2002) Metabolic Engineering, metabolite profiling and machine learning to investigate the phloem-mobile signal in systemic acquired resistance in tobacco. First International Congress on Plant Metabolomics, Wageningen, The Netherlands

Load Profiling in Distributed Real-Time Systems

Load balancing is often used to ensure that nodes in a distributed systems are equally loaded. In this paper, we show that for real-time systems, load balancing is not desirable. In particular, we propose a new load-profiling strategy that allows the nodes of a distributed system to be unequally loaded. Using load profiling, the system attempts to distribute the load amongst its nodes so as to maximize the chances of finding a node that would satisfy the computational needs of incoming real-time tasks. To that end, we describe and evaluate a distributed load-profiling protocol for dynamically scheduling time-constrained tasks in a loosely-coupled distributed environment. When a task is submitted to a node, the scheduling software tries to schedule the task locally so as to meet its deadline. If that is not feasible, it tries to locate another node where this could be done with a high probability of success, while attempting to maintain an overall load profile for the system. Nodes in the system inform each other about their state using a combination of multicasting and gossiping. The performance of the proposed protocol is evaluated via simulation, and is contrasted to other dynamic scheduling protocols for real-time distributed systems. Based on our findings, we argue that keeping a diverse availability profile and using passive bidding (through gossiping) are both advantageous to distributed scheduling for real-time systems.

Load Profiling for Efficient Route Selection in Multi-Class Networks

High-speed networks, such as ATM networks, are expected to support diverse Quality of Service (QoS) constraints, including real-time QoS guarantees. Real-time QoS is required by many applications such as those that involve voice and video communication. To support such services, routing algorithms that allow applications to reserve the needed bandwidth over a Virtual Circuit (VC) have been proposed. Commonly, these bandwidth-reservation algorithms assign VCs to routes using the least-loaded concept, and thus result in balancing the load over the set of all candidate routes. In this paper, we show that for such reservation-based protocols|which allow for the exclusive use of a preset fraction of a resource's bandwidth for an extended period of time-load balancing is not desirable as it results in resource fragmentation, which adversely affects the likelihood of accepting new reservations. In particular, we show that load-balancing VC routing algorithms are not appropriate when the main objective of the routing protocol is to increase the probability of finding routes that satisfy incoming VC requests, as opposed to equalizing the bandwidth utilization along the various routes. We present an on-line VC routing scheme that is based on the concept of "load profiling", which allows a distribution of "available" bandwidth across a set of candidate routes to match the characteristics of incoming VC QoS requests. We show the effectiveness of our load-profiling approach when compared to traditional load-balancing and load-packing VC routing schemes.

Evaluation of a Load Profiling Approach to Routing Guaranteed Bandwidth Flows

To support the diverse Quality of Service (QoS) requirements of real-time (e.g. audio/video) applications in integrated services networks, several routing algorithms that allow for the reservation of the needed bandwidth over a Virtual Circuit (VC) established on one of several candidate routes have been proposed. Traditionally, such routing is done using the least-loaded concept, and thus results in balancing the load across the set of candidate routes. In a recent study, we have established the inadequacy of this load balancing practice and proposed the use of load profiling as an alternative. Load profiling techniques allow the distribution of "available" bandwidth across a set of candidate routes to match the characteristics of incoming VC QoS requests. In this paper we thoroughly characterize the performance of VC routing using load profiling and contrast it to routing using load balancing and load packing. We do so both analytically and via extensive simulations of multi-class traffic routing in Virtual Path (VP) based networks. Our findings confirm that for routing guaranteed bandwidth flows in VP networks, load balancing is not desirable as it results in VP bandwidth fragmentation, which adversely affects the likelihood of accepting new VC requests. This fragmentation is more pronounced when the granularity of VC requests is large. Typically, this occurs when a common VC is established to carry the aggregate traffic flow of many high-bandwidth real-time sources. For VP-based networks, our simulation results show that our load-profiling VC routing scheme performs better or as well as the traditional load-balancing VC routing in terms of revenue under both skewed and uniform workloads. Furthermore, load-profiling routing improves routing fairness by proactively increasing the chances of admitting high-bandwidth connections.

Visualising ribosome profiling and using it for reading frame detection and exploration of eukaryotic translation initiation

Ribosome profiling (ribo-seq) is a recently developed technique that provides genomewide information on protein synthesis (GWIPS) in vivo. The high resolution of ribo-seq is one of the exciting properties of this technique. In Chapter 2, I present a computational method that utilises the sub-codon precision and triplet periodicity of ribosome profiling data to detect transitions in the translated reading frame. Application of this method to ribosome profiling data generated for human HeLa cells allowed us to detect several human genes where the same genomic segment is translated in more than one reading frame. Since the initial publication of the ribosome profiling technique in 2009, there has been a proliferation of studies that have used the technique to explore various questions with respect to translation. A review of the many uses and adaptations of the technique is provided in Chapter 1. Indeed, owing to the increasing popularity of the technique and the growing number of published ribosome profiling datasets, we have developed GWIPS-viz (http://gwips.ucc.ie), a ribo-seq dedicated genome browser. Details on the development of the browser and its usage are provided in Chapter 3. One of the surprising findings of ribosome profiling of initiating ribosomes carried out in 3 independent studies, was the widespread use of non-AUG codons as translation initiation start sites in mammals. Although initiation at non-AUG codons in mammals has been documented for some time, the extent of non-AUG initiation reported by these ribo-seq studies was unexpected. In Chapter 4, I present an approach for estimating the strength of initiating codons based on the leaky scanning model of translation initiation. Application of this approach to ribo-seq data illustrates that initiation at non-AUG codons is inefficient compared to initiation at AUG codons. In addition, our approach provides a probability of initiation score for each start site that allows its strength of initiation to be evaluated.

