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    ๋…ธ์ธ์—์„œ ์Šค๋งˆํŠธํฐ ์‚ฌ์šฉ๊ณผ ๋…ธ์‡ ์˜ ์—ฐ๊ด€์„ฑ ๋ฐ ๊ด€๋ จ์š”์ธ

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    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :๋ณด๊ฑด๋Œ€ํ•™์› ๋ณด๊ฑดํ•™๊ณผ(๋ณด๊ฑดํ•™์ „๊ณต),2019. 8. ์กฐ์„ฑ์ผ.Introduction: With worldwide aging, there are many ongoing studies to further identify the risk factors and ways to prevent age-related conditions. The most actively studied areas include frailty in the elderly. Rapid development and increasing use of smartphones have come to play an important role in health industries. Despite the increasing importance of smartphone use for sustaining healthy life, no large study has reported the characteristics of elderly smartphone users. Our hypothesis is that the ownership of a smartphone is inversely associated with frailty because smartphone owners can benefit from various health applications to manage their health, and the use of smartphone itself can be a good cognitive exercise that can help prevent frailty. Therefore, the aim of this study is to describe the various sociodemographic and medical characteristics of the elderly smartphone users and non-users, and to identify the association between the use of smartphones and frailty. The obtained information may be helpful to screening frailty in small clinics. Methods: We used the baseline data of the Korean Frailty and Aging Cohort Study which is a nationwide cohort study conducted to identify and prevent the factors contributing to aging and frailty. The data of a total of 2935 participants were analyzed for various demographic, socioeconomic, cognitive, and functional characteristics as well as frailty. Frailty was defined using Fried frailty index. The characteristics of the participants were described in terms of smartphone ownership, and multiple logistic regression analysis was performed to assess the association between the use of smartphones and frailty. Results: Out of 2935 participants aged between 70 and 84, 1404 (47.8%) participants were using smartphones, and 1531 (52.2%) participants were using cellphones other than smartphones or did not own a cellphone. The mean age of all participants was 76.0 years old. The smartphone users were more likely to be male (53.3%), with higher educational and economic background compared to non-users. They were also more likely to be in a marital relationship and not living alone, but received less social support, and exhibited poorer daily functional abilities. However, they exhibited higher cognitive capabilities, and more importantly, less frail in all aspects of frailty criteria compared to smartphone non-users. The odds ratio