An effective non-parametric method for globally clustering genes from expression profiles

Clustering is widely used in bioinformatics to find gene correlation patterns. Although many algorithms have been proposed, these are usually confronted with difficulties in meeting the requirements of both automation and high quality. In this paper, we propose a novel algorithm for clustering genes from their expression profiles. The unique features of the proposed algorithm are twofold: it takes into consideration global, rather than local, gene correlation information in clustering processes; and it incorporates clustering quality measurement into the clustering processes to implement non-parametric, automatic and global optimal gene clustering. The evaluation on simulated and real gene data sets demonstrates the effectiveness of the algorithm.

Coastal marine habitat mapping using multi-beam acoustics, video data and a decision tree classifier on the temperate south-east Australian continental shelf

In this habitat mapping study, multi-beam acoustic data are integrated with extensive, precisely geo-referenced video validation data in a GIS environment to classify benthic substrates and biota at a 33km2 site in the near shore waters of Victoria, Australia. Using an automated decision-tree classification method, 5 representative biotic groups were identified in the Cape Nelson survey area using a combination of multi-beam bathymetry, backscatter and derivative products. Rigorous error assessment of derived, classified maps produced high overall accuracies (>85%) for all mapping products. In addition, a discrete multivariate analysis technique (kappa analysis) was used to assess classification accuracy. High-resolution (2.5m cell-size) representation of sea floor morphology and textural characteristics provided by multi-beam bathymetry and backscatter datasets, allowed the interpretation of benthic substrates of the Cape Nelson site and the communities of sessile organisms that populate them. Non-parametric multivariate statistical analysis (ANOSIM) revealed a significant difference in biotic composition between depth strata, and between substrate types. Incorporated with other descriptive measures, these results indicate that depth and substrate are important factors in the distributional ecology of the biotic communities at the Cape Nelson study site. BIOENV analysis indicates that derivatives of both multi-beam datasets (bathymetry and backscatter) are correlated with distribution and density of biotic communities. Results from this study provide new tools for research and management of the coastal zone.

An illustration of variable precision rough set theory : The gender classification of the European barn swallow (Hirundo rustica)

This paper introduces a new technique in the investigation of object classification and illustrates the potential use of this technique for the analysis of a range of biological data, using avian morphometric data as an example. The nascent variable precision rough sets (VPRS) model is introduced and compared with the decision tree method ID3 (through a ‘leave n out’ approach), using the same dataset of morphometric measures of European barn swallows (Hirundo rustica) and assessing the accuracy of gender classification based on these measures. The results demonstrate that the VPRS model, allied with the use of a modern method of discretization of data, is comparable with the more traditional non-parametric ID3 decision tree method. We show that, particularly in small samples, the VPRS model can improve classification and to a lesser extent prediction aspects over ID3. Furthermore, through the ‘leave n out’ approach, some indication can be produced of the relative importance of the different morphometric measures used in this problem. In this case we suggest that VPRS has advantages over ID3, as it intelligently uses more of the morphometric data available for the data classification, whilst placing less emphasis on variables with low reliability. In biological terms, the results suggest that the gender of swallows can be determined with reasonable accuracy from morphometric data and highlight the most important variables in this process. We suggest that both analysis techniques are potentially useful for the analysis of a range of different types of biological datasets, and that VPRS in particular has potential for application to a range of biological circumstances.

Large-scale statistical modeling of motion patterns : a Bayesian nonparametric approach

We propose a novel framework for large-scale scene understanding in static camera surveillance. Our techniques combine fast rank-1 constrained robust PCA to compute the foreground, with non-parametric Bayesian models for inference. Clusters are extracted in foreground patterns using a joint multinomial+Gaussian Dirichlet process model (DPM). Since the multinomial distribution is normalized, the Gaussian mixture distinguishes between similar spatial patterns but different activity levels (eg. car vs bike). We propose a modification of the decayed MCMC technique for incremental inference, providing the ability to discover theoretically unlimited patterns in unbounded video streams. A promising by-product of our framework is online, abnormal activity detection. A benchmark video and two surveillance videos, with the longest being 140 hours long are used in our experiments. The patterns discovered are as informative as existing scene understanding algorithms. However, unlike existing work, we achieve near real-time execution and encouraging performance in abnormal activity detection.

Clinical research 5: quantitative data collection and analysis

This six-part research series is aimed at clinicians who wish to develop research skills, or who have a particular clinical problem that they think could be addressed through research. The series aims to provide insight into the decisions that researchers make in the course of their work, and to also provide a foundation for decisions that nurses may make in applying the findings of a study to practice in their own Unit or Department. The series emphasises the practical issues encountered when undertaking research in critical care settings; readers are encouraged to source research methodology textbooks for more detailed guidance on specific aspects of the research process.