Profiling side-channel attacks on cryptographic algorithms

Traditionally, attacks on cryptographic algorithms looked for mathematical weaknesses in the underlying structure of a cipher. Side-channel attacks, however, look to extract secret key information based on the leakage from the device on which the cipher is implemented, be it smart-card, microprocessor, dedicated hardware or personal computer. Attacks based on the power consumption, electromagnetic emanations and execution time have all been practically demonstrated on a range of devices to reveal partial secret-key information from which the full key can be reconstructed. The focus of this thesis is power analysis, more specifically a class of attacks known as profiling attacks. These attacks assume a potential attacker has access to, or can control, an identical device to that which is under attack, which allows him to profile the power consumption of operations or data flow during encryption. This assumes a stronger adversary than traditional non-profiling attacks such as differential or correlation power analysis, however the ability to model a device allows templates to be used post-profiling to extract key information from many different target devices using the power consumption of very few encryptions. This allows an adversary to overcome protocols intended to prevent secret key recovery by restricting the number of available traces. In this thesis a detailed investigation of template attacks is conducted, along with how the selection of various attack parameters practically affect the efficiency of the secret key recovery, as well as examining the underlying assumption of profiling attacks in that the power consumption of one device can be used to extract secret keys from another. Trace only attacks, where the corresponding plaintext or ciphertext data is unavailable, are then investigated against both symmetric and asymmetric algorithms with the goal of key recovery from a single trace. This allows an adversary to bypass many of the currently proposed countermeasures, particularly in the asymmetric domain. An investigation into machine-learning methods for side-channel analysis as an alternative to template or stochastic methods is also conducted, with support vector machines, logistic regression and neural networks investigated from a side-channel viewpoint. Both binary and multi-class classification attack scenarios are examined in order to explore the relative strengths of each algorithm. Finally these machine-learning based alternatives are empirically compared with template attacks, with their respective merits examined with regards to attack efficiency.

Profiling phytochemical and nutritional components of potato

Potatoes (Solanum Tuberosum L.) contain secondary metabolites that may have an impact on human health. The aim of this study was to assess the levels of some of these compounds in a wide range of varieties, including rare, heritage and commercial cultivars. Vitamin C, total carotenoids, phenolics, flavonoids, antioxidant activity and glycoalkaloids were determined, using spectroscopy and chromatography, in the skin and flesh of tubers grown in field trials. Transcript levels of key synthetic enzymes were assessed by qPCR. Accumulation of selected metabolites was higher in the skin than in the flesh of tubers, except ascorbate, which was undetected in the skin. Differences were on average 2.5 to 3-fold for carotenoids, 6-fold for phenolics, 15 to 16-fold for flavonoids, 21-fold for glycoalkaloids and 9 to 10-fold for antioxidant activity. Higher contents of carotenoids were associated with yellow skin or flesh, and higher values of phenolics, flavonoids and antioxidant activity with blue flesh. Variety ‘Burren’ had maxima values of carotenoids in skin and flesh, variety ‘Nicola’ of ascorbate, variety ‘Congo’ of phenolics, flavonoids and antioxidant activity in both tissues, except antioxidant activity in the skin, which was higher in ‘Edzell Blue’. Varieties ‘May Queen’ and ‘International Kidney’ had highest glycoalkaloid content in skin and flesh respectively. The effect of the environment was diverse: year of cultivation was significant for all metabolites, but site of cultivation was not for carotenoids and glycoalkaloids. Levels of expression of phenylalanine ammonia-lyase and chalcone synthase were higher in varieties accumulating high contents of phenolic compounds. However, levels of expression of phytoene synthase and L-galactono-1,4-lactone dehydrogenase were not different between varieties showing contrasting levels of carotenoids and ascorbate respectively. This work will help identify varieties that could be marketed as healthier and the most suitable varieties for extraction of high-value metabolites such as glycoalkaloids.

Communal larval rearing of European lobster (Homarus gammarus): family identification by microsatellite DNA profiling an offspring fitness.

Stock enhancement experiments of European lobster (Homarus gammarus) have been carried out around the Kvitsoy Islands in south-western Norway since 1990. In addition to releases of coded wire tagged lobster juveniles (cultured) and subsequent monitoring of commercial fishery, a lobster hatchery was established in 1997. Several experiments were made on the communal-rearing approach where the performance of mixed larval groups (families) was evaluated under identical conditions. Berried females of wild and cultured origin and their respective fertilised eggs were screened by using microsatellite DNA profiling involving a multiplex set of six lobster specific primers, thereby allowing determination of both parental genotypes. Each female were kept separately during hatching, and the offspring were later mixed and raised in a communal rearing system. The early-larval survival was estimated at stage IV (bottom stage), and the survivors were identified to family and group by microsatellite profiling. Five different communal experiments were conducted, representing offspring from 65 berried females. Of the surviving larvae, 6.3% could not be assigned to family due to degraded DNA and no PCR amplification. Significant differences in early survival between offspring of wild and cultured origin were found in the experiments. No differences between the groups were found in stage IV larval size. Based on the pooled data on survival (as a measure of early larvae fitness) offspring of cultured females displayed a relative fitness of 60% in comparison to offspring from wild females. Large variation in survival was also observed among families within the wild and cultured groups, suggesting a genetic component for these traits and a potential for selective breeding.