Predicting Cell Cycle Regulated Genes by Causal Interactions

The fundamental difference between classic and modern biology is that technological innovations allow to generate high-throughput data to get insights into molecular interactions on a genomic scale. These high-throughput data can be used to infer gene networks, e. g., the transcriptional regulatory or signaling network, representing a blue print of the current dynamical state of the cellular system. However, gene networks do not provide direct answers to biological questions, instead, they need to be analyzed to reveal functional information of molecular working mechanisms. In this paper we propose a new approach to analyze the transcriptional regulatory network of yeast to predict cell cycle regulated genes. The novelty of our approach is that, in contrast to all other approaches aiming to predict cell cycle regulated genes, we do not use time series data but base our analysis on the prior information of causal interactions among genes. The major purpose of the present paper is to predict cell cycle regulated genes in S. cerevisiae. Our analysis is based on the transcriptional regulatory network, representing causal interactions between genes, and a list of known periodic genes. No further data are used. Our approach utilizes the causal membership of genes and the hierarchical organization of the transcriptional regulatory network leading to two groups of periodic genes with a well defined direction of information flow. We predict genes as periodic if they appear on unique shortest paths connecting two periodic genes from different hierarchy levels. Our results demonstrate that a classical problem as the prediction of cell cycle regulated genes can be seen in a new light if the concept of a causal membership of a gene is applied consequently. This also shows that there is a wealth of information buried in the transcriptional regulatory network whose unraveling may require more elaborate concepts than it might seem at first.

Place and Special Places: Innovations in Conservation Practice in Northern Ireland

The sense of place that relates human beings to their environment is under threat from the rising tide of placelessness which can result from potentially positive forces such as urban regeneration as well as negative ones such as incremental degradation. The concept of sense of place, and the need to protect and enhance special places, has underpinned UK conservation legislation and policy in the post-war era. In Northern Ireland, due to its distinctive settlement tradition, its troubled political circumstances and its centralised administrative system, a unique hierarchy of special places has evolved, involving areas of townscape and village character as well as conventional conservation areas. For the first time a comprehensive comparative survey of the townscape quality of most of these areas has been carried out in order to test the hypothesis that too many conservation area designations may devalue the conservation coinage. It also assesses the contribution that areas of townscape character can make in this situation, as potential conservation areas or as second-level local amenity designations. Its findings support the initial hypothesis: assessment of townscape quality on the basis of consistent criteria demonstrates a decline in the quality of more recent conservation area designations, and hence some devaluation of the coinage. However, the need for local discretion in the protection of local amenity supports the concept of areas of townscape and village character as an additional and distinct designation. This contradicts recent policy recommendations from the Northern Ireland Planning Commission and contains valuable lessons for conservation policy and practice in other parts of the UK.

E-Commerce Innovations in the Personal Tax System of the United Kingdom

This study finds evidence that attempts to reduce costs and error rates in the Inland Revenue through the use of e-commerce technology are flawed. While it is technically possible to write software that will record tax data, and then transmit it to the Inland Revenue, there is little demand for this service. The key finding is that the tax system is so complex that many people are unable to complete their own tax returns. This complexity cannot be overcome by well-designed software. The recommendation is to encourage the use of agents to assist taxpayers or simplify the tax system. The Inland Revenue is interested in saving administrative costs and errors by encouraging electronic submission of tax returns. To achieve these objectives, given the raw data it would seem clear that the focus should be on facilitating the work of agents.

Ethnography of technological competence in clinical midwifery practice

Background. Concept analysis has identified three domains in the competent use of birth technology â?? interpersonal skills, professional knowledge and clinical proficiency â?? and tentative criteria for birth technology competence. Aim. Fieldwork was undertaken to observe, confirm and explore pre-defined attributes of birth technology competence. Method. The Swartz-Barcott and Kim (2000) hybrid model of concept development was expanded to include an ethnographic observation of theory in action. Findings. Key attributes of birth technology competence found in â??real-worldâ?? midwifery practice were skills in using the machines, decision-making and traditional midwifery skills. Conclusions. The confusion surrounding the use of technology in midwifery practice needs to be addressed by both professionals and educationalists. Midwives should be taught to value traditional midwifery skills alongside those of machine skills. The identification of a model of appropriate technology use is needed in midwifery.

Technological regimes, Schumpeterian patterns of innovation and firm-level productivity growth

The article investigates the relationships between technological regimes and firm-level productivity performance, and it explores how such a relationship differs in different Schumpeterian patterns of innovation. The analysis makes use of a rich dataset containing data on innovation and other economic characteristics of a large representative sample of Norwegian firms in manufacturing and service industries for the period 1998–2004. First, we decompose TFP growth into technical progress and efficiency changes by means of data envelopment analysis. We then estimate an empirical model that relates these two productivity components to the characteristics of technological regimes and a set of other firm-specific factors. The results indicate that: (i) TFP growth has mainly been achieved through technical progress, while technical efficiency has on average decreased; (ii) the characteristics of technological regimes are important determinants of firm-level productivity growth, but their impacts on technical progress are different from the effects on efficiency change; (iii) the estimated model works differently in the two Schumpeterian regimes. Technical progress has been more dynamic in Schumpeter Mark II industries, while efficiency change has been more important in Schumpeter Mark I markets.

Clinical Utility of Microarray-Based Gene Expression Profiling in the Diagnosis and Subclassification of Leukemia: Report From the International Microarray Innovations in Leukemia Study Group

The Microarray Innovations in Leukemia study assessed the clinical utility of gene expression profiling as a single test to subtype leukemias into conventional categories of myeloid and lymphoid malignancies. METHODS: The investigation was performed in 11 laboratories across three continents and included 3,334 patients. An exploratory retrospective stage I study was designed for biomarker discovery and generated whole-genome expression profiles from 2,143 patients with leukemias and myelodysplastic syndromes. The gene expression profiling-based diagnostic accuracy was further validated in a prospective second study stage of an independent cohort of 1,191 patients. RESULTS: On the basis of 2,096 samples, the stage I study achieved 92.2% classification accuracy for all 18 distinct classes investigated (median specificity of 99.7%). In a second cohort of 1,152 prospectively collected patients, a classification scheme reached 95.6% median sensitivity and 99.8% median specificity for 14 standard subtypes of acute leukemia (eight acute lymphoblastic leukemia and six acute myeloid leukemia classes, n = 693). In 29 (57%) of 51 discrepant cases, the microarray results had outperformed routine diagnostic methods. CONCLUSION: Gene expression profiling is a robust technology for the diagnosis of hematologic malignancies with high accuracy. It may complement current diagnostic algorithms and could offer a reliable platform for patients who lack access to today's state-of-the-art diagnostic work-up. Our comprehensive gene expression data set will be submitted to the public domain to foster research focusing on the molecular understanding of leukemias

An international standardization programme towards the application of gene expression profiling in routine leukaemia diagnostics: the Microarray Innovations in LEukemia study prephase

Gene expression profiling has the potential to enhance current methods for the diagnosis of haematological malignancies. Here, we present data on 204 analyses from an international standardization programme that was conducted in 11 laboratories as a prephase to the Microarray Innovations in LEukemia (MILE) study. Each laboratory prepared two cell line samples, together with three replicate leukaemia patient lysates in two distinct stages: (i) a 5-d course of protocol training, and (ii) independent proficiency testing. Unsupervised, supervised, and r(2) correlation analyses demonstrated that microarray analysis can be performed with remarkably high intra-laboratory reproducibility and with comparable quality and reliability.