Physical Sciences and Mathematics Commons^™

Case Study On The Pattern Change In Arabidopsis Thaliana Intron Sequence, Ren Zhang, Rachel Caldwell, Yan-Xia Lin, Jinda Kongcharoen, Yiren Yang

Associate Professor Yan-Xia Lin

A large portion in eukaryotic genomes is introns but their function is not yet fully elucidated. The aims of this study are to employ the generalized Bernoulli modeling approach to estimate the change points based on GC distribution in intron sequences of Arabidopsis thaliana and to investigate whether there is any correlation between gene properties (the gene expression level and the protein function) and these intron pattern changes. The influence of the intron length and the number of GC on the intron sequence pattern changes is demonstrated. Among the random sampled intron sequences, 10.71% have been identified to have pattern …

The Analysis Of Pattern Change In Intron Sequences, Jinda Kongcharoen, Yan-Xia Lin, Rachel Caldwell, Yiren Yang, Ren Zhang

Associate Professor Yan-Xia Lin

The Generalized Bernoulli Modeling approach is used to analyze the pattern change in intron sequences of a model plant species Arabidopsis thaliana. The influence of the intron length and the number of GC on the intron sequence pattern changes is examined. Two other gene properties, the gene expression level and the protein function encoded are also assessed. Among the random sampled intron sequences,10.71% of them have been identified to have sequence pattern change. Our study shows that the number of GC and the intron length significantly influence the intron pattern change while the gene expression level and the protein function …

Loss Protection In Pairs Trading Through Minimum Profit Bounds: A Cointegration Approach, Chandra Gulati, Yan-Xia Lin, Michael Mccrae

Associate Professor Yan-Xia Lin

No abstract provided.

Improving Promoter Prediction For The Nnpp2.2 Algorithm: A Case Study Using Escherichia Coli Dna Sequences, Ren Zhang, Alexandra Burden, Yan-Xia Lin

Associate Professor Yan-Xia Lin

No abstract provided.

Assessment Of Length Distributions Between Non-Coding And Coding Sequences Amongst Two Model Organisms, Ren Zhang, Rachel Caldwell, Yan-Xia Lin

Associate Professor Yan-Xia Lin

No abstract provided.

Evaluating The Volatility Forecasting Performance Of Best Fitting Garch Models In Emerging Asian Stock Markets, Chaiwat Kosapattarapim, Yan-Xia Lin, Michael Mccrae

Associate Professor Yan-Xia Lin

While modeling the volatility of returns is essential for many areas of finance, it is well known that financial return series exhibit many non-normal characteristics that cannot be captured by the standard GARCH model with a normal error distribution. But which GARCH model and which error distribution to use is still open to question, especially where the model that best fits the in-sample data may not give the most effective out-of-sample volatility forecasting ability. Approach: In this study, six simulated studies in GARCH(p,q) with six different error distributions are carried out. In each case, we determine the best fitting GARCH …

Initial Values In Estimation Procedures For State Space Models (Ssms), Raed Alzghool, Yan-Xia Lin

Associate Professor Yan-Xia Lin

In this paper, we will focus on State Space Models(SSMs), especially the stochastic volatility model, and lookfor a standard approach for assigning initial values in theQuasi-Likelihood (QL) and Asymptotic Quasi-Likelhood (AQL)estimation procedures.

Estimating Shared Copy Number Aberrations For Array Cgh Data: The Linear-Median Method, Yan-Xia Lin, Veera Baladandayuthapani, V Bonato, K.-A. Do

Associate Professor Yan-Xia Lin

Motivation: Existing methods for estimating copy number variations in array comparative genomic hybridization (aCGH) data are limited to estimations of the gain/loss of chromosome regions for single sample analysis. We propose the linear-median method for estimating shared copy numbers in DNA sequences across multiple samples, demonstrate its operating characteristics through simulations and applications to real cancer data, and compare it to two existing methods.

Results: Our proposed linear-median method has the power to estimate common changes that appear at isolated single probe positions or very short regions. Such changes are hard to detect by current methods. This new …

The Probability Distribution Of Distance Tss-Tls Is Organism Characteristic And Can Be Used For Promoter Prediction, Yun Dai, Ren Zhang, Yan-Xia Lin

Associate Professor Yan-Xia Lin

Transcription is a complicated process which involves the interactions of promoter cis-elements with multiple trans-protein factors. The specific interactions rely not only on the specific sequence recognition between the cis- and trans-factors but also on certain spatial arrangement of the factors in a complex. The relative positioning of involved cis-elements provides the framework for such a spatial arrangement. The distance distribution between gene transcription and translation start sites (TSS-TLS) is the subject of the present study to test an assumption that over evolution, the TSS-TLS distance becomes a distinct character for a given organism. Four representative organisms (Escherichia cloi, Saccharomyces …

Correlations Of Length Distributions Between Non-Coding And Coding Sequences Of Arabidopsis Thaliana, Rachel Caldwell, Yan-Xia Lin, Ren Zhang

Associate Professor Yan-Xia Lin

Gene length and organization are important attributes of genomics. With a large amount of sequence data becoming available, statistical analyses can be applied to this data and will offer beneficial output to research communities. Previous work in this field has focused on protein length and its coding region, while we are also investigating the non-coding regions, as well as trying to uncover any potential correlation that may exist between the regions. Analysis on the Arabidopsis thaliana found there was a strong correlation between the coding sequence length and the 3 UTR region, conditional on the 5 UTR ratios. These results …

Seasonal Adjustment Of An Aggregate Series Using Univariate And Multivariate Basic Structural Models, David Steel, Yan-Xia Lin, Carole Birrell

Associate Professor Yan-Xia Lin

Time series resulting from aggregation of several sub-series can be seasonally adjusted directlyor indirectly. With model-based seasonal adjustment, the sub-series may also be considered as amultivariate system of series and the analysis may be done jointly. This approach has considerableadvantage over the indirect method, as it utilises the covariance structure between the sub-series.This paper compares a model-based univariate and multivariate approach to seasonal adjustment.Firstly, the univariate basic structural model (BSM) is applied directly to the aggregate series. Secondly,the multivariate BSM is applied to a transformed system of sub-series. The prediction meansquared errors of the seasonally adjusted aggregate series resulting from …