Stochastic models for regulatory networks of the genetic toggle switch

Bistability arises within a wide range of biological systems from the λ phage switch in bacteria to cellular signal transduction pathways in mammalian cells. Changes in regulatory mechanisms may result in genetic switching in a bistable system. Recently, more and more experimental evidence in the form of bimodal population distributions indicates that noise plays a very important role in the switching of bistable systems. Although deterministic models have been used for studying the existence of bistability properties under various system conditions, these models cannot realize cell-to-cell fluctuations in genetic switching. However, there is a lag in the development of stochastic models for studying the impact of noise in bistable systems because of the lack of detailed knowledge of biochemical reactions, kinetic rates, and molecular numbers. In this work, we develop a previously undescribed general technique for developing quantitative stochastic models for large-scale genetic regulatory networks by introducing Poisson random variables into deterministic models described by ordinary differential equations. Two stochastic models have been proposed for the genetic toggle switch interfaced with either the SOS signaling pathway or a quorum-sensing signaling pathway, and we have successfully realized experimental results showing bimodal population distributions. Because the introduced stochastic models are based on widely used ordinary differential equation models, the success of this work suggests that this approach is a very promising one for studying noise in large-scale genetic regulatory networks.

Mean and variance of estimates of the bispectrum of a harmonic random process-an analysis including leakage effects

Analytical expressions are derived for the mean and variance, of estimates of the bispectrum of a real-time series assuming a cosinusoidal model. The effects of spectral leakage, inherent in discrete Fourier transform operation when the modes present in the signal have a nonintegral number of wavelengths in the record, are included in the analysis. A single phase-coupled triad of modes can cause the bispectrum to have a nonzero mean value over the entire region of computation owing to leakage. The variance of bispectral estimates in the presence of leakage has contributions from individual modes and from triads of phase-coupled modes. Time-domain windowing reduces the leakage. The theoretical expressions for the mean and variance of bispectral estimates are derived in terms of a function dependent on an arbitrary symmetric time-domain window applied to the record. the number of data, and the statistics of the phase coupling among triads of modes. The theoretical results are verified by numerical simulations for simple test cases and applied to laboratory data to examine phase coupling in a hypothesis testing framework

Compilation of somatic mutations of the CDKN2 gene in human cancers : non-random distribution of base substitutions

The CDKN2 gene, encoding the cyclin-dependent kinase inhibitor p16, is a tumour suppressor gene that maps to chromosome band 9p21-p22. The most common mechanism of inactivation of this gene in human cancers is through homozygous deletion; however, in a smaller proportion of tumours and tumour cell lines intragenic mutations occur. In this study we have compiled a database of over 120 published point mutations in the CDKN2 gene from a wide variety of tumour types. A further 50 deletions, insertions, and splice mutations in CDKN2 have also been compiled. Furthermore, we have standardised the numbering of all mutations according to the full-length 156 amino acid form of p16. From this study we are able to define several hot spots, some of which occur at conserved residues within the ankyrin domains of p16. While many of the hotspots are shared by a number of cancers, the relative importance of each position varies, possibly reflecting the role of different carcinogens in the development of certain tumours. As reported previously, the mutational spectrum of CDKN2 in melanomas differs from that of internal malignancies and supports the involvement of UV in melanoma tumorigenesis. Notably, 52% of all substitutions in melanoma-derived samples occurred at just six nucleotide positions. Nonsense mutations comprise a comparatively high proportion of mutations present in the CDKN2 gene, and possible explanations for this are discussed.

Look before you leap : a confidence-based method for selecting species criticality while avoiding negative populations in τ-leaping

The stochastic simulation algorithm was introduced by Gillespie and in a different form by Kurtz. There have been many attempts at accelerating the algorithm without deviating from the behavior of the simulated system. The crux of the explicit τ-leaping procedure is the use of Poisson random variables to approximate the number of occurrences of each type of reaction event during a carefully selected time period, τ. This method is acceptable providing the leap condition, that no propensity function changes “significantly” during any time-step, is met. Using this method there is a possibility that species numbers can, artificially, become negative. Several recent papers have demonstrated methods that avoid this situation. One such method classifies, as critical, those reactions in danger of sending species populations negative. At most, one of these critical reactions is allowed to occur in the next time-step. We argue that the criticality of a reactant species and its dependent reaction channels should be related to the probability of the species number becoming negative. This way only reactions that, if fired, produce a high probability of driving a reactant population negative are labeled critical. The number of firings of more reaction channels can be approximated using Poisson random variables thus speeding up the simulation while maintaining the accuracy. In implementing this revised method of criticality selection we make use of the probability distribution from which the random variable describing the change in species number is drawn. We give several numerical examples to demonstrate the effectiveness of our new method.

