Prediction of subcellular localization using sequence-biased recurrent networks

Motivation: Targeting peptides direct nascent proteins to their specific subcellular compartment. Knowledge of targeting signals enables informed drug design and reliable annotation of gene products. However, due to the low similarity of such sequences and the dynamical nature of the sorting process, the computational prediction of subcellular localization of proteins is challenging. Results: We contrast the use of feed forward models as employed by the popular TargetP/SignalP predictors with a sequence-biased recurrent network model. The models are evaluated in terms of performance at the residue level and at the sequence level, and demonstrate that recurrent networks improve the overall prediction performance. Compared to the original results reported for TargetP, an ensemble of the tested models increases the accuracy by 6 and 5% on non-plant and plant data, respectively.

Mechanics of raceway hysteresis in a packed bed

When a gas is introduced at high velocity through a nozzle into a packed bed, it creates a raceway in the packed bed. It has been found that the raceway size is larger when it is formed by decreasing the gas velocity from its highest value than when it is formed by increasing the gas velocity. This phenomenon is known as raceway hysteresis. A hypothesis has been oroposed to explain the hysteresis phenomenon based on a force-balance approach which includes frictional, bed-weight, and pressure forces. According to this hypothesis, the frictional force acts in different directions when the raceway is expanding and contracting. In this article, the entire packed bed has been divided into radial and Cartesian co-ordinate systems, and the forces acting on the raceway have been solved analytically for a simplified one-dimensional case. Based on the force-balance approach, a general equation has been obtained to predict the diameter of the raceway for increasing And decreasing velocities. A reasonable agreement has been found between the theoretical predictions and experimental observations. The model has also been compared with published experimental and plant data. The hysteresis mechanism in the packed beds can be described reasonably by taking into consideration the direction of frictional forces for the increasing- and decreasin-velocity cases. The effects of the particleshape factor and void fraction on the raceway hysteresis are examined.

Detecting and sorting targeting peptides wtih neural networks and support vector machines

This paper presents a composite multi-layer classifier system for predicting the subcellular localization of proteins based on their amino acid sequence. The work is an extension of our previous predictor PProwler v1.1 which is itself built upon the series of predictors SignalP and TargetP. In this study we outline experiments conducted to improve the classifier design. The major improvement came from using Support Vector machines as a "smart gate" sorting the outputs of several different targeting peptide detection networks. Our final model (PProwler v1.2) gives MCC values of 0.873 for non-plant and 0.849 for plant proteins. The model improves upon the accuracy of our previous subcellular localization predictor (PProwler v1.1) by 2% for plant data (which represents 7.5% improvement upon TargetP).

Probabilistic cost benefit analysis of generation investment in a deregulated electricity market

A new methodology is proposed for the analysis of generation capacity investment in a deregulated market environment. This methodology proposes to make the investment appraisal using a probabilistic framework. The probabilistic production simulation (PPC) algorithm is used to compute the expected energy generated, taking into account system load variations and plant forced outage rates, while the Monte Carlo approach has been applied to model the electricity price variability seen in a realistic network. The model is able to capture the price and hence the profitability uncertainties for generator companies. Seasonal variation in the electricity prices and the system demand are independently modeled. The method is validated on IEEE RTS system, augmented with realistic market and plant data, by using it to compare the financial viability of several generator investments applying either conventional or directly connected generator (powerformer) technologies. The significance of the results is assessed using several financial risk measures.

Partitioned likelihood support and the evaluation of data set conflict

In simultaneous analyses of multiple data partitions, the trees relevant when measuring support for a clade are the optimal tree, and the best tree lacking the clade (i.e., the most reasonable alternative). The parsimony-based method of partitioned branch support (PBS) forces each data set to arbitrate between the two relevant trees. This value is the amount each data set contributes to clade support in the combined analysis, and can be very different to support apparent in separate analyses. The approach used in PBS can also be employed in likelihood: a simultaneous analysis of all data retrieves the maximum likelihood tree, and the best tree without the clade of interest is also found. Each data set is fitted to the two trees and the log-likelihood difference calculated, giving partitioned likelihood support (PLS) for each data set. These calculations can be performed regardless of the complexity of the ML model adopted. The significance of PLS can be evaluated using a variety of resampling methods, such as the Kishino-Hasegawa test, the Shimodiara-Hasegawa test, or likelihood weights, although the appropriateness and assumptions of these tests remains debated.

