• 제목/요약/키워드: Objective clustering

검색결과 226건 처리시간 0.022초

Transcriptional Profiling of Differentially Expressed Genes in Porcine Satellite Cell

  • Jeong, Jin Young;Kim, Jang Mi;Rajesh, Ramanna Valmiki;Suresh, Sekar;Jang, Gul Won;Lee, Kyung-Tai;Kim, Tae Hun;Park, Mina;Jeong, Hak Jae;Kim, Kyung Woon;Cho, Yong Min;Lee, Hyun-Jeong
    • Reproductive and Developmental Biology
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    • 제37권4호
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    • pp.233-245
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    • 2013
  • Muscle satellite cell (SC) is responsible for postnatal muscle growth, repair, and regeneration. Satellite cell is an important source of multi-potent stem cell process and differentiation into adipogenic, myogenic, and osteoblastogenic. The objective of this study was to identify alter of transcriptome during differentiation in porcine satellite cell and to elevated transcriptome at different stages of postnatal development to gain insight into the differences in differentiated PSC. We used RNA-seq technique to investigate the transcriptomes during differentiation in pig muscle. Sequence reads were obtained from Illumina HiSeq2000. Differentially expressed genes (DEG) were detected by EdgeR. Gene ontology (GO) terms are powerful tool for unification among representation genes or products. In study of GO biological terms, functional annotation clustering involved in cell cycle, apoptosis, extracellular matrix, phosphorylation, proteolysis, and cell signaling in differences stage. Taken together, these results would be contributed to a better understanding of muscle biology and processes underlying differentiation. Our results suggest that the source of DEGs could be better understanding of the mechanism of muscle differentiation and transdifferentiation.

Water resources potential assessment of ungauged catchments in Lake Tana Basin, Ethiopia

  • Damtew, Getachew Tegegne;Kim, Young-Oh
    • 한국수자원학회:학술대회논문집
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    • 한국수자원학회 2015년도 학술발표회
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    • pp.217-217
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    • 2015
  • The objective of this study was mainly to evaluate the water resources potential of Lake Tana Basin (LTB) by using Soil and Water Assessment Tool (SWAT). From SWAT simulation of LTB, about 5236 km2 area of LTB is gauged watershed and the remaining 9878 km2 area is ungauged watershed. For calibration of model parameters, four gauged stations were considered namely: Gilgel Abay, Gummera, Rib, and Megech. The SWAT-CUP built-in techniques, particle swarm optimization (PSO) and generalized likelihood uncertainty estimation (GLUE) method was used for calibration of model parameters and PSO method were selected for the study based on its performance results in four gauging stations. However the level of sensitivity of flow parameters differ from catchment to catchment, the curve number (CN2) has been found the most sensitive parameters in all gauged catchments. To facilitate the transfer of data from gauged catchments to ungauged catchments, clustering of hydrologic response units (HRUs) were done based on physical similarity measured between gauged and ungauged catchment attributes. From SWAT land use/ soil use/slope reclassification of LTB, a total of 142 HRUs were identified and these HRUs are clustered in to 39 similar hydrologic groups. In order to transfer the optimized model parameters from gauged to ungauged catchments based on these clustered hydrologic groups, this study evaluates three parameter transfer schemes: parameters transfer based on homogeneous regions (PT-I), parameter transfer based on global averaging (PT-II), and parameter transfer by considering Gilgel Abay catchment as a representative catchment (PT-III) since its model performance values are better than the other three gauged catchments. The performance of these parameter transfer approach was evaluated based on values of Nash-Sutcliffe efficiency (NSE) and coefficient of determination (R2). The computed NSE values was found to be 0.71, 0.58, and 0.31 for PT-I, PT-II and PT-III respectively and the computed R2 values was found to be 0.93, 0.82, and 0.95 for PT-I, PT-II, and PT-III respectively. Based on the performance evaluation criteria, PT-I were selected for modelling ungauged catchments by transferring optimized model parameters from gauged catchment. From the model result, yearly average stream flow for all homogeneous regions was found 29.54 m3/s, 112.92 m3/s, and 130.10 m3/s for time period (1989 - 2005) for region-I, region-II, and region-III respectively.

