Model-based clustering in gene expression microarrays: An application to breast cancer data

In microarray studies, the application of clustering techniques is often used to derive meaningful insights into the data. In the past, hierarchical methods have been the primary clustering tool employed to perform this task. The hierarchical algorithms have been mainly applied heuristically to these cluster analysis problems. Further, a major limitation of these methods is their inability to determine the number of clusters. Thus there is a need for a model-based approach to these. clustering problems. To this end, McLachlan et al. [7] developed a mixture model-based algorithm (EMMIX-GENE) for the clustering of tissue samples. To further investigate the EMMIX-GENE procedure as a model-based -approach, we present a case study involving the application of EMMIX-GENE to the breast cancer data as studied recently in van 't Veer et al. [10]. Our analysis considers the problem of clustering the tissue samples on the basis of the genes which is a non-standard problem because the number of genes greatly exceed the number of tissue samples. We demonstrate how EMMIX-GENE can be useful in reducing the initial set of genes down to a more computationally manageable size. The results from this analysis also emphasise the difficulty associated with the task of separating two tissue groups on the basis of a particular subset of genes. These results also shed light on why supervised methods have such a high misallocation error rate for the breast cancer data.

Oxide ionic conductivity and microstructures of Sm- or La-doped CeO2-based systems

The concept of crystallographic index termed the effective index is suggested and applied to the design of ceria (CeO2)-based electrolytes to maximize oxide ionic conductivity. The suggested index considers the fluorite structure, and combines the expected oxygen vacancy level with the ionic radius mismatch between host and dopant cations. Using this approach, oxide ionic conductivity of Sm- or La-doped CeO2-based system has been optimized and tested under operating conditions of a solid oxide fuel cell. In the observation of microstructure in atomic scale, both Sm-doped CeO2 and La-doped CeO2 electrolytes had large micro-domains over 10 nm in the lattice. On the other hand, Sm or La and alkaline earth co-doped CeO2-based electrolytes with high effective index had small micro-domains around 1-3 nm in the microstructure. The large micro-domain would prevent oxide ion from passing through the lattice. Therefore, it is concluded that the improvement of ionic conductivity is reflected in changes of microstructure in atomic scale. (C) 2002 Elsevier Science B.V. All rights reserved.

An energy-based model for swing hammer mills

An energy-based swing hammer mill model has been developed for coke oven feed preparation. it comprises a mechanistic power model to determine the dynamic internal recirculation and a perfect mixing mill model with a dual-classification function to mimic the operations of crusher and screen. The model parameters were calibrated using a pilot-scale swing hammer mill at various operating conditions. The effects of the underscreen configurations and the feed sizes on hammer mill operations were demonstrated through the fitted model parameters. Relationships between the model parameters and the machine configurations were established. The model was validated using the independent experimental data of single lithotype coal tests with the same BJD pilot-scale hammer mill and full operation audit data of an industrial hammer mill. The outcome of the energy-based swing hammer mill model is the capability to simulate the impact of changing blends of coal or mill configurations and operating conditions on product size distribution. Alternatively, the model can be used to select the machine settings required to achieve a desired product. (C) 2003 Elsevier Science B.V. All rights reserved.

The modeling of turbulent reactive flows based on multiple mapping conditioning

A new modeling approach-multiple mapping conditioning (MMC)-is introduced to treat mixing and reaction in turbulent flows. The model combines the advantages of the probability density function and the conditional moment closure methods and is based on a certain generalization of the mapping closure concept. An equivalent stochastic formulation of the MMC model is given. The validity of the closuring hypothesis of the model is demonstrated by a comparison with direct numerical simulation results for the three-stream mixing problem. (C) 2003 American Institute of Physics.

Ocular melanoma is not associated with CDKN2A or MC1R variants - a population-based study

Germline variants in the melanocortin 1 receptor gene (MC1R) and the p16 gene (CDKN2A) are associated with an increased risk of cutaneous melanoma. The frequency of these germline variants was examined in a population-based, incident series of 62 ocular melanoma cases and ethnicity-matched population controls. In both cases and controls, 59% of individuals carried at least one MC1R variant and there were no significant differences in the frequency of any of the five most common variants of MC1R. We also found no significant differences between cases and controls in the frequency of any of the four most common variants of CDKN2A, and no melanoma case carried a deleterious germline CDKN2A mutation. Our findings argue against an important predisposing effect of the MC1R and CDKN2A genes for ocular melanoma.

Chromosomal gains and losses in ocular melanoma detected by comparative genomic hybridization in an Australian population-based study

To define the location of potential oncogenes and tumor suppressor genes in ocular melanoma we carried out comparative genomic hybridization (CGH) analysis on a population-based series of 25 formalin-fixed, paraffin-embedded primary tumors comprising 17 choroidal, 2 ciliary body, 4 iris, and 2 conjunctival melanomas. Twelve (48%) of the 25 melanomas showed no chromosomal changes and 13 (52%) had at least one chromosomal gain or loss. The mean number of CGH changes in all tumors was 3.3, with similar mean numbers of chromosomal gains (1.5) and losses (1.8). The highest number of chromosomal changes (i.e., nine) occurred in a conjunctival melanoma and included four changes not observed in tumors at any other ocular site (gains in 22q and 11p and losses in 6p and 17p). The most frequent gains in all primary ocular melanomas were on chromosome arm 8q (69%), 6p (31%) and 8p (23%) and the most frequent losses were on 6q (38%), 10q (23%), and 16q (23%). The most common pairing was gain in 8p and gain in 8q, implying a whole chromosome copy number increase; gains in 8p occurred only in conjunction with gains in 8q. The smallest regions of copy number alteration were mapped to gain of 8q21 and loss of 6q21, 10q21, and 16q22. Sublocalization of these chromosomal changes to single-band resolution should accelerate the identification of genes involved in the genesis of ocular melanoma.

The tree cut and merge algorithm for estimation of network reliability

This article presents Monte Carlo techniques for estimating network reliability. For highly reliable networks, techniques based on graph evolution models provide very good performance. However, they are known to have significant simulation cost. An existing hybrid scheme (based on partitioning the time space) is available to speed up the simulations; however, there are difficulties with optimizing the important parameter associated with this scheme. To overcome these difficulties, a new hybrid scheme (based on partitioning the edge set) is proposed in this article. The proposed scheme shows orders of magnitude improvement of performance over the existing techniques in certain classes of network. It also provides reliability bounds with little overhead.