miRPlant : an integrated tool for identification of plant miRNA from RNA sequencing data

Background Small RNA sequencing is commonly used to identify novel miRNAs and to determine their expression levels in plants. There are several miRNA identification tools for animals such as miRDeep, miRDeep2 and miRDeep*. miRDeep-P was developed to identify plant miRNA using miRDeep’s probabilistic model of miRNA biogenesis, but it depends on several third party tools and lacks a user-friendly interface. The objective of our miRPlant program is to predict novel plant miRNA, while providing a user-friendly interface with improved accuracy of prediction. Result We have developed a user-friendly plant miRNA prediction tool called miRPlant. We show using 16 plant miRNA datasets from four different plant species that miRPlant has at least a 10% improvement in accuracy compared to miRDeep-P, which is the most popular plant miRNA prediction tool. Furthermore, miRPlant uses a Graphical User Interface for data input and output, and identified miRNA are shown with all RNAseq reads in a hairpin diagram. Conclusions We have developed miRPlant which extends miRDeep* to various plant species by adopting suitable strategies to identify hairpin excision regions and hairpin structure filtering for plants. miRPlant does not require any third party tools such as mapping or RNA secondary structure prediction tools. miRPlant is also the first plant miRNA prediction tool that dynamically plots miRNA hairpin structure with small reads for identified novel miRNAs. This feature will enable biologists to visualize novel pre-miRNA structure and the location of small RNA reads relative to the hairpin. Moreover, miRPlant can be easily used by biologists with limited bioinformatics skills.

Combining opinions for use in Bayesian networks: A measurement error approach

Bayesian networks (BNs) are graphical probabilistic models used for reasoning under uncertainty. These models are becoming increasing popular in a range of fields including ecology, computational biology, medical diagnosis, and forensics. In most of these cases, the BNs are quantified using information from experts, or from user opinions. An interest therefore lies in the way in which multiple opinions can be represented and used in a BN. This paper proposes the use of a measurement error model to combine opinions for use in the quantification of a BN. The multiple opinions are treated as a realisation of measurement error and the model uses the posterior probabilities ascribed to each node in the BN which are computed from the prior information given by each expert. The proposed model addresses the issues associated with current methods of combining opinions such as the absence of a coherent probability model, the lack of the conditional independence structure of the BN being maintained, and the provision of only a point estimate for the consensus. The proposed model is applied an existing Bayesian Network and performed well when compared to existing methods of combining opinions.

Use of genetic decompositions to scaffold the development of a structurally sequenced curriculum for mathematics acceleration

The authors have collaboratively used a graphical language to describe their shared knowledge of a small domain of mathematics, which has in turn scaffolded their re-development of a related curriculum for mathematics acceleration. This collaborative use of the graphical language is reported as a simple descriptive case study. This leads to an evaluation of the graphical language’s usefulness as a tool to support the articulation of the structure of mathematics knowledge. In turn, implications are drawn for how the graphical language may be utilised as the detail of the curriculum is further elaborated and communicated to teachers.

Refractive indices with Haag-Streit Lenstar biometer

Purpose: To estimate refractive indices used with the Lenstar biometer. Methods: Axial lengths of model eyes were determined using an IOLMaster biometer and a Lenstar; comparing these lengths gave an overall eye index for the Lenstar. Using the Lenstar Graphical User interface, we determined that boundaries between media could be manipulated so that there were opposite changes in optical pathlength on either side of the boundary and specified changes in distances determined the ratios of media indices. These ratios were combined with the overall eye index to estimate indices. Results: The IOLMaster and Lenstar produced axial length estimates to within ±0.01 mm. Estimations of group refractive indices were 1.340, 1.341, 1.415 and 1.354 for cornea, aqueous, lens and overall eye, respectively. The aqueous and lens indices, but not those for the cornea, are similar to schematic eye indices and reasonable lens indices. Conclusion: The Lenstar appears to use different refractive indices for different ocular media.