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Comparison of genome-wide association and genomic prediction methods for milk production traits in Korean Holstein cattle

  • Lee, SeokHyun;Dang, ChangGwon;Choy, YunHo;Do, ChangHee;Cho, Kwanghyun;Kim, Jongjoo;Kim, Yousam;Lee, Jungjae
    • Asian-Australasian Journal of Animal Sciences
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    • 제32권7호
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    • pp.913-921
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    • 2019
  • Objective: The objectives of this study were to compare identified informative regions through two genome-wide association study (GWAS) approaches and determine the accuracy and bias of the direct genomic value (DGV) for milk production traits in Korean Holstein cattle, using two genomic prediction approaches: single-step genomic best linear unbiased prediction (ss-GBLUP) and Bayesian Bayes-B. Methods: Records on production traits such as adjusted 305-day milk (MY305), fat (FY305), and protein (PY305) yields were collected from 265,271 first parity cows. After quality control, 50,765 single-nucleotide polymorphic genotypes were available for analysis. In GWAS for ss-GBLUP (ssGWAS) and Bayes-B (BayesGWAS), the proportion of genetic variance for each 1-Mb genomic window was calculated and used to identify informative genomic regions. Accuracy of the DGV was estimated by a five-fold cross-validation with random clustering. As a measure of accuracy for DGV, we also assessed the correlation between DGV and deregressed-estimated breeding value (DEBV). The bias of DGV for each method was obtained by determining regression coefficients. Results: A total of nine and five significant windows (1 Mb) were identified for MY305 using ssGWAS and BayesGWAS, respectively. Using ssGWAS and BayesGWAS, we also detected multiple significant regions for FY305 (12 and 7) and PY305 (14 and 2), respectively. Both single-step DGV and Bayes DGV also showed somewhat moderate accuracy ranges for MY305 (0.32 to 0.34), FY305 (0.37 to 0.39), and PY305 (0.35 to 0.36) traits, respectively. The mean biases of DGVs determined using the single-step and Bayesian methods were $1.50{\pm}0.21$ and $1.18{\pm}0.26$ for MY305, $1.75{\pm}0.33$ and $1.14{\pm}0.20$ for FY305, and $1.59{\pm}0.20$ and $1.14{\pm}0.15$ for PY305, respectively. Conclusion: From the bias perspective, we believe that genomic selection based on the application of Bayesian approaches would be more suitable than application of ss-GBLUP in Korean Holstein populations.

한국 재래종 강낭콩 유전자원의 phytochemical 및 항산화 활성 평가 (Evaluation of Phytochemical econtents and antioxidant activity of Korean common bean (Phaseolus vulgaris L) landraces)

  • 이경준;신명재;조규택;이기안;마경호;정종욱;이정로
    • 한국국제농업개발학회지
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    • 제30권4호
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    • pp.357-369
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    • 2018
  • 1. 본 연구는 한국 재래종 강낭콩 209자원의 phytochemical 및 항산화활성을 평가하였다. 2. 항산화활성은 DPPH, ABTS, FRAP, SOD를 분석하였으며 phytochemical은 kaempferol, myricetin, quercetin, naringenin 함량을 각각 분석하였다. 3. 항산화활성은 강낭콩 자원 간 다양한 분포를 보였으며 DPPH의 경우 62.3~643.9 (IC50), ABTS의 경우 0.28~1.49 mgAAE/g, FRAP의 경우 0.41~5.44 mgAAE/g, SOD의 경우 50.4 ~ 299.8 (IC50)로 나타났다. 4. Relative antioxidant capacity index (RACI)로 강낭콩 자원의 항산화활성을 비교한 결과 IT104587이 가장 높은 항산화활성을 보였으며 IT189598이 가장 낮은 항산화활성을 보였다. 5. 분석된 Phytochemical 중에서 한국 재래종 강낭콩에서는 Kaempferol이 가장 높은 함량을 나타냈다. 6. PCA 분석 결과 209자원은 3개의 그룹으로 나뉘었으며 이중 그룹 III에 속한 46자원의 강낭콩이 낮은 항산화활성 및 phytochemical 함량을 보였다. 7. 본 연구 결과는 한국 재래종 강낭콩의 항산화활성 및 phytochemical 정보를 제공하며 이 정보는 강낭콩 품종 개발을 위한 기초 정보로 사용될 수 있을 것이다.