Development of a high-level gene expression system for the production of bioplastics in sugarcane

Despite various approaches, the production of biodegradable plastics such as polyhydroxybutyrate (PHB) in transgenic plants has met with limited success due largely to low expression levels. Even in the few instances where high levels of protein expression have been reported, the transgenic plants have been stunted indicating PHB is phytotoxic (Poirier 2002). This PhD describes the application of a novel virus-based gene expression technology, termed InPAct („In Plant Activation.), for the production of PHB in tobacco and sugarcane. InPAct is based on the rolling circle replication mechanism by which circular ssDNA viruses replicate and provides a system for controlled, high-level gene expression. Based on these features, InPAct was thought to represent an ideal system to enable the controlled, high-level expression of the three phb genes (phbA, phbB and phbC) required for PHB production in sugarcane at a preferred stage of plant growth. A Tobacco yellow dwarf virus (TbYDV)-based InPAct-phbA vector, as well as linear vectors constitutively expressing phbB and phbC were constructed and different combinations were used to transform tobacco leaf discs. A total of four, eight, three and three phenotypically normal tobacco lines were generated from discs transformed with InPAct-phbA, InPAct-phbA + p1300-TaBV P-phbB/phbC- 35S T, p1300-35S P-phbA-NOS T + p1300-TaBV P-phbB/phbC-35S T and InPAct-GUS, respectively. To determine whether the InPAct cassette could be activated in the presence of the TbYDV Rep, leaf samples from the eight InPActphbA + p1300-TaBV P-phbB/phbC-35S T plants were agroinfiltrated with p1300- TbYDV-Rep/RepA. Three days later, successful activation was indicated by the detection of episomes using both PCR and Southern analysis. Leaf discs from the eight InPAct-phbA + p1300-TaBV P-phbB/phbC-35S T transgenic plant lines were agroinfiltrated with p1300-TbYDV-Rep/RepA and leaf tissue was collected ten days post-infiltration and examined for the presence of PHB granules. Confocal microscopy and TEM revealed the presence of typical PHB granules in five of the eight lines, thus demonstrating the functionality of InPActbased PHB production in tobacco. However, analysis of leaf extracts by HPLC failed to detect the presence of PHB suggesting only very low level expression levels. Subsequent molecular analysis of three lines revealed low levels of correctly processed mRNA from the catalase intron contained within the InPAct cassette and also the presence of cryptic splice sites within the intron. In an attempt to increase expression levels, new InPAct-phb cassettes were generated in which the castorbean catalase intron was replaced with a synthetic intron (syntron). Further, in an attempt to both increase and better control Rep/RepA-mediated activation of InPAct cassettes, Rep/RepA expression was placed under the control of a stably integrated alc switch. Leaf discs from a transgenic tobacco line (Alc ML) containing 35S P-AlcR-AlcA P-Rep/RepA were supertransformed with InPAct-phbAsyn or InPAct-GUSsyn using Agrobacterium and three plants (lines) were regenerated for each construct. Analysis of the RNA processing of the InPAct-phbAsyn cassette revealed highly efficient and correct splicing of the syntron, thus supporting its inclusion within the InPAct system. To determine the efficiency of the alc switch to activate InPAct, leaf material from the three Alc ML + InPAct-phbAsyn lines was either agroinfiltrated with 35S P-Rep/RepA or treated with ethanol. Unexpectedly, episomes were detected not only in the infiltrated and ethanol treated samples, but also in non-treated samples. Subsequent analysis of transgenic Alc ML + InPAct-GUS lines, confirmed that the alc switch was leaky in tissue culture. Although this was shown to be reversible once plants were removed from the tissue culture environment, it made the regeneration of Alc ML + InPAct-phbsyn plant lines extremely difficult, due to unintentional Rep expression and therefore high levels of phb expression and phytotoxic PHB production. Two Alc ML + InPAct-phbAsyn + p1300-TaBV P-phbB/phbC-35S T transgenic lines were able to be regenerated, and these were acclimatised, alcohol-treated and analysed. Although episome formation was detected as late as 21 days post activation, no PHB was detected in the leaves of any plants using either microscopy or HPLC, suggesting the presence of a corrupt InPAct-phbA cassette in both lines. The final component of this thesis involved the application of both the alc switch and the InPAct systems to sugarcane in an attempt to produce PHB. Initial experiments using transgenic Alc ML + InPAct-GUS lines indicated that the alc system was not functional in sugarcane under the conditions tested. The functionality of the InPAct system, independent of the alc gene switch, was subsequently examined by bombarding the 35S Rep/RepA cassette into leaf and immature leaf whorl cells derived from InPAct-GUS transgenic sugarcane plants. No GUS expression was observed in leaf tissue, whereas weak and irregular GUS expression was observed in immature leaf whorl tissue derived from two InPAct- GUS lines and two InPAct-GUS + 35S P-AlcR-AlcA P-GUS lines. The most plausible reason to explain the inconsistent and low levels of GUS expression in leaf whorls is a combination of low numbers of sugarcane cells in the DNA replication-conducive S-phase and the irregular and random nature of sugarcane cells bombarded with Rep/RepA. This study details the first report to develop a TbYDV-based InPAct system under control of the alc switch to produce PHB in tobacco and sugarcane. Despite the inability to detect quantifiable levels of PHB levels in either tobacco or sugarcane, the findings of this study should nevertheless assist in the further development of both the InPAct system and the alc system, particularly for sugarcane and ultimately lead to an ethanol-inducible InPAct gene expression system for the production of bioplastics and other proteins of commercial value in plants.