Cultural and linguistic localization of games to bridge the digital and cultural divide in indigenous populations

Localization of technology is now widely applied to the preservation and revival of the culture of indigenous peoples around the world, most commonly through the translation into indigenous languages, which has been proven to increase the adoption of technology. However, this current form of localization excludes two demographic groups, which are key to the effectiveness of localization efforts in the African context: the younger generation (under the age of thirty) with an Anglo- American cultural view who have no need or interest in their indigenous culture; and the older generation (over the age of fifty) who are very knowledgeable about their indigenous culture, but have little or no knowledge on the use of a computer. This paper presents the design of a computer game engine that can be used to provide an interface for both technology and indigenous culture learning for both generations. Four indigenous Ugandan games are analyzed and identified for their attractiveness to both generations, to both rural and urban populations, and for their propensity to develop IT skills in older generations.

J-Circos : an interactive Circos plotter

Circos plots are graphical outputs that display three dimensional chromosomal interactions and fusion transcripts. However, the Circos plot tool is not an interactive visualization tool, but rather a figure generator. For example, it does not enable data to be added dynamically, nor does it provide information for specific data points interactively. Recently, an R-based Circos tool (RCircos) has been developed to integrate Circos to R, but similarly, Rcircos can only be used to generate plots. Thus, we have developed a Circos plot tool (J-Circos) that is an interactive visualization tool that can plot Circos figures, as well as being able to dynamically add data to the figure, and providing information for specific data points using mouse hover display and zoom in/out functions. J-Circos uses the Java computer language to enable it to be used on most operating systems (Windows, MacOS, Linux). Users can input data into JCircos using flat data formats, as well as from the GUI. J-Circos will enable biologists to better study more complex chromosomal interactions and fusion transcripts that are otherwise difficult to visualize from next-generation sequencing data.

A theory of process modeling impact

Process modeling – the design and use of graphical documentations of an organization’s business processes – is a key method to document and use information about the operations of businesses. Still, despite current interest in process modeling, this research area faces essential challenges. Key unanswered questions concern the impact of process modeling in organizational practice, and the mechanisms through which impacts are developed. To answer these questions and to provide a better understanding of process modeling impact, I turn to the concept of affordances. Affordances describe the possibilities for goal-oriented action that a technical object offers to a user. This notion has received growing attention from IS researchers. The purpose of my research is to further develop the IS discipline’s understanding of affordances and impacts from information objects, such as process models used by analysts for information systems analysis and design. Specifically, I seek to extend existing theory on the emergence, perception and actualization of affordances. I develop a research model that describes the process by which affordances emerge between an individual and an object, how affordances are perceived, and how they are actualized by the individual. The proposed model also explains the role of available information for the individual, and the influence of perceived actualization effort. I operationalize and test this research model empirically, using a full-cycle, mixed methods study consisting of case study and experiment.

Directional persistence and the optimality of run-and-tumble chemotaxis

E. coli does chemotaxis by performing a biased random walk composed of alternating periods of swimming (runs) and reorientations (tumbles). Tumbles are typically modelled as complete directional randomisations but it is known that in wild type E. coli, successive run directions are actually weakly correlated, with a mean directional difference of ∼63°. We recently presented a model of the evolution of chemotactic swimming strategies in bacteria which is able to quantitatively reproduce the emergence of this correlation. The agreement between model and experiments suggests that directional persistence may serve some function, a hypothesis supported by the results of an earlier model. Here we investigate the effect of persistence on chemotactic efficiency, using a spatial Monte Carlo model of bacterial swimming in a gradient, combined with simulations of natural selection based on chemotactic efficiency. A direct search of the parameter space reveals two attractant gradient regimes, (a) a low-gradient regime, in which efficiency is unaffected by directional persistence and (b) a high-gradient regime, in which persistence can improve chemotactic efficiency. The value of the persistence parameter that maximises this effect corresponds very closely with the value observed experimentally. This result is matched by independent simulations of the evolution of directional memory in a population of model bacteria, which also predict the emergence of persistence in high-gradient conditions. The relationship between optimality and persistence in different environments may reflect a universal property of random-walk foraging algorithms, which must strike a compromise between two competing aims: exploration and exploitation. We also present a new graphical way to generally illustrate the evolution of a particular trait in a population, in terms of variations in an evolvable parameter.

