Abstract: Gene expression profiling is rapidly evolving into a
powerful technique for investigating tumor malignancies. The
researchers are overwhelmed with the microarray-based platforms
and methods that confer them the freedom to conduct large-scale
gene expression profiling measurements. Simultaneously,
investigations into cross-platform integration methods have started
gaining momentum due to their underlying potential to help
comprehend a myriad of broad biological issues in tumor diagnosis,
prognosis, and therapy. However, comparing results from different
platforms remains to be a challenging task as various inherent
technical differences exist between the microarray platforms. In this
paper, we explain a simple ratio-transformation method, which can
provide some common ground for cDNA and Affymetrix platform
towards cross-platform integration. The method is based on the
characteristic data attributes of Affymetrix- and cDNA- platform. In
the work, we considered seven childhood leukemia patients and their
gene expression levels in either platform. With a dataset of 822
differentially expressed genes from both these platforms, we carried
out a specific ratio-treatment to Affymetrix data, which subsequently
showed an improvement in the relationship with the cDNA data.
Abstract: This paper provides an overview of auction theory
literature. We present a general review on literature of various
auctions and focus ourselves specifically on an English auction. We
are interested in modelling bidder-s behavior in an English auction
environment. And hence, we present an overview of the New Zealand
wool auction followed by a model that would describe a bidder-s
decision making behavior from the New Zealand wool auction. The
mathematical assumptions in an English auction environment are
demonstrated from the perspective of the New Zealand wool auction.
Abstract: This paper describes the optimization of a complex
dairy farm simulation model using two quite different methods of
optimization, the Genetic algorithm (GA) and the Lipschitz
Branch-and-Bound (LBB) algorithm. These techniques have been
used to improve an agricultural system model developed by Dexcel
Limited, New Zealand, which describes a detailed representation of
pastoral dairying scenarios and contains an 8-dimensional parameter
space. The model incorporates the sub-models of pasture growth and
animal metabolism, which are themselves complex in many cases.
Each evaluation of the objective function, a composite 'Farm
Performance Index (FPI)', requires simulation of at least a one-year
period of farm operation with a daily time-step, and is therefore
computationally expensive. The problem of visualization of the
objective function (response surface) in high-dimensional spaces is
also considered in the context of the farm optimization problem.
Adaptations of the sammon mapping and parallel coordinates
visualization are described which help visualize some important
properties of the model-s output topography. From this study, it is
found that GA requires fewer function evaluations in optimization
than the LBB algorithm.