Least-squares congealing for large numbers of images

In this paper we pursue the task of aligning an ensemble of images in an unsupervised manner. This task has been commonly referred to as “congealing” in literature. A form of congealing, using a least-squares criteria, has been recently demonstrated to have desirable properties over conventional congealing. Least-squares congealing can be viewed as an extension of the Lucas & Kanade (LK)image alignment algorithm. It is well understood that the alignment performance for the LK algorithm, when aligning a single image with another, is theoretically and empirically equivalent for additive and compositional warps. In this paper we: (i) demonstrate that this equivalence does not hold for the extended case of congealing, (ii) characterize the inherent drawbacks associated with least-squares congealing when dealing with large numbers of images, and (iii) propose a novel method for circumventing these limitations through the application of an inverse-compositional strategy that maintains the attractive properties of the original method while being able to handle very large numbers of images.

Triangular Linguistic Fuzzy based performance measurement model for supply chain to assess leanness attributes

Increasing global competitiveness worldwide has forced manufacturing organizations to produce high-quality products more quickly and at a competitive cost. In order to reach these goals, they need good quality components from suppliers at optimum price and lead time. This actually forced all the companies to adapt different improvement practices such as lean manufacturing, Just in Time (JIT) and effective supply chain management. Applying new improvement techniques and tools cause higher establishment costs and more Information Delay (ID). On the contrary, these new techniques may reduce the risk of stock outs and affect supply chain flexibility to give a better overall performance. But industry people are unable to measure the overall affects of those improvement techniques with a standard evaluation model .So an effective overall supply chain performance evaluation model is essential for suppliers as well as manufacturers to assess their companies under different supply chain strategies. However, literature on lean supply chain performance evaluation is comparatively limited. Moreover, most of the models assumed random values for performance variables. The purpose of this paper is to propose an effective supply chain performance evaluation model using triangular linguistic fuzzy numbers and to recommend optimum ranges for performance variables for lean implementation. The model initially considers all the supply chain performance criteria (input, output and flexibility), converts the values to triangular linguistic fuzzy numbers and evaluates overall supply chain performance under different situations. Results show that with the proposed performance measurement model, improvement area for each variable can be accurately identified.

Dark numbers: challenges in measuring human trafficking

Over the last decade nations around the world have renewed their efforts to address the problem of human trafficking, following the introduction of the United Nations Protocol to Prevent, Suppress and Punish Trafficking in Persons, Especially Women and Children. In Australia and the United States, legislators sought to quantify and characterise the human trafficking phenomenon, seeking to answer the question — how large is the problem of trafficking? This article explores the attempts of legislators in Australia and the United States to determine how many victims are trafficked into their countries, highlighting the significant uncertainty that still surrounds data on human trafficking. The challenges researchers face in measuring human trafficking are also explored. These challenges include disputes over the definition of a trafficking victim, the limitations of research using sampling to measure the trafficked population, and the mischaracterisation of the trafficking problem as a result of politicisation of the trafficking debate and a focus on trafficking for sexual exploitation versus other forms of labour. This article argues that in the absence of reliable data on trafficking, policy is often informed by misleading or false information.

Sequential fusion of decisions from adaptive and random samples for controlled verification of errors

Fusion techniques have received considerable attention for achieving performance improvement with biometrics. While a multi-sample fusion architecture reduces false rejects, it also increases false accepts. This impact on performance also depends on the nature of subsequent attempts, i.e., random or adaptive. Expressions for error rates are presented and experimentally evaluated in this work by considering the multi-sample fusion architecture for text-dependent speaker verification using HMM based digit dependent speaker models. Analysis incorporating correlation modeling demonstrates that the use of adaptive samples improves overall fusion performance compared to randomly repeated samples. For a text dependent speaker verification system using digit strings, sequential decision fusion of seven instances with three random samples is shown to reduce the overall error of the verification system by 26% which can be further reduced by 6% for adaptive samples. This analysis novel in its treatment of random and adaptive multiple presentations within a sequential fused decision architecture, is also applicable to other biometric modalities such as finger prints and handwriting samples.

Modeling random effect and excess zeros in road traffic accident prediction

Poisson distribution has often been used for count like accident data. Negative Binomial (NB) distribution has been adopted in the count data to take care of the over-dispersion problem. However, Poisson and NB distributions are incapable of taking into account some unobserved heterogeneities due to spatial and temporal effects of accident data. To overcome this problem, Random Effect models have been developed. Again another challenge with existing traffic accident prediction models is the distribution of excess zero accident observations in some accident data. Although Zero-Inflated Poisson (ZIP) model is capable of handling the dual-state system in accident data with excess zero observations, it does not accommodate the within-location correlation and between-location correlation heterogeneities which are the basic motivations for the need of the Random Effect models. This paper proposes an effective way of fitting ZIP model with location specific random effects and for model calibration and assessment the Bayesian analysis is recommended.