Multivariate monitoring of a biological wastewater treatment process: a case study at Melbourne Water's Western Treatment Plant

Biological wastewater treatment is a complex, multivariate process, in which a number of physical and biological processes occur simultaneously. In this study, principal component analysis (PCA) and parallel factor analysis (PARAFAC) were used to profile and characterise Lagoon 115E, a multistage biological lagoon treatment system at Melbourne Water's Western Treatment Plant (WTP) in Melbourne, Australia. In this study, the objective was to increase our understanding of the multivariate processes taking place in the lagoon. The data used in the study span a 7-year period during which samples were collected as often as weekly from the ponds of Lagoon 115E and subjected to analysis. The resulting database, involving 19 chemical and physical variables, was studied using the multivariate data analysis methods PCA and PARAFAC. With these methods, alterations in the state of the wastewater due to intrinsic and extrinsic factors could be discerned. The methods were effective in illustrating and visually representing the complex purification stages and cyclic changes occurring along the lagoon system. The two methods proved complementary, with each having its own beneficial features. (C) 2003 Elsevier B.V. All rights reserved.

A continent of plant defense peptide diversity: Cyclotides in Australian Hybanthus (Violaceae)

Cyclotides are plant-derived miniproteins that have the unusual features of a head-to-tail cyclized peptide backbone and a knotted arrangement of disulfide bonds. It had been postulated that they might be an especially large family of host defense agents, but this had not yet been tested by field data on cyclotide variation in wild plant populations. In this study, we sampled Australian Hybanthus (Violaceae) to gain an insight into the level of variation within populations, within species, and between species. A wealth of cyclotide diversity was discovered: at least 246 new cyclotides are present in the 11 species sampled, and 26 novel sequences were characterized. A new approach to the discovery of cyclotide sequences was developed based on the identification of a conserved sequence within a signal sequence in cyclotide precursors. The number of cyclotides in the Violaceae is now estimated to be >9000. Cyclotide physicochemical profiles were shown to be a useful taxonomic feature that reflected species and their morphological relationships. The novel sequences provided substantial insight into the tolerance of the cystine knot framework in cyclotides to amino acid substitutions and will facilitate protein engineering applications of this framework.

Identifying and discriminating among lucerne cultivars using plant morphological characters

The use of morphological data obtained from field (plot test) and glasshouse trials to identify and discriminate among four Iranian and two New Zealand lucerne (Medicago sativa L.) cultivars was investigated, following guidelines established by the International Union for the Protection of New Varieties of Plants (UPOV) for cultivar registration and the Organisation for Economic Co-operation and Development (OECD) for seed certification. Data were collected for terminal leaflet length, width and ratio, angle of stem growth, date of first flowering, stem height at first flowering, flower colour, cutting recovery height, and disease scores. None of these characters were sufficient to identify or discriminate among the six cultivars. The results indicate a need to find cost-effective and efficient laboratory techniques to enhance the assessment of distinctness of lucerne cultivars (UPOV) and for determining cultivar purity for lucerne seed certification (OECD).

Functional-structural plant modelling using a combination of architectural analysis, L-systems and a canonical model of function

This paper presents a new method for producing a functional-structural plant model that simulates response to different growth conditions, yet does not require detailed knowledge of underlying physiology. The example used to present this method is the modelling of the mountain birch tree. This new functional-structural modelling approach is based on linking an L-system representation of the dynamic structure of the plant with a canonical mathematical model of plant function. Growth indicated by the canonical model is allocated to the structural model according to probabilistic growth rules, such as rules for the placement and length of new shoots, which were derived from an analysis of architectural data. The main advantage of the approach is that it is relatively simple compared to the prevalent process-based functional-structural plant models and does not require a detailed understanding of underlying physiological processes, yet it is able to capture important aspects of plant function and adaptability, unlike simple empirical models. This approach, combining canonical modelling, architectural analysis and L-systems, thus fills the important role of providing an intermediate level of abstraction between the two extremes of deeply mechanistic process-based modelling and purely empirical modelling. We also investigated the relative importance of various aspects of this integrated modelling approach by analysing the sensitivity of the standard birch model to a number of variations in its parameters, functions and algorithms. The results show that using light as the sole factor determining the structural location of new growth gives satisfactory results. Including the influence of additional regulating factors made little difference to global characteristics of the emergent architecture. Changing the form of the probability functions and using alternative methods for choosing the sites of new growth also had little effect. (c) 2004 Elsevier B.V. All rights reserved.

