Desmond S. Lun

Minimum-cost multicast over coded packet networks

We consider the problem of establishing minimum-cost multicast connections over coded packet networks, i.e., packet networks where the contents of outgoing packets are arbitrary, causal functions of the contents of received packets. We consider both wireline and wireless packet networks as well as both static multicast (where membership of the multicast group remains constant for the duration of the connection) and dynamic multicast (where membership of the multicast group changes in time, with nodes joining and leaving the group). For static multicast, we reduce the problem to a polynomial-time solvable optimization problem, and we present decentralized algorithms for solving it. These algorithms, when coupled with existing decentralized schemes for constructing network codes, yield a fully decentralized approach for achieving minimum-cost multicast. By contrast, establishing minimum-cost static multicast connections over routed packet networks is a very difficult problem even using centralized computation, except in the special cases of unicast and broadcast connections. For dynamic multicast, we reduce the problem to a dynamic programming problem and apply the theory of dynamic programming to suggest how it may be solved.

Achieving minimum-cost multicast: a decentralized approach based on network coding

We present decentralized algorithms that compute minimum-cost subgraphs for establishing multicast connections in networks that use coding. These algorithms, coupled with existing decentralized schemes for constructing network codes, constitute a fully decentralized approach for achieving minimum-cost multicast. Our approach is in sharp contrast to the prevailing approach based on approximation algorithms for the directed Steiner tree problem, which is suboptimal and generally assumes centralized computation with full network knowledge. We also give extensions beyond the basic problem of fixed-rate multicast in networks with directed point-to-point links, and consider the case of elastic rate demand as well as the problem of minimum-energy multicast in wireless networks.

Interpreting expression data with metabolic flux models: predicting Mycobacterium tuberculosis mycolic acid production.

Metabolism is central to cell physiology, and metabolic disturbances play a role in numerous disease states. Despite its importance, the ability to study metabolism at a global scale using genomic technologies is limited. In principle, complete genome sequences describe the range of metabolic reactions that are possible for an organism, but cannot quantitatively describe the behaviour of these reactions. We present a novel method for modeling metabolic states using whole cell measurements of gene expression. Our method, which we call E-Flux (as a combination of flux and expression), extends the technique of Flux Balance Analysis by modeling maximum flux constraints as a function of measured gene expression. In contrast to previous methods for metabolically interpreting gene expression data, E-Flux utilizes a model of the underlying metabolic network to directly predict changes in metabolic flux capacity. We applied E-Flux to Mycobacterium tuberculosis, the bacterium that causes tuberculosis (TB). Key components of mycobacterial cell walls are mycolic acids which are targets for several first-line TB drugs. We used E-Flux to predict the impact of 75 different drugs, drug combinations, and nutrient conditions on mycolic acid biosynthesis capacity in M. tuberculosis, using a public compendium of over 400 expression arrays. We tested our method using a model of mycolic acid biosynthesis as well as on a genome-scale model of M. tuberculosis metabolism. Our method correctly predicts seven of the eight known fatty acid inhibitors in this compendium and makes accurate predictions regarding the specificity of these compounds for fatty acid biosynthesis. Our method also predicts a number of additional potential modulators of TB mycolic acid biosynthesis. E-Flux thus provides a promising new approach for algorithmically predicting metabolic state from gene expression data.

Codecast: a network-coding-based ad hoc multicast protocol

In this article we present CodeCast, a network-coding-based ad hoc multicast protocol. CodeCast is especially well-suited for multimedia applications with low-loss, low-latency constraints such as audio/video streaming. The key ingredient of CodeCast is random network coding, which transparently implements both localized loss recovery and path diversity with very low overhead. Simulation results show that in a typical setting, CodeCast yields a nearly 100 percent delivery ratio, as compared to a 94 percent delivery ratio by traditional multicast. More importantly, the overhead is reduced by as much as 50 percent

Network Coding for Multiple Unicasts: An Approach based on Linear Optimization

In this paper we consider the application of network coding to a multiple unicast setup. We present two suboptimal, yet practical code construction techniques. One consists of a linear program and the other of an integer program with fewer variables and constraints. We discuss the performance of the proposed techniques as well as their complexity