신제품 개발을 위한 데이터 기반 공동 디자인 프로세스: 스마트 난방복 사례 연구 (Data-driven Co-Design Process for New Product Development: A Case Study on Smart Heating Jacket)

  • 임수연;이상원
    • 한국융합학회논문지
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    • 제12권1호
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    • pp.133-141
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    • 2021
  • 본 연구는 객관적인 데이터 기반 방법을 통해 인간 중심 디자인 과정을 효과적으로 보완하는 디자인 프로세스를 제시한다. 즉, 주관적 방법에 의한 인간 중심 디자인 프로세스에서 결여되는 객관성이 데이터 기반 접근에 의해 보완되어 숨겨진 사용자의 니즈를 효과적으로 발견하는 프로세스로 발전될 수 있다. 이에 본 연구에서는 설문조사 데이터 마이닝 분석 과정과 공동 디자인 프로세스가 접목된 인간 중심 디자인 프로세스를 제시하며, 스마트 난방복 사례연구를 통해 이를 검증한다. 설문조사 데이터 마이닝 분석 과정에서는 클러스터링과 의사결정 나무의 두 가지 분석 방법이 사용된다. 클러스터링은 타겟 그룹을 선정하는 기준이 되는 페르소나의 초안을 제시하며, 의사결정 나무는 제품 구매에 중요한 사용자 인식 속성 파악과 사용자 가치 체계를 일차적으로 제안한다. 이후 데이터 분석을 통해 얻어진 광범위한 관점에 대하여 타겟 그룹을 대표하는 사용자가 직접 참여하는 공동 디자인 프로세스가 수행되며 맞춤형 워크북을 이용하여 신제품에 대한 사용자의 여정맵, 니즈, 아이디어, 가치 체계 등을 체계적으로 도출한다. 본 논문에서 수행한 스마트 난방복 사례 연구는 제안된 방법론의 적용성을 보여주고 있다.

Tumor Habitat Analysis Using Longitudinal Physiological MRI to Predict Tumor Recurrence After Stereotactic Radiosurgery for Brain Metastasis

  • Da Hyun Lee;Ji Eun Park;NakYoung Kim;Seo Young Park;Young-Hoon Kim;Young Hyun Cho;Jeong Hoon Kim;Ho Sung Kim
    • Korean Journal of Radiology
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    • 제24권3호
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    • pp.235-246
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    • 2023
  • Objective: It is difficult to predict the treatment response of tissue after stereotactic radiosurgery (SRS) because radiation necrosis (RN) and tumor recurrence can coexist. Our study aimed to predict tumor recurrence, including the recurrence site, after SRS of brain metastasis by performing a longitudinal tumor habitat analysis. Materials and Methods: Two consecutive multiparametric MRI examinations were performed for 83 adults (mean age, 59.0 years; range, 27-82 years; 44 male and 39 female) with 103 SRS-treated brain metastases. Tumor habitats based on contrast-enhanced T1- and T2-weighted images (structural habitats) and those based on the apparent diffusion coefficient (ADC) and cerebral blood volume (CBV) images (physiological habitats) were defined using k-means voxel-wise clustering. The reference standard was based on the pathology or Response Assessment in Neuro-Oncologycriteria for brain metastases (RANO-BM). The association between parameters of single-time or longitudinal tumor habitat and the time to recurrence and the site of recurrence were evaluated using the Cox proportional hazards regression analysis and Dice similarity coefficient, respectively. Results: The mean interval between the two MRI examinations was 99 days. The longitudinal analysis showed that an increase in the hypovascular cellular habitat (low ADC and low CBV) was associated with the risk of recurrence (hazard ratio [HR], 2.68; 95% confidence interval [CI], 1.46-4.91; P = 0.001). During the single-time analysis, a solid low-enhancing habitat (low T2 and low contrast-enhanced T1 signal) was associated with the risk of recurrence (HR, 1.54; 95% CI, 1.01-2.35; P = 0.045). A hypovascular cellular habitat was indicative of the future recurrence site (Dice similarity coefficient = 0.423). Conclusion: After SRS of brain metastases, an increased hypovascular cellular habitat observed using a longitudinal MRI analysis was associated with the risk of recurrence (i.e., treatment resistance) and was indicative of recurrence site. A tumor habitat analysis may help guide future treatments for patients with brain metastases.