Analysis of plant microfossils in archaeological deposits from two remote archipelagos: The Marshall Islands, Eastern Micronesia, and the Pitcairn Group, Southeast Polynesia

Pollen and starch residue analyses were conducted on 24 sediment samples from archaeological sites on Maloelap and Ebon Atolls in the Marshall Islands, eastern Micronesia, and Henderson and Pitcairn Islands in the Pitcairn Group, Southeast Polynesia. The sampled islands, two of which are mystery islands (Henderson and Pitcairn), previously occupied and abandoned before European contact, comprise three types of Pacific islands: low coral atolls, raised atolls, and volcanic islands. Pollen, starch grains, calcium oxylate crystals, and xylem cells of introduced non-Colocasia Araceae (aroids) were identified in the Marshalls and Henderson (ca. 1,900 yr B.P. and 1,200 yr B.P. at the earliest, respectively). The data provide direct evidence of prehistoric horticulture in those islands and initial fossil pollen sequences from Pitcairn Island. Combined with previous studies, the data also indicate a horticultural system on Henderson comprising both field and tree crops, with seven different cultigens, including at least two species of the Araceae. Starch grains and xylem cells of Ipomoea sp., possibly introduced 1. batatas, were identified in Pitcairn Island deposits dated to the last few centuries before European contact in 1790.

Onset of sheath extension and duration of lamina extension are major determinants of the response of maize lamina length to plant density

Background and Aims Plants regulate their architecture strongly in response to density, and there is evidence that this involves changes in the duration of leaf extension. This questions the approximation, central in crop models, that development follows a fixed thermal time schedule. The aim of this research is to investigate, using maize as a model, how the kinetics of extension of grass leaves change with density, and to propose directions for inclusion of this regulation in plant models. • Methods Periodic dissection of plants allowed the establishment of the kinetics of lamina and sheath extension for two contrasting sowing densities. The temperature of the growing zone was measured with thermocouples. Two-phase (exponential plus linear) models were fitted to the data, allowing analysis of the timing of the phase changes of extension, and the extension rate of sheaths and blades during both phases. • Key Results The duration of lamina extension dictated the variation in lamina length between treatments. The lower phytomers were longer at high density, with delayed onset of sheath extension allowing more time for the lamina to extend. In the upper phytomers—which were shorter at high density—the laminae had a lower relative extension rate (RER) in the exponential phase and delayed onset of linear extension, and less time available for extension since early sheath extension was not delayed. • Conclusions The relative timing of the onset of fast extension of the lamina with that of sheath development is the main determinant of the response of lamina length to density. Evidence is presented that the contrasting behaviour of lower and upper phytomers is related to differing regulation of sheath ontogeny before and after panicle initiation. A conceptual model is proposed to explain how the observed asynchrony between lamina and sheath development is regulated.

Eliminating non-renewable CO2 emissions from sewage treatment: An anaerobic migrating bed reactor pilot plant study

The aim of this work was to demonstrate at pilot scale a high level of energy recovery from sewage utilising a primary Anaerobic Migrating Bed Reactor (AMBR) operating at ambient temperature to convert COD to methane. The focus is the reduction in non-renewable CO2 emissions resulting from reduced energy requirements for sewage treatment. A pilot AMBR was operated on screened sewage over the period June 2003 to September 2004. The study was divided into two experimental phases. In Phase 1 the process operated at a feed rate of 10 L/h (HRT 50 h), SRT 63 days, average temperature 28 degrees C and mixing time fraction 0.05. In Phase 2 the operating parameters were 20 L/h, 26 days, 16 degrees C and 0.025. Methane production was 66% of total sewage COD in Phase 1 and 23% in Phase 2. Gas mixing of the reactor provided micro-aeration which suppressed sulphide production. Intermittent gas mixing at a useful power input of 6 W/m(3) provided satisfactory process performance in both phases. Energy consumption for mixing was about 1.5% of the energy conversion to methane in both operating phases. Comparative analysis with previously published data confirmed that methane supersaturation resulted in significant losses of methane in the effluent of anaerobic treatment systems. No cases have been reported where methane was considered to be supersaturated in the effluent. We have shown that methane supersaturation is likely to be significant and that methane losses in the effluent are likely to have been greater than previously predicted. Dissolved methane concentrations were measured at up to 2.2 times the saturation concentration relative to the mixing gas composition. However, this study has also demonstrated that despite methane supersaturation occurring, microaeration can result in significantly lower losses of methane in the effluent (< 11% in this study), and has demonstrated that anaerobic sewage treatment can genuinely provide energy recovery. The goal of demonstrating a high level of energy recovery in an ambient anaerobic bioreactor was achieved. An AMBR operating at ambient temperature can achieve up to 70% conversion of sewage COD to methane, depending on SRT and temperature. (c) 2006 Wiley Periodicals, Inc.