of the association between smartphone ownership and frailty was 0.47, 95% confidence interval 039-055, after adjusting for various related factors. Conclusion: Ownership of a smartphone is a result of multifactorial circumstances and conditions as is frailty. Smartphone non-users in this study were more frail than smartphone users, and exhibited poorer cognitive abilities while maintaining better daily functional abilities and social interaction. Therefore, it is our conclusion that the ownership of a smartphone in older adults represents many background factors that are often linked to frailty in an inverse manner, and a simple question or identification of ones type of phone may be used in conjunction with other methods to screen frailty in older adults.๋ฐฐ๊ฒฝ ๋ฐ ๋ชฉ์  : ์ „ ์„ธ๊ณ„์ ์œผ๋กœ ๊ณ ๋ นํ™”๊ฐ€ ์ง„ํ–‰๋จ์— ๋”ฐ๋ผ ๋งŒ์„ฑ์งˆํ™˜์„ ์˜ˆ๋ฐฉํ•  ์ˆ˜ ์žˆ๋Š” ์œ„ํ—˜์š”์†Œ์™€ ๋ฐฉ๋ฒ•์„ ํŒŒ์•…ํ•˜๊ณ ์ž ํ•˜๋Š” ๋งŽ์€ ์—ฐ๊ตฌ๊ฐ€ ์ง„ํ–‰๋˜๊ณ  ์žˆ๋‹ค. ๋…ธ์‡ ๋Š” ๊ฐ€์žฅ ํ™œ๋ฐœํ•˜๊ฒŒ ์—ฐ๊ตฌ๋˜๊ณ  ์žˆ๋Š” ๋ถ„์•ผ ์ค‘ ํ•˜๋‚˜์ด๋‹ค. ๋…ธ์‡  ์—ฐ๊ตฌ์™€ ๋™์‹œ์— ์ง€๋‚œ ์ˆ˜๋…„๊ฐ„ ์Šค๋งˆํŠธํฐ์€ ๋น ๋ฅธ ๋ฐœ์ „๊ณผ ์„ฑ์žฅ์„ ๋ณด์—ฌ ์ด์ œ ๊ฑด๊ฐ• ์‚ฌ์—…์— ์ค‘์š”ํ•œ ์—ญํ• ์„ ํ•˜๊ฒŒ ๋˜์—ˆ๋‹ค. ๊ฑด๊ฐ•ํ•œ ์‚ถ์˜ ์˜์œ„์— ์Šค๋งˆํŠธํฐ ์‚ฌ์šฉ์˜ ์ค‘์š”์„ฑ์ด ์ฆ๊ฐ€ํ•˜๊ณ  ์žˆ์Œ์—๋„ ๋ถˆ๊ตฌํ•˜๊ณ  ๋…ธ์ธ ์Šค๋งˆํŠธํฐ ์‚ฌ์šฉ์ž๋“ค์˜ ํŠน์„ฑ์— ๊ด€ํ•œ ๋Œ€๊ทœ๋ชจ ์—ฐ๊ตฌ๋Š” ๋ฏธ๋ฏธํ•˜๋‹ค. ๋ณธ ์—ฐ๊ตฌ์˜ ๊ฐ€์„ค์€ ์Šค๋งˆํŠธํฐ ์†Œ์œ ์ž๋“ค์€ ๊ฑด๊ฐ•์„ ๊ด€๋ฆฌํ•˜๊ธฐ ์œ„ํ•ด ๋‹ค์–‘ํ•œ ์Šค๋งˆํŠธํฐ ์• ํ”Œ๋ฆฌ์ผ€์ด์…˜์„ ์‚ฌ์šฉํ•  ์ˆ˜ ์žˆ์œผ๋ฉฐ ์Šค๋งˆํŠธํฐ์˜ ์‚ฌ์šฉ ์ž์ฒด๊ฐ€ ์ข‹์€ ์ธ์ง€๊ธฐ๋Šฅ ๋ฐœ๋‹ฌ์šด๋™์ด ๋˜๊ธฐ ๋•Œ๋ฌธ์— ์Šค๋งˆํŠธํฐ ์†Œ์œ ์ž๋“ค์—๊ฒŒ ๋…ธ์‡ ๊ฐ€ ๋œ ์กด์žฌํ•  ๊ฒƒ์ด๋ผ๋Š” ๊ฒƒ์ด๋‹ค. ๋”ฐ๋ผ์„œ, ๋ณธ ์—ฐ๊ตฌ๋ฅผ ํ†ตํ•ด ๋…ธ์ธ ์Šค๋งˆํŠธํฐ ์‚ฌ์šฉ์ž ๋ฐ ๋น„์‚ฌ์šฉ์ž์˜ ๋‹ค์–‘ํ•œ ์‚ฌํšŒ์ธ๊ตฌํ•™์  ๋ฐ ์˜ํ•™์  ํŠน์„ฑ์„ ๊ธฐ์ˆ ํ•˜๊ณ , ์Šค๋งˆํŠธํฐ ์‚ฌ์šฉ๊ณผ ๋…ธ์‡ ์˜ ์—ฐ๊ด€์„ฑ์„ ํ™•์ธํ•˜๊ณ ์ž ํ•œ๋‹ค. ์ด๋ฅผ ํ†ตํ•ด ์–ป์€ ์ •๋ณด๋Š” ์†Œ๊ทœ๋ชจ ์˜๋ฃŒ์‹œ์„ค์—์„œ ๋…ธ์‡ ๋ฅผ ์„ ๋ณ„ํ•˜๋Š”๋ฐ ํฐ ๋„์›€์ด ๋  ๊ฒƒ์ด๋‹ค. ๋ฐฉ๋ฒ• : ๋ณธ ์—ฐ๊ตฌ๋Š” ํ•œ๊ตญ๋…ธ์ธ๋…ธ์‡ ์ฝ”ํ˜ธํŠธ์‚ฌ์—…(KFACS)์˜ ์ž๋ฃŒ๋ฅผ 1์ฐจ ์ž๋ฃŒ๋ฅผ ์‚ฌ์šฉํ•˜์—ฌ ์ง„ํ–‰๋˜์—ˆ๋‹ค. KFACS๋Š” ๋…ธํ™” ๋ฐ ๋…ธ์‡ ์™€ ๊ด€๋ จํ•œ ์ธ์ž๋“ค์„ ์ฐพ์•„๋‚ด๊ณ  ์ด๋ฅผ ์˜ˆ๋ฐฉํ•˜๊ณ ์ž ์ง„ํ–‰๋˜๊ณ  ์žˆ๋Š” ํ•œ๊ตญ์˜ ๊ตญ๊ฐ€๊ธฐ๋ฐ˜ ์ฝ”ํ˜ธํŠธ ์—ฐ๊ตฌ์ด๋‹ค. ๋งŒ 70์„ธ์—์„œ 84์„ธ์˜ ์ด 2935๋ช… ์ฐธ๊ฐ€์ž์˜ ๋ฐ์ดํ„ฐ๋ฅผ ์‚ฌ์šฉํ•˜์—ฌ ๋‹ค์–‘ํ•œ ์ธ๊ตฌํ•™์ , ์‚ฌํšŒ๊ฒฝ์ œ์ , ์ธ์ง€์  ๋ฐ ๊ธฐ๋Šฅ์  ํŠน์„ฑ๊ณผ ๊ด€๋ จ๋œ ๋ถ„์„์„ ์ง„ํ–‰ํ•˜์˜€์œผ๋ฉฐ ๋…ธ์‡ ์™€์˜ ๊ด€๋ จ์„ฑ ๋˜ํ•œ ๋ถ„์„ํ•˜์˜€๋‹ค. ๋…ธ์‡ ๋Š” Fried ๋…ธ์‡ ์ง€์ˆ˜๋ฅผ ์‚ฌ์šฉํ•˜์—ฌ ์ •์˜ํ•˜์˜€๋‹ค. ์ฐธ๊ฐ€์ž๋“ค์˜ ํŠน์„ฑ์„ ์Šค๋งˆํŠธํฐ ์†Œ์œ  ์œ ๋ฌด์— ๋”ฐ๋ผ ๊ธฐ์ˆ ํ•˜์˜€์œผ๋ฉฐ ๋กœ์ง€์Šคํ‹ฑ ๋‹ค์ค‘ํšŒ๊ท€๋ถ„์„์„ ์ˆ˜ํ–‰ํ•˜์—ฌ ์Šค๋งˆํŠธํฐ ์‚ฌ์šฉ๊ณผ ๋…ธ์‡ ์˜ ์—ฐ๊ด€์„ฑ์„ ํ‰๊ฐ€ํ•˜์˜€๋‹ค. ๊ฒฐ๊ณผ : ์ด 2935๋ช…์˜ ์ฐธ๊ฐ€์ž ์ค‘ 