Association between High Diffusion-Weighted Imaging-Derived Functional Tumor Burden of Peritoneal Carcinomatosis and Overall Survival in Patients with Advanced Ovarian Carcinoma

  • He An;Jose AU Perucho;Keith WH Chiu;Edward S Hui;Mandy MY Chu;Siew Fei Ngu;Hextan YS Ngan;Elaine YP Lee
    • Korean Journal of Radiology
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    • 제23권5호
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    • pp.539-547
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    • 2022
  • Objective: To investigate the association between functional tumor burden of peritoneal carcinomatosis (PC) derived from diffusion-weighted imaging (DWI) and overall survival in patients with advanced ovarian carcinoma (OC). Materials and Methods: This prospective study was approved by the local research ethics committee, and informed consent was obtained. Fifty patients (mean age ± standard deviation, 57 ± 12 years) with stage III-IV OC scheduled for primary or interval debulking surgery (IDS) were recruited between June 2016 and December 2021. DWI (b values: 0, 400, and 800 s/mm2) was acquired with a 16-channel phased-array torso coil. The functional PC burden on DWI was derived based on K-means clustering to discard fat, air, and normal tissue. A score similar to the surgical peritoneal cancer index was assigned to each abdominopelvic region, with additional scores assigned to the involvement of critical sites, denoted as the functional peritoneal cancer index (fPCI). The apparent diffusion coefficient (ADC) of the largest lesion was calculated. Patients were dichotomized by immediate surgical outcome into high- and low-risk groups (with and without residual disease, respectively) with subsequent survival analysis using the Kaplan-Meier curve and log-rank test. Multivariable Cox proportional hazards regression was used to evaluate the association between DWI-derived results and overall survival. Results: Fifteen (30.0%) patients underwent primary debulking surgery, and 35 (70.0%) patients received neoadjuvant chemotherapy followed by IDS. Complete tumor debulking was achieved in 32 patients. Patients with residual disease after debulking surgery had reduced overall survival (p = 0.043). The fPCI/ADC was negatively associated with overall survival when accounted for clinicopathological information with a hazard ratio of 1.254 for high fPCI/ADC (95% confidence interval, 1.007-1.560; p = 0.043). Conclusion: A high DWI-derived functional tumor burden was associated with decreased overall survival in patients with advanced OC.

Improving the Performance of Radiologists Using Artificial Intelligence-Based Detection Support Software for Mammography: A Multi-Reader Study

  • Jeong Hoon Lee;Ki Hwan Kim;Eun Hye Lee;Jong Seok Ahn;Jung Kyu Ryu;Young Mi Park;Gi Won Shin;Young Joong Kim;Hye Young Choi
    • Korean Journal of Radiology
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    • 제23권5호
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    • pp.505-516
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    • 2022
  • Objective: To evaluate whether artificial intelligence (AI) for detecting breast cancer on mammography can improve the performance and time efficiency of radiologists reading mammograms. Materials and Methods: A commercial deep learning-based software for mammography was validated using external data collected from 200 patients, 100 each with and without breast cancer (40 with benign lesions and 60 without lesions) from one hospital. Ten readers, including five breast specialist radiologists (BSRs) and five general radiologists (GRs), assessed all mammography images using a seven-point scale to rate the likelihood of malignancy in two sessions, with and without the aid of the AI-based software, and the reading time was automatically recorded using a web-based reporting system. Two reading sessions were conducted with a two-month washout period in between. Differences in the area under the receiver operating characteristic curve (AUROC), sensitivity, specificity, and reading time between reading with and without AI were analyzed, accounting for data clustering by readers when indicated. Results: The AUROC of the AI alone, BSR (average across five readers), and GR (average across five readers) groups was 0.915 (95% confidence interval, 0.876-0.954), 0.813 (0.756-0.870), and 0.684 (0.616-0.752), respectively. With AI assistance, the AUROC significantly increased to 0.884 (0.840-0.928) and 0.833 (0.779-0.887) in the BSR and GR groups, respectively (p = 0.007 and p < 0.001, respectively). Sensitivity was improved by AI assistance in both groups (74.6% vs. 88.6% in BSR, p < 0.001; 52.1% vs. 79.4% in GR, p < 0.001), but the specificity did not differ significantly (66.6% vs. 66.4% in BSR, p = 0.238; 70.8% vs. 70.0% in GR, p = 0.689). The average reading time pooled across readers was significantly decreased by AI assistance for BSRs (82.73 vs. 73.04 seconds, p < 0.001) but increased in GRs (35.44 vs. 42.52 seconds, p < 0.001). Conclusion: AI-based software improved the performance of radiologists regardless of their experience and affected the reading time.

