Discovering classes in microarray data using island counts

We present a new biclustering algorithm to simultaneously discover tissue classes and identify a set of genes that well-characterize these classes from DNA microarray data sets. We employ a combinatorial optimization approach where the object is to simultaneously identify an interesting set of genes and a partition of the array samples that optimizes a certain score based on a novel color island statistic. While this optimization problem is NP-complete in general, we are effectively able to solve problems of interest to optimality using a branch-and-bound algorithm. We have tested the algorithm on a 30 sample Cutaneous T-cell Lymphoma data set; it was able to almost perfectly discriminate short-term survivors from long-term survivors and normal controls. Another useful feature of our method is that can easily handle missing expression data.     

Letters to the editor

Relatively little attention has been paid to the use and importance of labels used by men who have sex with men to describe insertive or receptive sexual behavior during intercourse. This study examines sexual self‐labels, sexual behavior, HIV transmission risk, and psychological functioning among 205 HIV‐seropositive men who have sex with men. The majority of participants (88%) identified as a “top, “ a “bottom, “ or “versatile. “ Tops were more likely to engage in insertive anal intercourse than bottoms, and bottoms were more likely to engage in receptive anal intercourse than tops, with versatiles reporting intermediate rates of both behaviors. Although the results suggest preliminary evidence regarding the predictive utility of self‐labels, sexual behaviors of self‐label groups were greatly overlapping. Differences were found among self‐label groups in gay self‐identification, internalized homophobia, sexual sensation seeking, and anxiety. Results suggest an added value in assessing self‐labels in addition to asking about sexual behavior.     

Applying the ‘comply-or-explain’ principle: discursive legitimacy tactics with regard to codes of corporate governance

The comply-or-explain principle is a central element of most codes of corporate governance. Originally put forward by the Cadbury Committee in the UK as a practical means of establishing a code of corporate governance whilst avoiding an inflexible “one size fits all” approach, it has since been incorporated into code regimes around the world. Companies can either comply with code provisions or may explain why they do not comply, i.e., why they deviate from a code provision. Despite its wide application very little is known about the ways in which comply-or-explain is used. In addressing this we employ legitimacy theory by which explanations for deviating can be understood as means of legitimizing the company’s actions. We analyzed the compliance statements and reports of 257 listed companies in the UK and Germany, producing some 715 records of deviation. From this we generated an empirically derived taxonomy of the explanations. In a second order analysis we examine the underlying logic and identify various legitimacy tactics. We discuss the consequences of these legitimacy tactics for code regimes and the implications for policy makers.     

A Generic Semantic Grammar for Quantitative Text Analysis: Applications to East and West Berlin Radio News Content from 1979

In a semantic text analysis the researcher begins by creating one of two types of semantic grammars, each of which provides one or more templates that specify the ways concepts (or more general themes) may be related. On the one hand, a phenomenal semantic grammar can be created to extract phenomenon-related information from a text population (e.g., "Among the population's grievances [the phenomenon of interest in this case], which were ones for the abolition of taxes?"). On the other hand, a generic semantic grammar may be developed to yield data about the text population itself (e.g., "Among all clauses in the text population, how many were grievances for the abolition of taxes?"). This paper describes a generic semantic grammar that can be used to encode themes and theme relations in every clause within randomly sampled texts. Unlike the surface-grammatical relations mapped by syntax grammars, the theme relations allowed in this grammar only permit unambiguous encoding according to the meanings that clauses were intended to convey within their social context. An application of the grammar provides a concrete illustration of its research potential.     

Bayesian Nonparametric Hidden Markov Models with application to the analysis of copy-number-variation in mammalian genomes

We consider the development of Bayesian Nonparametric methods for product partition models such as Hidden Markov Models and change point models. Our approach uses a Mixture of Dirichlet Process (MDP) model for the unknown sampling distribution (likelihood) for the observations arising in each state and a computationally efficient data augmentation scheme to aid inference. The method uses novel MCMC methodology which combines recent retrospective sampling methods with the use of slice sampler variables. The methodology is computationally efficient, both in terms of MCMC mixing properties, and robustness to the length of the time series being investigated. Moreover, the method is easy to implement requiring little or no user-interaction. We apply our methodology to the analysis of genomic copy number variation.     

Financial assistance for families with severely disabled children and transport costs

Families with severely disabled children encounter many difficulties in getting out and about. The inadequacy of statutory financial assistance for transport related costs is confirmed by an analysis of families receiving grants from the Family Fund Trust. A third of the sample of 37 000 families with a severely disabled child, received grants for transport related costs. Such grants were more common for families with very young disabled children, children with particular diagnoses, or severely impaired motor function, sight and speech, and families whose children were dependent on technology, or who subsequently died. Recommendations for improving current statutory support are made. Copyright © 1999 John Wiley & Sons, Ltd.     

The duration of unemployment in Russia

This paper uses longitudinal survey data to assess factors affecting the duration of unemployment in Russia. We examine four types of marginalised labour force participants, according to ILO guidelines and survey responses, and we estimate duration models for each type. It turns out that the sets of characteristics with the strongest effects on the duration are remarkably similar across the different unemployment definitions and model specifications. Therefore, despite the formidable practical measurement problems, problematic groups of individuals can actually be identified. Received: 27 January 1999/Accepted: 27 January 2000     

Thirty‐five Years Later in Development Assistance: Have We Moved On,or Just Performed a Minuet?

Development economists have presented the problems of development in varying and incompatible terms, and have influentially advocated contradictory policies. After twists and turns a broad consensus has emerged on pro‐poor growth objectives and on the policy and institutional means of achieving them. But a number of important questions remain unresolved or indeterminate. Development experts, economists and others, should have the humility to recognise the country specificity of much development experience and the multiplicity of valid paths to the goal of material wellbeing. They are least likely to mislead if their advice acknowledges the likely joint importance of macroeconomic stability, reasonably efficient markets, and supportive institutions.