1404๋ช…(47.8%)์ด ์Šค๋งˆํŠธํฐ์„ ์‚ฌ์šฉํ•˜์˜€์œผ๋ฉฐ 1531๋ช…(52.2%)๋Š” ์Šค๋งˆํŠธํฐ์ด ์•„๋‹Œ ํ•ธ๋“œํฐ์„ ์‚ฌ์šฉํ•˜๊ฑฐ๋‚˜ ํ•ธ๋“œํฐ์„ ๊ฐ€์ง€๊ณ  ์žˆ์ง€ ์•Š์•˜๋‹ค. ์ฐธ๊ฐ€์ž๋“ค์˜ ํ‰๊ท  ์—ฐ๋ น์€ 76.0์„ธ์˜€๋‹ค. ์Šค๋งˆํŠธํฐ ์‚ฌ์šฉ์ž๋“ค์€ ๋‚จ์„ฑ์ด ๋” ๋งŽ์•˜์œผ๋ฉฐ (53.3%), ๋น„์‚ฌ์šฉ์ž๋“ค์— ๋น„ํ•ด ๊ต์œก ๋ฐ ๊ฒฝ์ œ์  ์ˆ˜์ค€์ด ๋†’์•˜๋‹ค. ์‚ฌ์šฉ์ž๋“ค์€ ๋˜ํ•œ ๊ฒฐํ˜ผ์ƒํƒœ์ธ ๋น„์œจ์ด ๋†’๊ณ  ๋…๊ฑฐ์˜ ๋น„์œจ์ด ๋‚ฎ์•˜์œผ๋‚˜ ์‚ฌํšŒ์  ์ƒํ˜ธ๊ด€๊ณ„๊ฐ€ ์ ์—ˆ๊ณ  ๋” ๋‚ฎ์€ ์ผ์ƒ์  ๋Šฅ๋ ฅ์„ ๋ณด์—ฌ์ฃผ์—ˆ๋‹ค. ์ด์— ๋ฐ˜ํ•ด ์ธ์ง€๊ธฐ๋Šฅ์€ ๋” ๋›ฐ์–ด๋‚ฌ์œผ๋ฉฐ, ํŠนํžˆ ๋…ธ์‡ ๊ธฐ์ค€์˜ 5๊ฐ€์ง€ ํ•ญ๋ชฉ ๋ชจ๋‘์—์„œ ๋น„์‚ฌ์šฉ์ž๋“ค๋ณด๋‹ค ๋›ฐ์–ด๋‚œ ์ƒํƒœ๋ฅผ ๋ณด์˜€๋‹ค. ์Šค๋งˆํŠธํฐ ์‚ฌ์šฉ๊ณผ ๋…ธ์‡ ์˜ ์—ฐ๊ด€์„ฑ์˜ ๊ต์ฐจ๋น„๋Š” ๋‹ค์–‘ํ•œ ๊ด€๋ จ ์š”์†Œ๋ฅผ ๋ณด์ •ํ•œ ํ›„ 0.47์ด์—ˆ์œผ๋ฉฐ 95% ์‹ ๋ขฐ๊ตฌ๊ฐ„์€ 0.39~0.55์˜€๋‹ค. ๊ฒฐ๋ก  : ์Šค๋งˆํŠธํฐ์˜ ์†Œ์œ ๋Š” ๋…ธ์‡ ์™€ ๋งˆ์ฐฌ๊ฐ€์ง€๋กœ ์—ฌ๋Ÿฌ๊ฐ€์ง€ ์š”์†Œ๊ฐ€ ์ƒํ˜ธ์ž‘์šฉํ•œ ๊ฒฐ๊ณผ๋ฌผ์ด๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์Šค๋งˆํŠธํฐ ๋น„์‚ฌ์šฉ์ž๋“ค์ด ์Šค๋งˆํŠธํฐ ์‚ฌ์šฉ์ž๋“ค๋ณด๋‹ค ๋” ๋›ฐ์–ด๋‚œ ์ผ์ƒ์  ๋Šฅ๋ ฅ๊ณผ ์‚ฌํšŒ์  ์ƒํ˜ธ๊ด€๊ณ„๋ฅผ ๋ณด์—ฌ์ฃผ์—ˆ์œผ๋‚˜ ์ธ์ง€๊ธฐ๋Šฅ์ด ๋” ๋ถ€์กฑํ•˜์˜€์œผ๋ฉฐ ๋” ๋†’์€ ๋…ธ์‡ ์˜ ๋น„์œจ์„ ๋‚˜ํƒ€๋‚ด์—ˆ๋‹ค. ๋”ฐ๋ผ์„œ, ๊ณ ๋ น์ž์˜ ์Šค๋งˆํŠธํฐ ์†Œ์œ ๋Š” ์ข…์ข… ๋…ธ์‡ ์™€ ์—ญ์ƒ๊ด€๊ด€๊ณ„๋ฅผ ๋‚˜ํƒ€๋‚ด๋Š” ์—ฌ๋Ÿฌ๊ฐ€์ง€ ์ธ์ž๋ฅผ ๋Œ€๋ณ€ํ•œ๋‹ค๊ณ  ๋ณผ ์ˆ˜ ์žˆ์œผ๋ฉฐ, ์–ด๋–ค ํƒ€์ž…์˜ ํ•ธ๋“œํฐ์„ ์‚ฌ์šฉํ•˜๊ณ  ์žˆ๋Š”์ง€์— ๋Œ€ํ•œ ๊ฐ„๋‹จํžˆ ์งˆ๋ฌธ์ด ๋‹ค๋ฅธ ๋…ธ์‡  ๊ด€๋ จ ์„ ๋ณ„๊ฒ€์‚ฌ์™€ ํ•จ๊ป˜ ์ž‘์€ ์˜๋ฃŒ๊ธฐ๊ด€์—์„œ ๋…ธ์‡ ๋ฅผ ์„ ๋ณ„ํ•˜๊ธฐ ์œ„ํ•œ ์ข‹์€ ๋ฐฉ๋ฒ•์ด ๋  ์ˆ˜ ์žˆ๊ฒ ๋‹ค.Chapter 1. Introduction 1 1.1. Aging society and frailty 1 1.2. Adoption of smartphones 1 1.2.1. mHealth 1 1.2.2. Characteristics of elderly smartphone adopters 2 1.3. Frailty and smartphones 3 1.4. Objective 4 Chapter 2. Materials and Methods 6 2.1. Study Design and Population 6 2.2. Definition of Frailty 6 2.3. Other covariates of interest 7 2.4. Statistical Methods 9 Chapter 3. Results 10 3.1. General characteristics of the participants 10 3.2. Distribution of smartphone use and prevalence of frailty 15 3.3. Social, functional, and cognitive assessments 21 3.4. Association between smartphone use and frailty 26 Chapter 4. Discussion 32 4.1. Characteristics of elderly smartphone users and non-users 32 4.2. Digital frailty 36 4.3. Strengths and limitations 38 Chapter 5. Conclusion 41 References 42 Abstract in Korean 46Maste

    Legislative Research on the Delegation of the Ship Inspections under the Ship Safety Act