Exploring variation in measurement as a foundation for statistical thinking in the elementary school

This study was based on the premise that variation is the foundation of statistics and statistical investigations. The study followed the development of fourth-grade students' understanding of variation through participation in a sequence of two lessons based on measurement. In the first lesson all students measured the arm span of one student, revealing pathways students follow in developing understanding of variation and linear measurement (related to research question 1). In the second lesson each student's arm span was measured once, introducing a different aspect of variation for students to observe and contrast. From this second lesson, students' development of the ability to compare their representations for the two scenarios and explain differences in terms of variation was explored (research question 2). Students' documentation, in both workbook and software formats, enabled us to monitor their engagement and identify their increasing appreciation of the need to observe, represent, and contrast the variation in the data. Following the lessons, a written student assessment was used for judging retention of understanding of variation developed through the lessons and the degree of transfer of understanding to a different scenario (research question 3).

Edge-weighting of gene expression graphs

In recent years, considerable research efforts have been directed to micro-array technologies and their role in providing simultaneous information on expression profiles for thousands of genes. These data, when subjected to clustering and classification procedures, can assist in identifying patterns and providing insight on biological processes. To understand the properties of complex gene expression datasets, graphical representations can be used. Intuitively, the data can be represented in terms of a bipartite graph, with weighted edges corresponding to gene-sample node couples in the dataset. Biologically meaningful subgraphs can be sought, but performance can be influenced both by the search algorithm, and, by the graph-weighting scheme and both merit rigorous investigation. In this paper, we focus on edge-weighting schemes for bipartite graphical representation of gene expression. Two novel methods are presented: the first is based on empirical evidence; the second on a geometric distribution. The schemes are compared for several real datasets, assessing efficiency of performance based on four essential properties: robustness to noise and missing values, discrimination, parameter influence on scheme efficiency and reusability. Recommendations and limitations are briefly discussed. Keywords: Edge-weighting; weighted graphs; gene expression; bi-clustering

Positioning as a source of competitive advantage: Benchmarking Rotorua’s position as a domestic short break holiday destination

Travellers are spoilt by holiday choice, and yet will usually only seriously consider a few destinations during the decision process. With thousands of destination marketing organisations (DMOs) competing for attention, places are becoming increasingly substitutable. The study of destination competitiveness is an emerging field, and thesis contributes to an enhanced understanding by addressing three topics that have received relatively little attention in the tourism literature: destination positioning, the context of short break holidays, and domestic travel in New Zealand. A descriptive model of positioning as a source of competitive advantage is developed, and tested through 12 propositions. The destination of interest is Rotorua, which was arguably New Zealand’s first tourist destination. The market of interest is Auckland, which is Rotorua’s largest visitor market. Rotorua’s history is explored to identify factors that may have contributed to the destination’s current image in the Auckland market. A mix of qualitative and quantitative procedures is then utilised to determine Rotorua’s position, relative to a competing set of destinations. Based on an applied research problem, the thesis attempts to bridge the gap between academia and industry by providing useable results and benchmarks for five regional tourism organisations (RTOs). It is proposed that, in New Zealand, the domestic short break market represents a valuable opportunity not explicitly targeted by the competitive set of destinations. Conceptually, the thesis demonstrates the importance of analysing a destination’s competitive position, from the demand perspective, in a travel context; and then the value of comparing this ‘ideal’ position with that projected by the RTO. The thesis concludes Rotorua’s market position in the Auckland short break segment represents a source of comparative advantage, but is not congruent with the current promotional theme, which is being used in all markets. The findings also have implications for destinations beyond the context of the thesis. In particular, a new definition for ‘destination attractiveness’ is proposed, which warrants consideration in the design of future destination positioning analyses.

