A comparison of forensic toolkits and mass market data recovery applications

Digital forensic application suites are large, expensive, complex software products, offering a range of functions to assist in the investigation of digital artifacts. Several authors have raised concerns as to the reliability of evidence derived from these products. This is of particular concern, given that many forensic suites are closed source and therefore can only be subject to black box evaluation. In addition, many of the individual functions integrated into forensic suites are available as commercial stand-alone products, typically at a much lower cost, or even free. This paper reports research which compared (rather than individually evaluated) the data recovery function of two forensic suites and three stand alone `non-forensic' commercial applications. The research demonstrates that, for this function at least, the commercial data recovery tools provide comparable performance to that of the forensic software suites. In addition, the research demonstrates that there is some variation in results presented by all of the data recovery tools

A developmental evaluation approach to lesson study: exploring the impact of lesson study in London schools

This article presents a methodology for the developmental evaluation of a lesson study programme in primary and secondary schools. Our approach combined the principles of (i) user-focused evaluation, in which, as evaluators, we acted as participatory members of the innovation team and sought to involve users in the design and implementation of evaluation tools, (ii) a multi-level logical model to guide data collection and impact measurement and (iii) an ‘improving rather than proving’ approach to evaluation. The evaluation tools were used on a programme to promote lesson study in London schools involving 133 teachers and 33 schools. The evaluation methodology included outcomes at school leadership, teacher and student levels. Issues of internal and external validity are discussed and strengths and weaknesses are described. Findings showed promise in the use of our scale to measure changes in teacher pedagogical outcomes and in the recording of qualitative changes to both teachers and students as a result of the lesson study cycles. Suggestions for the future use and development of this methodology are proposed, including better use of control groups and quantitative measures to record changes in learning outcomes for students. List of Abbreviations: HE: Higher Education; LS: Lesson Study; PD: Professional Developmen

Conserved noncoding sequences highlight shared components of regulatory networks in dicotyledonous plants

Conserved noncoding sequences (CNSs) in DNA are reliable pointers to regulatory elements controlling gene expression. Using a comparative genomics approach with four dicotyledonous plant species (Arabidopsis thaliana, papaya [Carica papaya], poplar [Populus trichocarpa], and grape [Vitis vinifera]), we detected hundreds of CNSs upstream of Arabidopsis genes. Distinct positioning, length, and enrichment for transcription factor binding sites suggest these CNSs play a functional role in transcriptional regulation. The enrichment of transcription factors within the set of genes associated with CNS is consistent with the hypothesis that together they form part of a conserved transcriptional network whose function is to regulate other transcription factors and control development. We identified a set of promoters where regulatory mechanisms are likely to be shared between the model organism Arabidopsis and other dicots, providing areas of focus for further research

Nonparametric Bayesian inference for perturbed and orthologous gene regulatory networks

Motivation: The generation of time series transcriptomic datasets collected under multiple experimental conditions has proven to be a powerful approach for disentangling complex biological processes, allowing for the reverse engineering of gene regulatory networks (GRNs). Most methods for reverse engineering GRNs from multiple datasets assume that each of the time series were generated from networks with identical topology. In this study, we outline a hierarchical, non-parametric Bayesian approach for reverse engineering GRNs using multiple time series that can be applied in a number of novel situations including: (i) where different, but overlapping sets of transcription factors are expected to bind in the different experimental conditions; that is, where switching events could potentially arise under the different treatments and (ii) for inference in evolutionary related species in which orthologous GRNs exist. More generally, the method can be used to identify context-specific regulation by leveraging time series gene expression data alongside methods that can identify putative lists of transcription factors or transcription factor targets. Results: The hierarchical inference outperforms related (but non-hierarchical) approaches when the networks used to generate the data were identical, and performs comparably even when the networks used to generate data were independent. The method was subsequently used alongside yeast one hybrid and microarray time series data to infer potential transcriptional switches in Arabidopsis thaliana response to stress. The results confirm previous biological studies and allow for additional insights into gene regulation under various abiotic stresses. Availability: The methods outlined in this article have been implemented in Matlab and are available on request

High-resolution temporal profiling of transcripts during Arabidopsis leaf senescence reveals a distinct chronology of processes and regulation

Leaf senescence is an essential developmental process that impacts dramatically on crop yields and involves altered regulation of thousands of genes and many metabolic and signaling pathways, resulting in major changes in the leaf. The regulation of senescence is complex, and although senescence regulatory genes have been characterized, there is little information on how these function in the global control of the process. We used microarray analysis to obtain a highresolution time-course profile of gene expression during development of a single leaf over a 3-week period to senescence. A complex experimental design approach and a combination of methods were used to extract high-quality replicated data and to identify differentially expressed genes. The multiple time points enable the use of highly informative clustering to reveal distinct time points at which signaling and metabolic pathways change. Analysis of motif enrichment, as well as comparison of transcription factor (TF) families showing altered expression over the time course, identify clear groups of TFs active at different stages of leaf development and senescence. These data enable connection of metabolic processes, signaling pathways, and specific TF activity, which will underpin the development of network models to elucidate the process of senescence

Listen to genes : dealing with microarray data in the frequency domain

Background: We present a novel and systematic approach to analyze temporal microarray data. The approach includes normalization, clustering and network analysis of genes. Methodology: Genes are normalized using an error model based uniform normalization method aimed at identifying and estimating the sources of variations. The model minimizes the correlation among error terms across replicates. The normalized gene expressions are then clustered in terms of their power spectrum density. The method of complex Granger causality is introduced to reveal interactions between sets of genes. Complex Granger causality along with partial Granger causality is applied in both time and frequency domains to selected as well as all the genes to reveal the interesting networks of interactions. The approach is successfully applied to Arabidopsis leaf microarray data generated from 31,000 genes observed over 22 time points over 22 days. Three circuits: a circadian gene circuit, an ethylene circuit and a new global circuit showing a hierarchical structure to determine the initiators of leaf senescence are analyzed in detail. Conclusions: We use a totally data-driven approach to form biological hypothesis. Clustering using the power-spectrum analysis helps us identify genes of potential interest. Their dynamics can be captured accurately in the time and frequency domain using the methods of complex and partial Granger causality. With the rise in availability of temporal microarray data, such methods can be useful tools in uncovering the hidden biological interactions. We show our method in a step by step manner with help of toy models as well as a real biological dataset. We also analyse three distinct gene circuits of potential interest to Arabidopsis researchers

On African Eupsilobiinae (Coleoptera: Endomychidae) with Descriptions of a New Genus and Species

Species of the South African genus Microxenus Wollaston are revised. Microxenus laticollis Wollaston is redescribed, and M. muelleri sp. nov. and M. krugeri sp. nov. are described. Natalinus gen. nov. and its single included species, N. klimaszewskii sp. nov. are described. All of these taxa are diagnosed and illustrated, and a key to the species of Microxenus is presented. Female genitalia of newly described species are discussed in terms of monophyly of Eupsilobiinae. Zoogeographical and biological data of African Eupsilobiinae are summarized

Perturbation of cytokinin and ethylene-signalling pathways explain the strong rooting phenotype exhibited by Arabidopsis expressing the Schizosaccharomyces pombe mitotic inducer, cdc25

Background Entry into mitosis is regulated by cyclin dependent kinases that in turn are phosphoregulated. In most eukaryotes, phosphoregulation is through WEE1 kinase and CDC25 phosphatase. In higher plants a homologous CDC25 gene is unconfirmed and hence the mitotic inducer Schizosaccharomyces pombe (Sp) cdc25 has been used as a tool in transgenic plants to probe cell cycle function. Expression of Spcdc25 in tobacco BY-2 cells accelerates entry into mitosis and depletes cytokinins; in whole plants it stimulates lateral root production. Here we show, for the first time, that alterations to cytokinin and ethylene signaling explain the rooting phenotype elicited by Spcdc25 expression in Arabidopsis. Results Expressing Spcdc25 in Arabidopsis results in increased formation of lateral and adventitious roots, a reduction of primary root width and more isodiametric cells in the root apical meristem (RAM) compared with wild type. Furthermore it stimulates root morphogenesis from hypocotyls when cultured on two way grids of increasing auxin and cytokinin concentrations. Microarray analysis of seedling roots expressing Spcdc25 reveals that expression of 167 genes is changed by > 2-fold. As well as genes related to stress responses and defence, these include 19 genes related to transcriptional regulation and signaling. Amongst these was the up-regulation of genes associated with ethylene synthesis and signaling. Seedlings expressing Spcdc25 produced 2-fold more ethylene than WT and exhibited a significant reduction in hypocotyl length both in darkness or when exposed to 10 ppm ethylene. Furthermore in Spcdc25 expressing plants, the cytokinin receptor AHK3 was down-regulated, and endogenous levels of iPA were reduced whereas endogeous IAA concentrations in the roots increased. Conclusions We suggest that the reduction in root width and change to a more isodiametric cell phenotype in the RAM in Spcdc25 expressing plants is a response to ethylene over-production. The increased rooting phenotype in Spcdc25 expressing plants is due to an increase in the ratio of endogenous auxin to cytokinin that is known to stimulate an increased rate of lateral root production. Overall, our data reveal important cross talk between cell division and plant growth regulators leading to developmental changes