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    ํ˜„ํ–‰ ์„ ๋ฐ•์•ˆ์ „๋ฒ•์ƒ์˜ โ€˜๋Œ€ํ–‰โ€™์ œ๋„์™€ ์ •๋ถ€์กฐ์ง๋ฒ•์ƒ์˜ โ€˜๋ฏผ๊ฐ„์œ„ํƒโ€™์ œ๋„์˜ ๊ณตํ†ต์ ์€ ๋ชจ๋‘ ๊ตญ๊ฐ€์‚ฌ๋ฌด ์ดํ–‰์ฃผ์ฒด๋กœ์„œ ์•„์ง๋„ ๋ฏผ๊ฐ„์— ๋Œ€ํ•œ ์ถฉ๋ถ„ํ•œ ์‹ ๋ขฐ๊ฐ€ ๋ถ€์กฑํ•˜๋‹ค๋Š” ๊ฒƒ์„ ๋ณด์—ฌ์ค€๋‹ค๋Š” ์ ์ด๋‹ค. ๋” ์ •ํ™•ํžˆ ๋งํ•˜๋ฉด ๋ฏผ๊ฐ„์˜ ์ „๋ฌธ์„ฑ์„ ์‹ ๋ขฐํ•˜๋”๋ผ๋„ ๊ทธ ์‹ ๋ขฐ๋ฅผ ๋‹ด์„ ์ˆ˜ ์žˆ๋Š” ๋ฒ•์ œ๋„์  ์žฅ์น˜๋กœ์„œ ์ž…๋ฒ•๊ธฐ์ˆ ์˜ ์ฐฝ์˜๋ ฅ ๋ถ€์กฑ์ด๋ผ๊ณ  ํ•  ์ˆ˜ ์žˆ๋‹ค. ์‚ฌ์ธ์„ ํ™œ์šฉํ•œ ๊ตญ๊ฐ€ํ–‰์ •์‚ฌ๋ฌด์˜ ์ฒ˜๋ฆฌ์— ์žˆ์–ด์„œ ๊ถŒํ•œ๊ณผ ์ฑ…์ž„์˜ ์ด์ „์—ฌ๋ถ€๋ผ๋Š” ๊ฐœ๋…๋ก ์  ๋„๊ทธ๋งˆ์— ์‚ฌ๋กœ์žกํ˜€ ์‹ค์šฉ์ ์ธ ์ ‘๊ทผ์„ ํ•˜์ง€ ๋ชปํ•˜๊ณ  ์œ„ํƒ๊ณผ ๋Œ€ํ–‰์˜ ์–‘ ๊ทน๋‹จ ์‚ฌ์ด์—์„œ ํ˜ผ๋ˆ์„ ๊ฑฐ๋“ญํ–ˆ๋˜ ๊ฒƒ์ด๋‹ค. ์ด ๋…ผ๋ฌธ์€ ์ตœ์†Œํ•œ ์„ ๋ฐ•์•ˆ์ „๋ฒ•์ƒ ์„ ๋ฐ•๊ฒ€์‚ฌ์˜ ์˜์—ญ์—์„œ๋Š” ๊ตญ์ œํ˜‘์•ฝ๊ณผ ์™ธ๊ตญ(EU, ๋ฏธ๊ตญ)์—์„œ ์ทจํ•˜๊ณ  ์žˆ๋Š” delegation (๊ตญ๋ฏผ์˜ ๊ถŒ๋ฆฌ์˜๋ฌด ๊ด€๋ จ์‚ฌ๋ฌด์— ๊ด€ํ•œ ๋Œ€๋ฆฌํšจ๊ณผ๋ฅผ ์ˆ˜๋ฐ˜ํ•˜๋Š” ํŠน์ˆ˜ํ•œ ๋ฏผ๊ฐ„์œ„ํƒ)์ด ์œ„ํƒ๊ณผ ๋Œ€ํ–‰์˜ ์–‘ ๊ทน๋‹จ์˜ ํ•œ๊ณ„๋ฅผ ๋ฒ—์–ด๋‚˜ ๊ฐ„๊ฒฐ ๋ช…๋ฃŒํ•œ ๋ฒ•๋ฅ ๊ด€๊ณ„์˜ ํ•ด๋ฒ•์„ ์ œ์‹œํ•  ์ˆ˜ ์žˆ์Œ์„ ์ฆ๋ช…ํ•˜๊ณ  ์žˆ๋‹ค. ๊ทธ๋ฆฌ๊ณ  ๊ทธ ์‹ค์šฉ์  ๋Œ€์•ˆ์€ ์„ ๋ฐ•์•ˆ์ „๋ฒ• ๋ฟ๋งŒ ์•„๋‹ˆ๋ผ ์‚ฌ์‹ค์ƒ ๊ด‘์˜์˜ ์„ ๋ฐ•๊ฒ€์‚ฌ์— ํ•ด๋‹นํ•˜๋Š” ๊ฐ์ข… ํ•ด์‚ฌ๋ฒ•๊ทœ์ƒ ๋ฏผ๊ฐ„์˜ ์ „๋ฌธ์„ฑ์— ์˜์กดํ•  ์ˆ˜๋ฐ–์— ์—†๋Š” ์ค‘๋Œ€ํ•œ ๊ตญ๊ฐ€์‚ฌ๋ฌด์˜ ์‚ฌ์ธ์— ๋Œ€ํ•œ ์œ„ํƒ์—์„œ ์„ ํƒ ๊ฐ€๋Šฅํ•œ ๋ฒ•ํ˜•์‹์ด ๋  ์ˆ˜ ์žˆ๋Š” ๊ฐ€๋Šฅ์„ฑ์„ ์ œ์‹œํ•˜๊ณ  ์žˆ๋‹ค. ์ •๋ถ€์กฐ์ง๋ฒ•์ƒ ๋ฏผ๊ฐ„์œ„ํƒ์˜ ๊ธฐ์ค€์„ ์—„๊ฒฉํžˆ ๋”ฐ๋ฅผ ๋•Œ ์„ ๋ฐ•๊ฒ€์‚ฌ๋Š” ๊ตญ๋ฏผ์˜ ๊ถŒ๋ฆฌ์˜๋ฌด์™€ ๊ด€๋ จ๋˜๊ธฐ ๋•Œ๋ฌธ์— ์‚ฌ์ธ์—๊ฒŒ ์œ„ํƒํ•  ์ˆ˜ ์—†๊ณ  ์ •๋ถ€๊ฐ€ ์ง์ ‘ ์ˆ˜ํ–‰ํ•ด์•ผ ํ•œ๋‹ค. ์„ ๋ฐ•์•ˆ์ „๋ฒ•์ƒ ์—…๋ฌด์˜ ๋Œ€ํ–‰์˜ ๊ธฐ์ค€์„ ์—„๊ฒฉํžˆ ๋”ฐ๋ฅผ ๋•Œ ๋Œ€ํ–‰๊ธฐ๊ด€์€ ์‚ฌ์‹คํ–‰์œ„(๋‹จ์ˆœ ํ–‰์ •์‚ฌ๋ฌด)๋งŒ์„ ์ˆ˜ํ–‰ํ•ด์•ผ ํ•˜๊ธฐ ๋•Œ๋ฌธ์— ์„ ๋ฐ•์˜ ๊ฐํ•ญ์„ฑ๊ณผ ์•ˆ์ „์— ๊ด€ํ•œ ์ค€๋ฒ•๋ฅ ํ–‰์œ„์  ํ–‰์ •ํ–‰์œ„์ธ ํ™•์ธํ–‰์œ„(์„ ๋ฐ•์•ˆ์ „๋ฒ• ๋“ฑ ๊ธฐ์ˆ ๊ทœ์น™ ์ ํ•ฉ์„ฑ ํ‰๊ฐ€ํ–‰์œ„)๋กœ์„œ์˜ ์„ ๋ฐ•๊ฒ€์‚ฌ๋ฅผ ์ˆ˜ํ–‰ํ•ด์„œ๋Š” ์•ˆ ๋œ๋‹ค. ๊ทธ๋ ‡๋‹ค๋ฉด ํ˜„์‹ค์—์„œ ์„ ๊ธ‰๋ฒ•์ธ ๋“ฑ ๊ณต์ธ์„ ๋ฐ•๊ฒ€์‚ฌ๊ธฐ๊ด€์ด ๊ตญ๋ฏผ์˜ ๊ถŒ๋ฆฌ์˜๋ฌด์™€ ๊ด€๋ จ๋œ ๊ตญ๊ฐ€์‚ฌ๋ฌด๋ฅผ ์ค€๋ฒ•๋ฅ ํ–‰์œ„์  ํ–‰์ •ํ–‰์œ„(ํ™•์ธํ–‰์œ„) ๋˜๋Š” ๊ถŒ๋ ฅ์  ์‚ฌ์‹คํ–‰์œ„๋กœ์„œ ์œ„ํƒ์ด ์•„๋‹Œ ๋Œ€ํ–‰์˜ ๋ฐฉ์‹์œผ๋กœ ์ˆ˜ํ–‰ํ•˜๊ฒŒ ๋˜๋Š” ๊ฒƒ์„ ์–ด๋–ป๊ฒŒ ์ดํ•ดํ•ด์•ผ ํ•˜๋Š” ๊ฒƒ์ผ๊นŒ? ์ด ๋…ผ๋ฌธ์€ ํ•ด์ƒ์˜ ์˜์—ญ์—์„œ ์„ ๋ฐ•๊ฒ€์‚ฌ๋Š” ํ•œ๊ตญ๋ฒ•์ƒ์˜ ์œ„ํƒ์ด๋‚˜ ๋Œ€ํ–‰๊ณผ ๋‹ค๋ฅธ ๊ตญ์ œ์‚ฌํšŒ์˜ ์˜ค๋žœ ๊ด€ํ–‰๊ณผ ๊ทœ๋ฒ”์— ์˜ํ•ด ํ˜•์„ฑ๋œ ๊ณ ์œ ํ•œ delegation์˜ ๋ฒ•ํ˜•์‹์„ ์ทจํ•  ์ˆ˜ ์žˆ์Œ์„ ์ œ์‹œํ•˜๊ณ  ์žˆ๋‹ค.Abstract ๏ฅถ ่ชž ์ œ1์žฅ ์„œ ๋ก  ์ œ1์ ˆ ์—ฐ๊ตฌ์˜ ๋ชฉ์  ๋ฐ ๋ฐฐ๊ฒฝ 1 ์ œ2์ ˆ ์—ฐ๊ตฌ์˜ ๋ฐฉ๋ฒ• ๋ฐ ๋ฒ”์œ„ 6 ์ œ2์žฅ ์„ ๋ฐ•๊ฒ€์‚ฌ์˜ ๊ฐœ๋…๊ณผ ๊ตฌ์„ฑ ์ œ1์ ˆ ์„ ๋ฐ•๊ฒ€์‚ฌ์˜ ๊ทœ๋ฒ”์  ์ •์˜ 14 โ… . ์ตœ๊ด‘์˜์˜ ์„ ๋ฐ•๊ฒ€์‚ฌ (๊ฐ•์ œ๊ฒ€์‚ฌ์™€ ์ž„์˜๊ฒ€์‚ฌ) 14 โ…ก. ๊ด‘์˜์˜ ์„ ๋ฐ•๊ฒ€์‚ฌ (ํ•ด์‚ฌ๋ฒ•๊ทœ ์ค‘์‹ฌ) 17 โ…ข. ํ˜‘์˜์˜ ์„ ๋ฐ•๊ฒ€์‚ฌ (์„ ๋ฐ•์•ˆ์ „๋ฒ• ์ค‘์‹ฌ) 19 โ…ฃ. ๊ทœ๋ฒ”์  ์„ ๋ฐ•๊ฒ€์‚ฌ๊ฐœ๋…์˜ ์‹ค์ต 26 ์ œ2์ ˆ ์„ ๋ฐ•๊ฒ€์‚ฌ์˜ ๋‹ค์›์  ๋ฒ•์›์„ฑ(ๆณ•ๆบๆ€ง)๊ณผ ๋ฒ•์  ์„ฑ์งˆ 33 โ… . ์„ ๋ฐ•๊ฒ€์‚ฌ์˜ ๋‹ค์›์  ๋ฒ•์›์„ฑ 33 โ…ก. ์„ ๋ฐ•๊ฒ€์‚ฌ์˜ ๋ฒ•์  ์„ฑ์งˆ 35 โ…ข. ํ–‰์ •์ฒญ์˜ ๊ณ ๊ถŒ์  ํ–‰์ •ํ–‰์œ„๋กœ์„œ์˜ ์„ ๋ฐ•๊ฒ€์‚ฌ 