2,363 research outputs found
SO MEE KWON
No full text학위논문(박사)--아주대학교 일반대학원 :의학계열,2014. 2TABLE OF CONTENTS
ABSTRACT i
TABLE OF CONTENTS iii
LIST OF FIGURES v
LIST OF TABLES vi
ABBREVIATIONS vii
I. INTORDUCTION 1
A. Background of study 1
B. Cancer genomic study of HCC 3
C. Aims of study 7
II. MATERIALS AND METHODS 10
A. MATERIALS 10
1. Cell-lines 10
2. Human tissues and FFPE samples 10
3. Preparation of RNA and genomic DNA 10
B. METHODS 11
1. Comparative genomic hybridization (CGH) profiling 11
2. Data pre-processing 12
3. DNA copy number profiling based on the T-statistic map (TM) 13
4. cDNA Microarray profiling 14
5. Determination of DNA copy number-dependent transcriptional deregulation 14
6. Validation of the prognostic relevance in the independent data set 15
7. Estimation of genomic DNA copy number by quantitative PCR (qPCR) 16
8. Gene set enrichment analysis 17
9. Short hairpin RNA (shRNA)-mediated knock-down experiment 17
10. Estimation of mRNA expression level using quantitative PCR (qPCR) 20
11. Cell viability and proliferation assay 21
12. Cell invasion assay 22
13. Western Blot analysis 22
14. Statistical analysis 23
III. RESULTS 25
A. Identification of subtype-specific DNA copy number alteration 25
B. Region of Interest at 6p showed subtype-specific DNA copy number alteration and concomitant transcriptional deregulation 32
C. IER3 is a putative biomarker for the ROI at 6p amplicon 33
IV. DISCUSSION 70
V. CONCLUSION 78
VI. REFERENCES 79
국문 요약 91DoctoralIn recent years, cancer heterogeneity, which is essentially inherent in various types of cancer, has been of interest to the cancer genome research. Many studies using various approaches have tried to solve the conundrum of so-called cancer heterogeneity. However, even though many successes have been earned in this area using the genomic analysis, the identification of precise cancer subtypes, which can be informative and useful from the biological and clinical point of view, still remains a challenge. Among the many trials, the multi-layered genomic profiles analysis, in which the genomic copy numbers and gene expression profiles are analyzed by the integrative way to define the chromosomal regions with both genomic copy number variation and concomitant transcriptional deregulation, is posited to provide a promising strategy to identify driver targets. Here, the integrative analysis of the DNA copy numbers and gene expression profiles of hepatocellular carcinoma (HCC) was performed. By comparing DNA copy numbers in HCC subtypes, which have been previously defined based on gene expression pattern, it was found that the HCC subtype showing aggressive phenotype without expressing stemness-related genes had DNA copy number alteration with concordant gene expression changes in the specific chromosomal area at 6p21-24. Among the genes residing at 6p21-24, IER3 was identified as a potential driver. The clinical utility of IER3 copy numbers was demonstrated by validating its clinical correlation in the independent cohorts. In addition, short hairpin RNA-mediated knock-down experiment revealed the functional relevance of IER3 in liver cancer progression. In conclusion, the results of this study suggest that genomic copy number alterations with transcriptional deregulation at 6p21-24 identify an aggressive HCC phenotype and a novel functional biomarker
Optimizing credit limit policy by Markov Decision Process Models
No full textCredit cards have become an essential product for most consumers. Lenders have recognized the profit that can be achieved from the credit card market and thus they have introduced different credit cards to attract consumers. Thus, the credit card market has undergone keen competition in recent years. Lenders realize their operation decisions are crucial in determining how much profit is achieved from a card. This thesis focuses on the most well-known operating policy: the management of credit limit. Lenders traditionally applied static decision models to manage the credit limit of credit card accounts. A growing number of lenders though want improved models so as to monitor the long-term risk and return of credit card borrowers.This study aims to use Markov Decision Process, which is a well-developed sequential decision model, to adjust the credit limit of current credit card accounts. The behavioural score, which is the way of assessing credit card holder's default risk in the next year, is used as the key parameter to monitor the risk of every individual account. The model formulation and the corresponding application techniques, such as state coarse-classification, choice of Markovity order, are discussed in this thesis. One major concern of using Markov Decision Process model is the small sample size in certain states. In general credit card lenders have lots of data. However, there may be no examples in the data of transitions from certain states to default, particularly for those high quality credit card accounts. If one simply uses zero to estimate these states' transition probabilities, this leads to apparent 'structural zeros' states which change the connectedness of the dynamics in the state space. A method is developed in this thesis to overcome such problems in real applications.The economy and retail credit risk are highly correlated and so one key focus of this study is to look at