Accurate inference of shoot biomass from high-throughput images of cereal plants

With the establishment of advanced technology facilities for high throughput plant phenotyping, the problem of estimating plant biomass of individual plants from their two dimensional images is becoming increasingly important. The approach predominantly cited in literature is to estimate the biomass of a plant as a linear function of the projected shoot area of plants in the images. However, the estimation error from this model, which is solely a function of projected shoot area, is large, prohibiting accurate estimation of the biomass of plants, particularly for the salt-stressed plants. In this paper, we propose a method based on plant specific weight for improving the accuracy of the linear model and reducing the estimation bias (the difference between actual shoot dry weight and the value of the shoot dry weight estimated with a predictive model). For the proposed method in this study, we modeled the plant shoot dry weight as a function of plant area and plant age. The data used for developing our model and comparing the results with the linear model were collected from a completely randomized block design experiment. A total of 320 plants from two bread wheat varieties were grown in a supported hydroponics system in a greenhouse. The plants were exposed to two levels of hydroponic salt treatments (NaCl at 0 and 100 mM) for 6 weeks. Five harvests were carried out. Each time 64 randomly selected plants were imaged and then harvested to measure the shoot fresh weight and shoot dry weight. The results of statistical analysis showed that with our proposed method, most of the observed variance can be explained, and moreover only a small difference between actual and estimated shoot dry weight was obtained. The low estimation bias indicates that our proposed method can be used to estimate biomass of individual plants regardless of what variety the plant is and what salt treatment has been applied. We validated this model on an independent set of barley data. The technique presented in this paper may extend to other plants and types of stresses.

Large-scale identification of genetic design strategies using local search

In the past decade, computational methods have been shown to be well suited to unraveling the complex web of metabolic reactions in biological systems. Methods based on flux–balance analysis (FBA) and bi‐level optimization have been used to great effect in aiding metabolic engineering. These methods predict the result of genetic manipulations and allow for the best set of manipulations to be found computationally. Bi‐level FBA is, however, limited in applicability because the required computational time and resources scale poorly as the size of the metabolic system and the number of genetic manipulations increase. To overcome these limitations, we have developed Genetic Design through Local Search (GDLS), a scalable, heuristic, algorithmic method that employs an approach based on local search with multiple search paths, which results in effective, low‐complexity search of the space of genetic manipulations. Thus, GDLS is able to find genetic designs with greater in silico production of desired metabolites than can feasibly be found using a globally optimal search and performs favorably in comparison with heuristic searches based on evolutionary algorithms and simulated annealing.

Network Coding for Efficient Wireless Unicast

We consider the problem of establishing an efficient unicast connection over a wireless packet network. We show how network coding, combined with distributed flow optimization, gives a practicable approach that promises to significantly outperform the present approach of end-to-end or link-by-link retransmission combined with route optimization, where performance may be measured in terms of energy consumption, congestion, or any other cost that increases with the number of transmissions made by each node. We present a specific coding scheme and specific distributed flow optimization techniques that may be used to form the basis of a protocol

Remodeling of intermediate metabolism in the diatom Phaeodactylum tricornutum under nitrogen stress

Significance When starved for nutrients, diatoms redirect carbon toward biosynthesis of storage lipids, triacylglycerols (TAGs). We examined how this modification is achieved in the diatom Phaeodactylum tricornutum. Under nitrogen stress, the cells cannibalized their photosynthetic apparatus while recycling intracellular nitrogen and redirecting it to synthesize nitrogen assimilation enzymes. Simultaneously, they allocated newly fixed carbon toward lipids. In contrast, a nitrate reductase knocked-down strain shunted ∼40% more carbon toward TAGs than the wild type without losing photosynthetic capacity. Our results show that diatoms can remodel their intermediate metabolism on environmental cues and reveal that a key signal in this remodeling is associated with nitrogen assimilation. This insight informs a strategy of developing a much more efficient pathway to produce algal-based biofuels. Diatoms are unicellular algae that accumulate significant amounts of triacylglycerols as storage lipids when their growth is limited by nutrients. Using biochemical, physiological, bioinformatics, and reverse genetic approaches, we analyzed how the flux of carbon into lipids is influenced by nitrogen stress in a model diatom, Phaeodactylum tricornutum. Our results reveal that the accumulation of lipids is a consequence of remodeling of intermediate metabolism, especially reactions in the tricarboxylic acid and the urea cycles. Specifically, approximately one-half of the cellular proteins are cannibalized; whereas the nitrogen is scavenged by the urea and glutamine synthetase/glutamine 2-oxoglutarate aminotransferase pathways and redirected to the de novo synthesis of nitrogen assimilation machinery, simultaneously, the photobiological flux of carbon and reductants is used to synthesize lipids. To further examine how nitrogen stress triggers the remodeling process, we knocked down the gene encoding for nitrate reductase, a key enzyme required for the assimilation of nitrate. The strain exhibits 40–50% of the mRNA copy numbers, protein content, and enzymatic activity of the wild type, concomitant with a 43% increase in cellular lipid content. We suggest a negative feedback sensor that couples photosynthetic carbon fixation to lipid biosynthesis and is regulated by the nitrogen assimilation pathway. This metabolic feedback enables diatoms to rapidly respond to fluctuations in environmental nitrogen availability.

On Feedback for Network Coding

In this paper we examine possible ways that feedback can be used, in the context of systems with network coding capabilities. We illustrate, through a number of simple examples, that use of feedback can be employed for parameter adaptation to satisfy QoS requirements as well as for reliability purposes. We also argue that there are benefits in applying network coding to the feedback packets themselves, and finally, we examine the design of acknowledgment packets.