39 ์ œ3์ ˆ ์„ ๋ฐ•์•ˆ์ „๋ฒ•์ƒ ์„ ๋ฐ•๊ฒ€์‚ฌ์˜ ๊ตฌ์„ฑ 40 โ… . ์„ ๋ฐ•์•ˆ์ „๋ฒ•์˜ ๋ฒ•๋ น์ฒด๊ณ„์™€ ์„ ๊ธ‰๊ทœ์น™์˜ ํ‘œ์ค€์ฒด๊ณ„ 40 โ…ก. ๊ธฐ๊ตญ์ •๋ถ€์˜ ๊ฐํ•ญ์„ฑ ๋ฐ ์•ˆ์ „ ๊ฒ€์‚ฌ 44 โ…ข. ์„ ๊ธ‰๋ฒ•์ธ์˜ ๊ณต์ต์  ์„ ๊ธ‰๊ฒ€์‚ฌ์™€ ์ •๋ถ€๋Œ€ํ–‰๊ฒ€์‚ฌ์˜ ๋ณ‘ํ–‰์„ฑ 48 ์ œ3์žฅ ๋ฏผ๊ฐ„์œ„ํƒ๋ฒ•์ œ ๋‚ด ์„ ๋ฐ•๊ฒ€์‚ฌ ๋Œ€ํ–‰์ œ๋„์˜ ํ•œ๊ณ„ ์ œ1์ ˆ ์‚ฌ์ธ์— ์˜ํ•œ ๋Œ€ํ–‰์˜ ์ผ๋ฐ˜๋ฒ•์  ๊ทผ๊ฑฐ 51 โ… . ํ–‰์ •๊ถŒํ•œ๋ฒ•์ •์ฃผ์˜์™€ ๊ตญ๊ฐ€์‚ฌ๋ฌด ์œ„์ž„์˜ ์™„ํ™” 51 โ…ก. ๊ตญ๋‚ด๋ฒ•๋ น์ƒ ๋ฏผ๊ฐ„์œ„ํƒ์ œ๋„์˜ ๊ธฐ๋ณธ๊ตฌ์กฐ 54 โ…ข. ๋ฏผ๊ฐ„์œ„ํƒ์˜ ์ผ๋ฐ˜๋ฒ•์œผ๋กœ์„œ ์ •๋ถ€์กฐ์ง๋ฒ•์˜ ํ•œ๊ณ„ 60 ์ œ2์ ˆ ์„ ๋ฐ•๊ฒ€์‚ฌ์˜ ์ œ๋„์  ์œ„ํƒ๊ตฌ์กฐ 62 โ… . ์„ ๋ฐ•์•ˆ์ „๋ฒ•์ƒ ๋ถˆ์™„์ „ ์„ ๋ฐ•๊ฒ€์‚ฌ ์œ„ํƒ๊ตฌ์กฐ 62 โ…ก. ๊ตญ์ œํ˜‘์•ฝ ๋ฐ EU์˜ ์ œ๋„ํ™”๋œ ์„ ๋ฐ•๊ฒ€์‚ฌ์œ„ํƒ 63 โ…ข. ์„ ๋ฐ•๊ฒ€์‚ฌ ์œ„ํƒ์ œ๋„์˜ ์‚ฌํšŒ์  ๊ธฐ๋Šฅ 64 โ…ฃ. ๊ตญ๋‚ด๋ฒ•์ƒ ์ œ๋„ํ™”๋œ ๋ฏผ๊ฐ„์œ„ํƒ์œผ๋กœ์˜ ์ •๋ฆฝ ํ•„์š”์„ฑ 70 ์ œ3์ ˆ ์„ ๋ฐ•์•ˆ์ „๋ฒ•์ƒ ์—…๋ฌด๋Œ€ํ–‰์˜ ์Ÿ์  72 I. ์—…๋ฌด๋Œ€ํ–‰์˜ ๋ฒ•๋ฅ ๊ด€๊ณ„ ๋ถˆ๋ช…ํ™•์„ฑ๊ณผ ํ•ด๊ฒฐ๊ณผ์ œ 72 II. ๊ตญ๋ฏผ์˜ ๊ถŒ๋ฆฌ์˜๋ฌด ๊ด€๋ จ์‚ฌ๋ฌด์™€ ๋Œ€ํ–‰์˜ ์ ํ•ฉ์„ฑ ์—ฌ๋ถ€ 74 III. ํ–‰์ •ํ˜•๋ฒŒ์ œ๋„์˜ ๊ณผ์ž‰์„ฑ 76 ์ œ4์žฅ ์„ ๋ฐ•๊ฒ€์‚ฌ ์œ„ํƒ์ œ๋„์— ๊ด€ํ•œ ๋น„๊ต๋ฒ•์  ๊ณ ์ฐฐ ์ œ1์ ˆ ๊ตญ์ œํ˜‘์•ฝ์ƒ ์„ ๋ฐ•๊ฒ€์‚ฌ์˜ ๋ฏผ๊ฐ„์œ„ํƒ 81 โ… . ๋…ผ์˜์˜ ๊ธฐ์ดˆ 81 โ…ก. RO Code ์ƒ ๊ณต์ธ์„ ๋ฐ•๊ฒ€์‚ฌ๊ธฐ๊ด€์— ๋Œ€ํ•œ ์œ„ํƒ์ œ๋„ 82 โ…ข. SOLAS, MARPOL, ICLL ๋“ฑ์˜ ์„ ๋ฐ•๊ฒ€์‚ฌ ์œ„ํƒ์ œ๋„ 95 IV. ์†Œ๊ฒฐ: ์„ ๊ธ‰๊ทœ์น™์˜ ๊ณต๊ทœ๋ฒ”ํ™” ๊ธฐ๋ฐ˜ ์ •๋ถ€์ฑ…์ž„ ๊ฐ•์กฐํ˜• ๋ฏผ๊ฐ„์œ„ํƒ 106 ์ œ2์ ˆ EU ๊ณตํ†ต์ง€์นจ์ƒ ์„ ๋ฐ•๊ฒ€์‚ฌ์˜ ๋ฏผ๊ฐ„์œ„ํƒ 108 โ… . EU ๊ณตํ†ต์ง€์นจ๊ณผ ์ •๋ถ€์˜ ์˜๋ฌด 108 โ…ก. EU ๊ณตํ†ต์ง€์นจ ๋ณธ๋ฌธ๊ณผ ์„ ๋ฐ•๊ฒ€์‚ฌ ์œ„ํƒ์ œ๋„ 119 โ…ข. ์†Œ๊ฒฐ: ์„ ๊ธ‰๊ทœ์น™์˜ ๊ณต๊ทœ๋ฒ”ํ™” ๊ธฐ๋ฐ˜ ๋ฏผ๊ด€ํ˜‘๋ ฅ ๊ฐ•์กฐํ˜• ๋ฏผ๊ฐ„์œ„ํƒ 130 ์ œ3์ ˆ EU๊ณตํ†ต๊ทœ์น™์ƒ ์„ ๋ฐ•๊ฒ€์‚ฌ์˜ ๋ฏผ๊ฐ„์œ„ํƒ 133 โ… . EU ๊ณตํ†ต๊ทœ์น™๊ณผ RO์˜ ์˜๋ฌด 133 โ…ก. EU ๊ณตํ†ต๊ทœ์น™ ๋ณธ๋ฌธ๊ณผ ์„ ๋ฐ•๊ฒ€์‚ฌ ์œ„ํƒ์ œ๋„ 139 โ…ข. ์†Œ๊ฒฐ: ์ •๋ถ€์˜ ์—„๊ฒฉ ๊ด€๋ฆฌํ˜• ํŠน์ˆ˜ํ•œ ๋ฏผ๊ฐ„์œ„ํƒ 155 ์ œ4์ ˆ ๋ฏธ๊ตญ์—ฐ๋ฐฉ๋ฒ•๋ น์ƒ ์„ ๋ฐ•๊ฒ€์‚ฌ์˜ ๋ฏผ๊ฐ„์œ„ํƒ 156 โ… . ๋…ผ์˜์˜ ๊ธฐ์ดˆ 157 โ…ก. ๋ฏธ๊ตญ ์—ฐ๋ฐฉ๋ฒ•๋ น์ƒ ์œ„ํƒ์ œ๋„์™€ ๊ตญ๊ฐ€์‚ฌ๋ฌด์˜ ๊ธฐ๋Šฅ์  ์œ ํ˜•ํ™” 157 III. ๋ฏผ๊ฐ„์œ„ํƒ ๋Œ€์ƒ์‚ฌ๋ฌด๋กœ์„œ์˜ ์„ ๋ฐ•๊ฒ€์‚ฌ์™€ ๊ทธ ์„ฑ์งˆ ํ•ด์„ 171 โ…ฃ. ์†Œ๊ฒฐ: ์ •๋ถ€์˜ ์˜จ๊ฑด ๊ด€๋ฆฌํ˜• ํŠน์ˆ˜ํ•œ ๋ฏผ๊ฐ„์œ„ํƒ 175 ์ œ5์žฅ ์„ ๋ฐ•๊ฒ€์‚ฌ ์œ„ํƒ์ œ๋„์˜ ๊ตญ๋‚ด์  ๋ฒ•๋ฅ ๊ด€๊ณ„ ์ œ1์ ˆ ๋ฏผ๊ฐ„์œ„ํƒ๊ณผ ์„ ๋ฐ•๊ฒ€์‚ฌ ๋Œ€ํ–‰์— ๊ด€ํ•œ ๊ตญ๋‚ด๋ฒ•๋ น ์—ฐํ˜๊ฒ€ํ†  182 โ… . ์ •๋ถ€์กฐ์ง๋ฒ•์ƒ ๋ฏผ๊ฐ„์œ„ํƒ์ œ๋„ ๋„์ž…์—ฐํ˜ 182 โ…ก. ํ–‰์ •๊ถŒํ•œ์˜์œ„์ž„๋ฐ์œ„ํƒ์—๊ด€ํ•œ๊ทœ์ •์ƒ ๋ฏผ๊ฐ„์œ„ํƒ์ œ๋„ ๋„์ž…์—ฐํ˜ 185 โ…ข. ์„ ๋ฐ•์•ˆ์ „๋ฒ•์ƒ ๊ฒ€์‚ฌ๋Œ€ํ–‰์ œ๋„์˜ ๋„์ž…์—ฐํ˜ 198 โ…ฃ. ์‚ฌ์  ํ–‰์œ„์˜ ๊ตญ๊ฐ€ํ–‰์ •์‚ฌ๋ฌด ์˜์ œ๊ธฐ๋ฐ˜ํ˜• ๋ฏผ๊ฐ„์œ„ํƒ 211 ์ œ2์ ˆ ๋ฏผ๊ฐ„์œ„ํƒ, ๋Œ€ํ–‰, ์œ ์‚ฌ๊ฐœ๋… ๊ฐ„ ๊ฐœ๋…๋ก ์  ๊ฒ€ํ†  213 โ… . ์„ ๋ฐ•์•ˆ์ „๋ฒ•์ƒ ๋Œ€ํ–‰๊ณผ ์œ ์‚ฌ๊ฐœ๋…๊ณผ์˜ ๊ตฌ๋ณ„ 213 โ…ก. ์„ ๋ฐ•์•ˆ์ „๋ฒ•์ƒ ๋Œ€ํ–‰๊ณผ ์ •๋ถ€์กฐ์ง๋ฒ•์ƒ ๋ฏผ๊ฐ„์œ„ํƒ์˜ ๊ทผ์ ‘์„ฑ 225 ์ œ3์ ˆ ์„ ๋ฐ•์•ˆ์ „๋ฒ•์ƒ ๋Œ€ํ–‰์ œ๋„์˜ ๋ฒ•์  ์„ฑ์งˆ 227 โ… . ์„ ๋ฐ•์•ˆ์ „๋ฒ•์ƒ ๋Œ€ํ–‰์ œ๋„์™€ ์„ ๋ฐ•๊ฒ€์‚ฌ๊ถŒ 227 โ…ก. ๋Œ€ํ–‰์ œ๋„์˜ ๋ฒ•์  ์„ฑ์งˆ์— ๊ด€ํ•œ ํ•ด์„๋ก  228 โ…ข. ํ•ด์„๋ก ์˜ ํ•œ๊ณ„์™€ ์ž…๋ฒ•๋ก ์˜ ํ•„์š”์„ฑ 232 ์ œ4์ ˆ ์„ ๋ฐ•๊ฒ€์‚ฌ ๋Œ€ํ–‰์ œ๋„์˜ ๋ฏผ๊ฐ„์œ„ํƒ์ œ๋„๋กœ์˜ ํŽธ์ž… 235 โ… . ์„ ๋ฐ•๊ฒ€์‚ฌ ๋Œ€ํ–‰์ œ๋„์™€ ๋ฏผ๊ฐ„์œ„ํƒ์ œ๋„์˜ ๋‚ด๋ถ€๊ด€๊ณ„ ์œ ์‚ฌ์„ฑ 235 โ…ก. ์„ ๋ฐ•๊ฒ€์‚ฌ ๋Œ€ํ–‰์ œ๋„์™€ ๋ฏผ๊ฐ„์œ„ํƒ์ œ๋„์˜ ์™ธ๋ถ€๊ด€๊ณ„ ์œ ์‚ฌ์„ฑ 237 ์ œ5์ ˆ ๊ตญ๊ฐ€์‚ฌ๋ฌด์˜์ œํ˜• ํŠน์ˆ˜ํ•œ ๋ฏผ๊ฐ„์œ„ํƒ์œผ๋กœ์˜ ์žฌ๊ตฌ์„ฑ 242 ์ œ6์žฅ ์„ ๋ฐ•๊ฒ€์‚ฌ ์œ„ํƒ์ œ๋„์˜ ๊ตญ์™ธ์  ๋ฒ•๋ฅ ๊ด€๊ณ„ ์ œ1์ ˆ ์œ ์—”ํ•ด์–‘๋ฒ•ํ˜‘์•ฝ๊ณผ ์ฃผ๊ถŒ๊ตญ๊ฐ€์˜ ๊ธฐ์ˆ ์  ๊ด€ํ• ๊ถŒ 245 โ… . UNCLOS์ƒ ๊ธฐ๊ตญ์ •๋ถ€์˜ ๊ธฐ์ˆ ์  ๊ด€ํ• ๊ถŒ 245 โ…ก. ์„ ๋ฐ•๊ฒ€์‚ฌ์˜ ๊ตญ์ œ ๊ทœ์น™ ๊ธฐ์†์„ฑ 246 โ…ข. ์ฃผ๊ถŒ๊ตญ๊ฐ€์˜ ๊ธฐ์ˆ ์  ๊ด€ํ• ๊ถŒ ํ–‰์‚ฌ์˜ ํ†ต๋กœ์™€ ์„ ๋ฐ•๊ฒ€์‚ฌ 247 ์ œ2์ ˆ EU๊ณตํ†ต๊ทœ์น™์ƒ ์„ ๊ธ‰๊ฒ€์‚ฌ ์ƒํ˜ธ์ธ์ • ๊ทœ์ •๊ณผ ๊ด€ํ• ๊ถŒ ์นจํ•ด์šฐ๋ ค 250 โ… . ๋ฌธ์ œ์˜ ์†Œ์žฌ 250 โ…ก. ๊ธฐ๊ตญ์ •๋ถ€์˜ ๊ธฐ์ˆ ์  ๊ด€ํ• ๊ถŒ ์ถฉ๋Œ์˜ ์ ‘์ ์œผ๋กœ์„œ์˜ ์„ ๊ธ‰๋ฒ•์ธ 251 โ…ข. EU ๊ณตํ†ต๊ทœ์น™์ƒ ํƒ€ ๊ตญ๊ฐ€ ๊ด€ํ• ๊ถŒ ์นจํ•ด ์šฐ๋ ค์กฐํ•ญ 253 ์ œ3์ ˆ ๋ฏธ๊ตญ ๋ฐ EU์˜ ์ด๋ž€์ œ์žฌ๋ฒ•๋ น๊ณผ ์„ ๊ธ‰๋ฒ•์ธ ํ™œ๋™์ œํ•œ 260 โ… . ๋ฏธ๊ตญ์˜ ์ด๋ž€์ œ์žฌ๋ฒ•๋ น๊ณผ ์„ ๊ธ‰๋ฒ•์ธ์˜ ๊ฒ€์‚ฌ์ œํ•œ 260 โ…ก. EU์˜ ์ด๋ž€์ œ์žฌ๋ฒ•๋ น๊ณผ ์„ ๊ธ‰๋ฒ•์ธ์˜ ๊ฒ€์‚ฌ์ œํ•œ 264 ์ œ4์ ˆ WTO/GATs์™€ ์ •๋ถ€์˜ ์„ ๋ฐ•๊ฒ€์‚ฌ์‚ฌ๋ฌด 265 โ… . ๋…ผ์˜์˜ ์‹ค์ต - ์„ ๋ฐ•๊ฒ€์‚ฌ์˜ ๋ณธ๋ž˜์  ์ •๋ถ€ ์‚ฌ๋ฌด์„ฑ 265 โ…ก. WTO/GATs ๊ทœ์ •์ƒ์˜ ์Ÿ์  266 โ…ข. ์œ„ํƒ๋œ ์„ ๋ฐ•๊ฒ€์‚ฌ์‚ฌ๋ฌด์— ๊ด€ํ•œ RO Code์˜ ์ž…์žฅ 268 ์ œ7์žฅ ๊ฒฐ ๋ก  ์ œ1์ ˆ ๋…ผ์˜์˜ ์ •๋ฆฌ 272 ์ œ2์ ˆ ์ž…๋ฒ•๋ก ์  ์ œ์–ธ 282 ์ฐธ๊ณ ๋ฌธํ—Œ 286Docto

    Analysis of relationships among genetic variations using single nucleotide polymorphisms in the gene regulatory re

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    ์˜๊ณผํ•™๊ณผ/๋ฐ•์‚ฌ[ํ•œ๊ธ€]์ธ๊ฐ„ ์œ ์ „์ฒด์—์„œ ๋ฐœ๊ฒฌ๋˜๋Š” ์—ผ๊ธฐ์„œ์—ด ๋ณ€์ด ์ค‘ ๋‹จ์ผ์—ผ๊ธฐ๋ณ€์ด(single nucleotide polymorphism, SNP) ๋ฅผ ์ด์šฉํ•˜์—ฌ ์ง„ํ–‰ํ•œ ๋งŽ์€ ์—ฐ๊ตฌ๋“ค์€ ๋Œ€๋ถ€๋ถ„ ๋™์ผ ์—ผ์ƒ‰์ฒด ๋‚ด์˜ ์œ ์ „์ž๋“ค๋งŒ์„ ๋Œ€์ƒ์œผ๋กœ ํ•˜๊ธฐ ๋•Œ๋ฌธ์— ์„œ๋กœ ๋‹ค๋ฅธ ์—ผ์ƒ‰์ฒด์— ๋ถ„ํฌํ•˜๊ณ  ์žˆ๋Š” ์œ ์ „์ž๋“ค๊ฐ„์˜ ์œ ์ „์ ์ธ ์—ฐ๊ด€ ๊ด€๊ณ„๋ฅผ ๋„คํŠธ์›Œํฌ ์ฐจ์›์—์„œ ํ•ด์„ํ•˜๊ธฐ ์–ด๋ ต๋‹ค๋Š” ๋‹จ์ ์ด ์žˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์ธ๊ฐ„์˜ ์ „์ฒด ์œ ์ „์ฒด๋ฅผ ๋Œ€์ƒ์œผ๋กœ, Pearsonโ€™s chi-square test ๋ฅผ ์ด์šฉํ•˜์—ฌ ์œ ์ „์ž์˜ ์ „์‚ฌ ์กฐ์ ˆ ํ›„๋ณด ์˜์—ญ์—์„œ ๋ฐœ๊ฒฌ๋˜๋Š” SNP genotype ๋“ค๊ฐ„์˜ ์—ฐ๊ด€ ๊ด€๊ณ„๋ฅผ ๋ถ„์„ํ•˜์˜€๋‹ค. ๋˜ํ•œ, SNP ๋“ค์„ ์ด์šฉํ•˜์—ฌ ์ถ”์ •๋œ haplotype(์ผ๋ฐฐ์ฒดํ˜•) ๋“ค๋กœ ๊ตฌ์„ฑํ•œ diplotype(์ด๋ฐฐ์ฒดํ˜•) ํŒจํ„ด์„ ์ด์šฉํ•˜์—ฌ ์œ ์ „์ž ์Œ ๊ฐ„์˜ ์—ฐ๊ด€ ๊ด€๊ณ„๋ฅผ ๋ถ„์„ํ•œ ํ›„ SNP genotype ๋“ค๊ฐ„, ๊ทธ๋ฆฌ๊ณ  haplotype ๋“ค๊ฐ„์— ๊ฐ•ํ•œ ์—ฐ๊ด€ ๊ด€๊ณ„๊ฐ€ ์žˆ๋Š” ์œ ์ „์ž๋“ค์„ ์ด์šฉํ•˜์—ฌ ์œ ์ „์ž ์—ฐ๊ด€ ๊ด€๊ณ„ ๋„คํŠธ์›Œํฌ๋ฅผ ๊ตฌ์ถ•ํ•˜์˜€๋‹ค. ์—ฐ๊ตฌ๋ฅผ ์œ„ํ•ด International HapMap ๋ฐ์ดํ„ฐ๋ฒ ์ด์Šค์—์„œ SNP genotype ์ž๋ฃŒ์™€ KEGG pathway ๋ฐ์ดํ„ฐ๋ฒ ์ด์Šค์—์„œ pathway ์ •๋ณด๋ฅผ ๊ฐ€์ ธ์™€ ์ด์šฉํ•˜์˜€๋‹ค. ๋ถ„์„ ๊ฒฐ๊ณผ, ๋™์ผ pathway ์˜ subtype ์„ ๊ตฌ์„ฑํ•˜๋Š” ์œ ์ „์ž๋“ค ๊ฐ„์—๋Š” ๋ฌด์ž‘์œ„ ์ถ”์ถœ ์œ ์ „์ž๋“ค์— ๋น„ํ•ด SNP genotype ๋“ค๊ฐ„, ๊ทธ๋ฆฌ๊ณ  haplotype ๋“ค๊ฐ„์— ์—ฐ๊ด€ ๊ด€๊ณ„๊ฐ€ ์žˆ์„ ํ™•๋ฅ ์ด ํ˜„์ €ํžˆ ๋†’์•˜์œผ๋ฉฐ, ์—ฐ๊ด€ ๊ด€๊ณ„๊ฐ€ ์žˆ๋Š” ์œ ์ „์ž๋“ค์„ ๋Œ€์ƒ์œผ๋กœ ์œ ์ „์ž ์—ฐ๊ด€ ๊ด€๊ณ„ ๋„คํŠธ์›Œํฌ๋ฅผ ๊ตฌ์ถ•ํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ๊ตฌ์ถ•ํ•œ ๋„คํŠธ์›Œํฌ์—์„œ๋Š” ์„œ๋กœ ๋‹ค๋ฅธ ์—ผ์ƒ‰์ฒด์— ์œ„์น˜ํ•ด ์žˆ๋Š” ๋‹ค์ˆ˜์˜ ์œ ์ „์ž๋“ค๊ณผ ์ง์ ‘์ ์ธ ์—ฐ๊ด€ ๊ด€๊ณ„๋ฅผ ๋งบ๊ณ  ์žˆ๋Š” ์ค‘์‹ฌ ์œ ์ „์ž๋“ค์„ ํ™•์ธํ•  ์ˆ˜ ์žˆ์—ˆ์œผ๋ฉฐ, ์ค‘์‹ฌ ์œ ์ „์ž ๋ฐ ์ค‘์‹ฌ ์œ ์ „์ž์™€ ์—ฐ๊ด€ ๊ด€๊ณ„๋ฅผ ๋งบ๊ณ  ์žˆ๋Š” ์œ ์ „์ž๋“ค์ด ๋‹ค์ˆ˜์˜ ์„œ๋กœ ๋‹ค๋ฅธ pathway ๋กœ ์—ฐ๊ฒฐ๋˜์–ด ์žˆ์Œ์„ ํ™•์ธํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ๋˜ํ•œ, RNA expression ๋ฐ์ดํ„ฐ ๋ถ„์„ ๊ฒฐ๊ณผ, ๋ฐœํ˜„ ์ƒ๊ด€ ๊ด€๊ณ„๋ฅผ ๊ฐ€์ง€๊ณ  ์žˆ๋Š” ์œ ์ „์ž๋“ค ์ผ๋ถ€๊ฐ€ ์œ ์ „์ž ์—ฐ๊ด€ ๊ด€๊ณ„ ๋„คํŠธ์›Œํฌ์—์„œ ์„œ๋กœ ์—ฐ๊ฒฐ๋˜์–ด ์žˆ์Œ์„ ํ™•์ธํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ๋”ฐ๋ผ์„œ, pathway ๋ฅผ ๊ตฌ์„ฑํ•˜๋Š” ์œ ์ „์ž๋“ค ์ค‘ ์„œ๋กœ ์ง์ ‘์ ์ธ ๋ฐ˜์‘ ๊ด€๊ณ„์— ์žˆ๋Š” ์œ ์ „์ž๋“ค์˜ ์ „์‚ฌ ์กฐ์ ˆ ํ›„๋ณด ์˜์—ญ ๋‚ด SNP genotype ๋ฐ haplotype ๋“ค์€ ๋ฌด์ž‘์œ„๋กœ ๋‚˜ํƒ€๋‚˜๋Š” ๊ฒƒ์ด ์•„๋‹ˆ๋ผ ์„œ๋กœ ์—ฐ๊ด€ ๋˜์–ด ์žˆ์Œ์„ ํ™•์ธ ํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ๋˜ํ•œ, SNP genotype ๋ฐ haplotype ์—ฐ๊ด€ ๊ด€๊ณ„๋ฅผ ๋งบ๊ณ  ์žˆ๋Š” ์œ ์ „์ž๋“ค์„ ์ด์šฉํ•˜์—ฌ ์œ ์ „์ž ์—ฐ๊ด€ ๊ด€๊ณ„ ๋„คํŠธ์›Œํฌ๋ฅผ ๊ตฌ์ถ•ํ•  ์ˆ˜ ์žˆ์œผ๋ฉฐ, ๋„คํŠธ์›Œํฌ ์ƒ์— ๋งคํ•‘๋œ pathway ์ •๋ณด์™€ ์œ ์ „์ž ์—ฐ๊ด€ ๊ด€๊ณ„๋ฅผ ์ ‘๋ชฉํ•˜๋ฉด ๋„คํŠธ์›Œํฌ๋ฅผ ๊ตฌ์„ฑํ•˜๋Š” ์ค‘์‹ฌ ์œ ์ „์ž ๋ฐ ์„œ๋กœ ๋‹ค๋ฅธ pathway ๋ฅผ ์—ฐ๊ฒฐ์‹œ์ผœ ์ฃผ๋Š” ์œ ์ „์ž๋“ค์„ ์ฐพ์„ ์ˆ˜ ์žˆ์Œ์„ ํ™•์ธํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. [์˜๋ฌธ]Many researches have been done to discover the genetic relationships among single nucleotide polymorphisms (SNPs) found on the human genes. However, there were common shortcomings to these studies for the network-based study because they have only focused on the several genes or nearby genetic loci on the same chromosome. Therefore, for comprehensive understanding of complex biology, it is required to take a genome-wide approach in addition to the gene-specific approach. To elucidate the genome-wide connectivity of genes based on the genetic variation, the relationships among genetic variations were investigated using SNPs and haplotypes found on the entire human genes. Also, for the integrated investigation of the connectivity of genes in