Relationships between major ions in coal seam gas groundwaters: Examples from the Surat and Clarence-Moreton basins

Using a combination of multivariate statistical techniques and the graphical assessment of major ion ratios, the influences on hydrochemical variability of coal seam gas (or coal bed methane) groundwaters from several sites in the Surat and Clarence-Moreton basins in Queensland, Australia, were investigated. Several characteristic relationships between major ions were observed: 1) strong positive linear correlation between the Na/Cl and alkalinity/Cl ratios; 2) an exponentially decaying trend between the Na/Cl and Na/alkalinity ratios; 3) inverse linear relationships between increasing chloride concentrations and decreasing pH for high salinity groundwaters, and; 4) high residual alkalinity for lower salinity waters, and an inverse relationship between decreasing residual alkalinity and increasing chloride concentrations for more saline waters. The interpretation of the hydrochemical data provides invaluable insights into the hydrochemical evolution of coal seam gas (CSG) groundwaters that considers both the source of major ions in coals and the influence of microbial activity. Elevated chloride and sodium concentrations in more saline groundwaters appear to be influenced by organic-bound chlorine held in the coal matrix; a sodium and chloride ion source that has largely been neglected in previous CSG groundwater studies. However, contrastingly high concentrations of bicarbonate in low salinity waters could not be explained, and are possibly associated with a number of different factors such as coal degradation, methanogenic processes, the evolution of high-bicarbonate NaHCO3 water types earlier on in the evolutionary pathway, and variability in gas reservoir characteristics. Using recently published data for CSG groundwaters in different basins, the characteristic major ion relationships identified for new data presented in this study were also observed in other CSG groundwaters from Australia, as well as for those in the Illinois Basin in the USA. This observation suggests that where coal maceral content and the dominant methanogenic pathway are similar, and where organic-bound chlorine is relatively abundant, distinct hydrochemical responses may be observed. Comparisons with published data of other NaHCO3 water types in non-CSG environments suggest that these characteristic major ion relationships described here can: i) serve as an indicator of potential CSG groundwaters in certain coal-bearing aquifers that contain methane; and ii) help in the development of strategic sampling programmes for CSG exploration and to monitor potential impacts of CSG activities on groundwater resources.

A multi-criteria analysis approach for ranking and selection of microorganisms for the production of oils for biodiesel production

Oleaginous microorganisms have potential to be used to produce oils as alternative feedstock for biodiesel production. Microalgae (Chlorella protothecoides and Chlorella zofingiensis), yeasts (Cryptococcus albidus and Rhodotorula mucilaginosa), and fungi (Aspergillus oryzae and Mucor plumbeus) were investigated for their ability to produce oil from glucose, xylose and glycerol. Multi-criteria analysis (MCA) using analytic hierarchy process (AHP) and preference ranking organization method for the enrichment of evaluations (PROMETHEE) with graphical analysis for interactive aid (GAIA), was used to rank and select the preferred microorganisms for oil production for biodiesel application. This was based on a number of criteria viz., oil concentration, content, production rate and yield, substrate consumption rate, fatty acids composition, biomass harvesting and nutrient costs. PROMETHEE selected A. oryzae, M. plumbeus and R. mucilaginosa as the most prospective species for oil production. However, further analysis by GAIA Webs identified A. oryzae and M. plumbeus as the best performing microorganisms.

Resampling-based approaches to study variation in morphological modularity

Modularity has been suggested to be connected to evolvability because a higher degree of independence among parts allows them to evolve as separate units. Recently, the Escoufier RV coefficient has been proposed as a measure of the degree of integration between modules in multivariate morphometric datasets. However, it has been shown, using randomly simulated datasets, that the value of the RV coefficient depends on sample size. Also, so far there is no statistical test for the difference in the RV coefficient between a priori defined groups of observations. Here, we (1), using a rarefaction analysis, show that the value of the RV coefficient depends on sample size also in real geometric morphometric datasets; (2) propose a permutation procedure to test for the difference in the RV coefficient between a priori defined groups of observations; (3) show, through simulations, that such a permutation procedure has an appropriate Type I error; (4) suggest that a rarefaction procedure could be used to obtain sample-size-corrected values of the RV coefficient; and (5) propose a nearest-neighbor procedure that could be used when studying the variation of modularity in geographic space. The approaches outlined here, readily extendable to non-morphometric datasets, allow study of the variation in the degree of integration between a priori defined modules. A Java application – that will allow performance of the proposed test using a software with graphical user interface – has also been developed and is available at the Morphometrics at Stony Brook Web page (http://life.bio.sunysb.edu/morph/).