텍스트 마이닝 기반의 이슈 관련 R&D 키워드 패키징 방법론 (Methodology for Issue-related R&D Keywords Packaging Using Text Mining)

  • 현윤진;윌리엄;김남규
    • 인터넷정보학회논문지
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    • 제16권2호
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    • pp.57-66
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    • 2015
  • 빅데이터 기술에 대한 관심이 급증함에 따라, 소셜 미디어를 통해 유통되는 방대한 양의 비정형 데이터를 분석하고자 하는 시도가 활발히 이루어지고 있다. 이에 따라서 텍스트 형태의 비정형 데이터 분석을 통해 의미 있는 정보를 찾고자 하는 시도가 비즈니스 영역뿐 아니라, 정치, 경제, 문화 등 다양한 영역에서 이루어지고 있다. 특히 최근에는 여러 현안 및 이슈들을 발굴하여 이를 의사결정에 활용하고자 하는 시도가 활발히 이루어지고 있다. 이처럼 빅데이터 분석을 통해 국가현안이나 이슈를 발굴하고자 하는 시도가 꾸준히 이루어져왔음에도 불구하고, 국가현안 및 이슈로부터 이와 관련된 R&D 문서를 효율적으로 제공하는 방안은 마련되지 않고있다. 이는 사용자들이 인식하는 현안 키워드와 실제 사용되는 R&D 키워드 사이의 이질성이 존재하기 때문이다. 따라서 현안 및 R&D키워드간의 이질성을 극복하기 위한 중간 장치가 필요하며, 이 중간 장치를 통해 각 현안 키워드와 R&D 키워드간에 적절한 대응이 이루어져야 한다. 이를 위해 본 연구에서는 (1) 현안 키워드 추출을 위한 하이브리드 방법론, (2) 현안 대응 R&D 정보 패키징 방법론, 그리고 (3) R&D 관점에서의 연관 현안 네트워크 구축 방법론의 총 세 가지 방법론을 제안한다. 제안하는 방법론은 텍스트 마이닝, 소셜네트워크 분석, 그리고 연관 규칙 마이닝 등의 데이터 분석 기법들을 활용하여 수행하였으며, 그 결과, (1)에 의한 키워드 보강률은 42.8%로 나타났으며, (2)의 경우, 현안 키워드와 R&D 키워드간 다수의 연관 규칙이 나타났다. (3)의 경우는 현재 진행 중에 있으며, 향후 가시적 성과를 낼 수 있을 것으로 예상된다.

전라남도 무안만에 도래하는 수조류의 서식지 이용 및 갯벌등급 평가 (A Study on the Habitat Use of Waterbirds and Grading Assessment of the Tidal Flat at Muan Bay in Jeollanamdo, Korea)

  • 강태한;유승화;이시완;최옥인;이종빈
    • 한국환경생태학회지
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    • 제22권5호
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    • pp.521-529
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    • 2008
  • 전라남도에 위치한 무안만 연안습지를 4개 영역(동암, 구로, 복룡 및 완산 갯벌)의 갯벌로 구분하여 수조류의 서식지 이용, 갯벌의 가치 및 등급평가를 위해 2007년 2월부터 10월까지 계절별로 4회에 걸쳐 이 지역에 도래하는 수조류를 조사하였다. 논병아리류 2종, 백로류 7종, 수면성 오리류 7종, 잠수성 오리류 6종, 섭금류 20종, 갈매기 3종 및 기타 9종 등을 포함하여 54종 15,755개체의 수조류가 관찰되었으며, 9,291개체가 관찰된 섭금류가 우점 분류군으로 나타났다. 이들 분류군에서 갈매기류와 섭금류는 동암갯벌을 이용하는 비율이 높았으며, 구로갯벌을 이용하는 분류군은 주로 수면성 및 잠수성 오리류와 논병아리류로 나타났다. 종과 개체수를 고려한 UPGMA 군집분석 결과, 동암갯벌과 복룡갯벌이 밀접한 유사성을 보였으며 구로갯벌과 왕산갯벌이 유사하게 나타났다. 수조류의 다양도지수, 풍부도지수, 우점도지수 등의 생태적 지수, 법적보호종 및 최대 개체수 등을 기준으로 해서 갯벌등급을 살펴보았을 때, 복룡갯벌의 가치 및 중요도 순위가 다른 3개 갯벌보다 높게 나타났다. 이와 같이 수조류에 의한 갯벌 등급화는 중요한 갯벌지역의 판단 및 지정, 그에 따른 효율적인 보전과 관리에 있어서 객관적인 자료를 제시할 순 있을 것으로 판단된다.