regard to both the genetic variation and the pathway, the complex networks were constructed with the genes having relationship of genetic variation with other genes on the related pathways. To find out the relationships among genetic variations, SNPs and their genotypes were gotten from the International HapMap project database and pathway information from the KEGG database. SNPs were confined within 5000 base pairs of the upstream region of genes and this region was designated as the candidate location of gene regulatory region. Seven subtypes were redefined according to the chemical reactions or binary relations in the pathways. Pearsonโ€™s chi-square test was used to investigate whether there exist particular genotype relationships among SNPs. In addition to the genotype relationships, haplotype relationships were investigated using diplotype patterns. Using the genes of which SNP genotypes and haplotypes were both in statistically significant relationships, relationship networks of genetic variations were constructed, and the related pathways were investigated on the constructed networks. Finally, the expression patterns of RNA were investigated on the constructed networks using normal colon mucosal tissue and colon tumor tissue. As a result of the study, the probability that there are genotype relationships among SNPs and haplotype relationships among genes in the subtypes of the same pathway were remarkably higher than the relationships among randomly selected SNPs and genes. Relationship networks of genetic variations could be constructed using the genes that were in SNP genotype relationships and haplotype relationships. In the constructed networks, several key genes that were multiply connected with different genes located in different chromosomes were found, and a number of different pathways overlapped on the groups of the connected genes. And, some genes that had significantly correlated RNA expression level were found out to have SNP genotype and haplotype relationships in the constructed networks. Therefore, it was concluded that the SNPs and haplotypes found in the regulatory regions of the genes that are directly connected with other genes via chemical reactions or binary relations in the same pathway may not occur randomly. And, relationship network of genetic variations could be constructed and used for the integrated investigation of the connectivity of genes in regard to both the genetic variation and the pathway. Finally, it was suggested that the key genes and pathway-connecting genes could be found by mapping the pathway information to the relationship network of genetic variations.ope

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