A couple of points:

1. It is artificial to describe research as qualitative or quantitative. Studies often include both dimensions. However, for the purposes of this paper/series, this distinction is drawn for clarity of writing.

2. It is common practice for quantitative studies to refer to study ‘subjects’ and qualitative studies to refer to study ‘participants’. For ease of reading, the latter term will be used throughout this series.

Productivity growth and efficiency change in Malaysian manufacturing: recent evidence from disaggregated data

This paper estimates productivity growth in Malaysian manufacturing over the period 1983-1999. Malmquist productivity Indices (MPIs) have been computed using non parametric Data Envelopment Analysis (DEA) type linear programming, which show productivity growth sourced from efficiency change and growth in technology. Unlike previous studies, this study identifies the sources of productivity growth in Malaysian manufacturing industries at the five digit breakdown of Malaysian Standard Industrial Classification (MSIC) thereby revealing more industry specific efficiency and technical growth patterns. Results indicated that a high majority of the industries operated with low levels of technical efficiency with little or no improvement over time. Growth estimates revealed that two third of the industries (76 out of total 114 categories) experienced average annual productivity improvement ranging from 0.1% to 7.8%. Average annual technical progress was recorded by 95 industry categories while technical efficiency improvement was achieved by 53 industries. Overall yearly average indicated relatively low productivity growth from the mid 1990’s onwards caused by either efficiency decline or technical regress. Summary results for industries showed that some of the high rates of productivity growth have been recorded in glass and glass products (7.3%), Petroleum and coal (7.2%), industrial chemicals (4.9%) contributed from both efficiency improvement and technical progress ranging from 0.8% to 5.4% and from 1.7% to 4.1%, respectively. These results are expected to have some implications for ongoing and future strategic policy reform in Malaysian manufacturing generating a more sustainable growth for specific industry categories.

The efficiency of Australian universities: a data envelopment analysis

With participation in higher education amongst young people rising, governments around the world have been faced with increasing pressure on their finances, giving rise to the need to operate universities with a higher degree of efficiency. In this paper, non-parametric techniques are used to estimate technical and scale efficiency of individual Australian universities. Various measures of output and inputs are used. The results show that regardless of the output–input mix, Australian universities as a whole recorded high levels of efficiency relative to each other.

Technical and scale efficiency of Islamic banking operations in Malaysia: an empirical investigation with a longitudinal perspective

Against the background of increasing competition from globalization and the trend towards consolidation, diversification and rationalization, the study of efficiency is most relevant in the Malaysian Islamic banking context, where all domestic commercial banks operate Islamic banking schemes. Using the non-parametric method of Data Envelopment Analysis (DEA), this study investigates the recent efficiency of the Malaysian Islamic Banking system. The attributions of technical efficiency (utilization of capacity) and scale efficiency (optimality of scale achieved) are identified. Further, Islamic Banking Schemes operating under the dual banking system of foreign and domestic commercial banks were benchmarked to the country's two full-fledged Islamic banks to provide insight of the relative efficiencies. Amidst an overall improvement in TE and SE, it was noted that foreign banks (FB) increased efficiency levels to achieve full efficiency over the six-year period, and domestic banks (DB) followed by smaller improvement while the fully-fledged Islamic banks (FFIE) experienced a general decline in efficiency which was solely attributed to scale inefficiency. The findings provide useful guidelines for policy implications and may also assist banks concerned with their strategic planning with regard to the future of Islamic banking.

Validation of comprehensive assessment of activities of daily living in stroke survivors

This study determined whether the Functional Independence Measure (FIM) and the Frenchay Activities Index (FAI) could be used together as a more comprehensive score to assess the activities of daily living (ADL) in stroke survivors. Subjects were recruited from stroke patients consecutively admitted to the inpatient neurology or rehabilitation department at a university hospital in southern Taiwan. We interviewed 209 first stroke survivors at least 1 year after stroke onset during their clinical visits, at home, or in long-term care institutions. Combinations of FIM and FAI as a comprehensive assessment of ADL were measured. All items of the FIM and the FAI were included in a non-parametric factor analysis to determine their underlying constructs. Two comprehensive functional independence scores were then computed as functions of the FIM and FAI scores. The distributional characteristics of the comprehensive scores were examined. Approximately 90% of the total variation was explained by three factors. One single factor comprised all the items from FIM, while the FAI items loaded on two other factors, suggesting that FIM supplements FAI without overlap in content. We further demonstrated that the presence of ceiling or floor effects when either the FIM or the FAI was used could be removed using combined scores of the two instruments. The FIM and the FAI assessed different domains with good construct validity. A comprehensive assessment of functional independence obtained by combining the FIM and the FAI scores is potentially more appropriate and useful for clinical and research applications in stroke patients.