the interaction between credit card behavioural score migrations and the economy. This study uses different credit card datasets, one from Hong Kong and one from United Kingdom, to examine the impact of economy on the credit card borrowers' behaviour. The economies in these two areas were different during the sampling period. Based on these empirical findings, this study has generalized the use of macroeconomic measurements in the credit limit models. This thesis also proposed segmenting the credit card accounts by the accounts' repayment patterns. The credit card population in general can be segmented into Transactors or Revolvers. Empirical findings show the impact of economy are significantly different for Transactors and Revolvers. This study provides a detailed picture of the application of Markov Decision Process models in adjusting the credit limit of credit card accounts
Predicting credit card debt recovery rates: an empirical study using generalised additive models
No full textModelling the profitability of credit cards by Markov decision processes
No full textThis paper derives a model for the profitability of credit cards, which allow lenders to find the optimal dynamic credit limit policy. The model is a Markov decision process, where the states of the system are based on the borrower's behavioural score and the decisions are what credit limit to give the borrower each period. In determining the Markov chain which best describes the borrower's performance second order as well as first order Markov chains are considered and estimation procedures that deal with the low default levels that may exist in the data are considered. A case study is used to show how the optimal credit limit can be derive
Dataset supporting the University of Southampton PhD Thesis 'When Institutional Logics Collide: The Influence of Subjective Knowledge on Novel Products related Behavioural Intentions while Intra-and-Inter-institutional Logics are in Conflict or Synchronised"
No full textDataset supports PhD thesis by Kang, Sukyoung (2024) 'When Institutional Logics Collide: The Influence of Subjective Knowledge on Novel Products related Behavioural Intentions while Intra-and-Inter-institutional Logics are in Conflict or Synchronised".
For the data collection, the online survey was designed in Qualtrics.
The data collection spread out through Prolific
In order to view the data, Excel or SPSS can be used.
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Domain identification for commercial intention-holding posts on Twitter
No full textToday, more people use social networking platforms to convey their desires and recent needs. Actually, there are numerous daily posts carrying commercial intention. The detection of these kinds of user intention would be quite valuable, especially for the platform itself. Firstly, it could help the platform provide precise and instant recommendations to users for its own business interests. Secondly, intention mining works may help link users’ needs by detecting potential buyers and sellers and their specific intentions which can benefit users by optimizing the resources in their hand and increase functional richness.The whole intention mining process generally includes three main stages: user commercial intention filtering, intention domain identification and specific intention words extraction. In this work, the first stage was simplified usingkeywords-based automatic filter followed by a manual screening. The main focus of this paper is the second stage, assigning the intention-holding posts into their own single domain. Three machine learning models and two deeplearning models were proposed to solve this text classification problem. The proposed methods have been evaluated on a dataset containing 5500 real-time intention-holding tweets collected from Twitter. In general, the experimentalresults showed impressive performance with the highest classification accuracy of 96% achieved by Long short-term memory
Modelling the lifetime of banknotes with a semi-Markov chain model
No full textThe quality of banknotes in circulation is important for cash cycles. Central banks continuously try to find new methods for improving the quality of banknotes in circulation, whether by improving the specification of the banknotes or the characteristics of the cash cycle. The way that banknotes deteriorate and the speed with which they do so are some of the main factors affecting the quality of banknotes in circulation and thus, have been drawing the interest of central banks. This study develops a new semi-Markov chain model that could be used by banknote printing companies and central banks to model banknote deterioration. Discrete states of fitness are used in this semi-Markov model to simulate how the banknotes transit between fitness levels. The model requires some input parameters to simulate the cash cycle and present the probability distributions for each state. It is applied to theoretical cash cycles and a sensitivity analysis is performed to identify the parameters that have the greatest impact on the quality of banknotes. This study is the first to apply a semi-Markov model to estimate the lifetime of banknotes. It can be used as a forecasting tool for the proportion of unfit banknotes in circulation
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