The effects of clustered data on standard error estimates in covariance structure analysis : a field data application

Purpose – The purpose of this article is to present an empirical analysis of complex sample data with regard to the biasing effect of non-independence of observations on standard error parameter estimates. Using field data structured in the form of repeated measurements it is to be shown, in a two-factor confirmatory factor analysis model, how the bias in SE can be derived when the non-independence is ignored.

Design/methodology/approach – Three estimation procedures are compared: normal asymptotic theory (maximum likelihood); non-parametric standard error estimation (naïve bootstrap); and sandwich (robust covariance matrix) estimation (pseudo-maximum likelihood).

Findings – The study reveals that, when using either normal asymptotic theory or non-parametric standard error estimation, the SE bias produced by the non-independence of observations can be noteworthy.

Research limitations/implications – Considering the methodological constraints in employing field data, the three analyses examined must be interpreted independently and as a result taxonomic generalisations are limited. However, the study still provides “case study” evidence suggesting the existence of the relationship between non-independence of observations and standard error bias estimates.

Originality/value – Given the increasing popularity of structural equation models in the social sciences and in particular in the marketing discipline, the paper provides a theoretical and practical insight into how to treat repeated measures and clustered data in general, adding to previous methodological research. Some conclusions and suggestions for researchers who make use of partial least squares modelling are also drawn.

The reliability of performance of healthy adults on three visual perception tests

Problems with visual perceptual skills have been shown to have a negative impact on the daily living skills of individuals and are, therefore, commonly assessed by occupational therapists. The purpose of this study was to examine two types of reliability (internal consistency and test-retest reliability) of three newly revised or developed adult visual perception tests. The participants were 50 healthy adults, aged 18 to 55 years, from Melbourne, Victoria, Australia. The participants completed the Developmental Test of Visual Perception - Adolescent and Adult (DTVP-A), the Motor-Free Visual Perception Test - Third Edition (MVPT-3) and the Test of Visual Perceptual Skills (non-motor) - Third Edition (TVPS-3). Internal consistency was examined using Cronbach's alpha calculations and test-retest reliability was analysed using Spearman rho non-parametric correlation coefficients.

The results indicated that the DTVP-A, the MVPT-3 and the TVPS-3 had total scale internal consistency correlation scores of 0.60 or higher (0.60, 0.69 and 0.63 respectively). The majority of the subscales of each test had lower correlation coefficients than the overall scores (ranging from 0.22 to 0.49). For the DTVP-A, MVPT-3 and TVPS-3 total scale scores, the test-retest reliability correlation coefficients were statistically significant (rho = 0.46, p<0.05; rho = 0.62, p<0.01; and rho = 0.59, p<0.01, respectively). Overall, the three visual perceptual tests exhibited low to moderate levels of internal consistency and test-retest reliability.

Productivity growth and efficiency change in Malaysian manufacturing : recent evidence from disaggregated data

This paper estimates productivity growth in Malaysian manufacturing over the period 1983-1999. Malmquist productivity Indices (MPIs) have been computed using non parametric Data Envelopment Analysis (DEA) type linear programming, which show productivity growth sourced from efficiency change and growth in technology. Unlike previous studies, this study identifies the Malaysian manufacturing industries at the five digit breakdown of Malaysian Standard Industrial Classification (MSIC) thereby revealing more industry specific efficiency and technical growth patterns. Results indicate that two third of the industries (76 out of total 114 categories) experienced average annual
productivity improvement ranging from 0.1% to 7.8% over the sampled period. Average annual technical progress was recorded by 95 industry categories while technical efficiency improvement was achieved by 53 industries. Overall yearly average indicated relatively low productivity growth from the mid 1990’s onwards caused by either efficiency decline or technical regress. Summary results for industries reveal that some of the high rates of productivity growth have been recorded in glass and glass products (7.3%), Petroleum and coal (7.2%), industrial chemicals (4.9%) contributed from both efficiency improvement and technical progress ranging from 0.8% to 5.4% and from 1.7% to 4.1%, respectively. These results are expected to have some implications for ongoing and future strategic policy reform in Malaysian manufacturing generating a more sustainable growth for specific industry categories.