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림 구동 일체형 추진장치의 유체역학적 특성에 관한 수치적 연구
정성문(Seongmun Jung),박정훈(Jeong-Hoon Park),최재엽(Jae-Yeop Choi),하성준(Sung-Jun Ha),권오준(Oh Joon Kwon) 한국전산유체공학회 2019 한국전산유체공학회지 Vol.24 No.1
In this paper, the hydrodynamic characteristics of a rim driven integrated thruster was numerically investigated. To consider the effect of cavitation phenomenon, multi-phase flow model and homogeneous mixture model were applied to the three dimensional incompressible RANS equations. To validate the numerical methods and the models adopted to the present study, the propeller P4381 was numerically analyzed and the numerical results and experimental one reached good agreement. The rim driven integrated thruster applied to the unmanned underwater vehicle at the water depth of 5m was numerically solved for various advance ratios. The flow field of the conventional thruster that has gap between the tip of the propeller and inner wall of the duct was also numerically solve and the results were compared to the results of the rim driven integrated thruster. As a result, it was revealed that both the rim driven integrated thruster and conventional thruster suffer from the cavitation phenomenon on the suction side of the propeller and the stator. It was also found that the difference of the thrust generated by the rim driven integrated thruster and conventional thruster is not significant whereas the difference of the torque could not be neglected. Finally, it was observed that the thrust and torque by thruster in the multi-phase flow was estimated to be smaller than those of single-phase flow.
Kim Su Yeon,Jeong Seongmun,Lee Wookjae,Jeon Yujin,Kim Yong-Jin,Park Seowoo,Lee Dongin,Go Dayoung,Song Sang-Hyun,Lee Sanghoo,Woo Hyun Goo,Yoon Jung-Ki,Park Young Sik,Kim Young Tae,Lee Se-Hoon,Kim Kwang 생화학분자생물학회 2023 Experimental and molecular medicine Vol.55 No.-
Cell-free DNA (cfDNA) sequencing has demonstrated great potential for early cancer detection. However, most large-scale studies have focused only on either targeted methylation sites or whole-genome sequencing, limiting comprehensive analysis that integrates both epigenetic and genetic signatures. In this study, we present a platform that enables simultaneous analysis of whole-genome methylation, copy number, and fragmentomic patterns of cfDNA in a single assay. Using a total of 950 plasma (361 healthy and 589 cancer) and 240 tissue samples, we demonstrate that a multifeature cancer signature ensemble (CSE) classifier integrating all features outperforms single-feature classifiers. At 95.2% specificity, the cancer detection sensitivity with methylation, copy number, and fragmentomic models was 77.2%, 61.4%, and 60.5%, respectively, but sensitivity was significantly increased to 88.9% with the CSE classifier (p value < 0.0001). For tissue of origin, the CSE classifier enhanced the accuracy beyond the methylation classifier, from 74.3% to 76.4%. Overall, this work proves the utility of a signature ensemble integrating epigenetic and genetic information for accurate cancer detection.
Controlling the false-discovery rate by procedures adapted to the length bias of RNA-Seq
Yang, Tae Young,Jeong, Seongmun The Korean Statistical Society,Korean Internationa 2018 Journal of the Korean Statistical Society Vol.47 No.1
In RNA-Seq experiments, the number of mapped reads for a given gene is proportional to its expression level and length. Because longer genes contribute more sequencible fragments than do shorter ones, it is expected that even if two genes have the same expression level, the longer gene will have a greater number of total reads. This characteristic creates a length bias such that the proportion of significant genes increases with the gene length. However, genes with a long length are not more biologically meaningful than genes with a short length. Therefore, the length bias should be properly corrected to determine the accurate list of significant genes in RNA-Seq. For this purpose, we proposed two multiple-testing procedures based on a weighted-FDR and a separate-FDR approach. These two methods use prior information on differential gene length while keeping the false-discovery rate (FDR) controlled at <TEX>${\alpha}$</TEX>. In the weighted-FDR controlling procedure, we incorporated prior weights for the length of each gene. These weights increase the power when the gene's length is short and decrease the power when its length is long. In the separate-FDR controlling procedure, we sequentially ordered all genes according to their lengths and then split these genes into two subgroups of short and long genes. The adaptive Benjamini-Hochberg procedure was then performed separately for each subgroup. The proposed procedures were compared with existing methods and evaluated in two numerical examples and one simulation study. We concluded that the weighted p-value procedure properly reduced the length bias of RNA-Seq.
Bioinformatics services for analyzing massive genomic datasets
Ko, Gunhwan,Kim, Pan-Gyu,Cho, Youngbum,Jeong, Seongmun,Kim, Jae-Yoon,Kim, Kyoung Hyoun,Lee, Ho-Yeon,Han, Jiyeon,Yu, Namhee,Ham, Seokjin,Jang, Insoon,Kang, Byunghee,Shin, Sunguk,Kim, Lian,Lee, Seung-Wo Korea Genome Organization 2020 Genomics & informatics Vol.18 No.1
The explosive growth of next-generation sequencing data has resulted in ultra-large-scale datasets and ensuing computational problems. In Korea, the amount of genomic data has been increasing rapidly in the recent years. Leveraging these big data requires researchers to use large-scale computational resources and analysis pipelines. A promising solution for addressing this computational challenge is cloud computing, where CPUs, memory, storage, and programs are accessible in the form of virtual machines. Here, we present a cloud computing-based system, Bio-Express, that provides user-friendly, cost-effective analysis of massive genomic datasets. Bio-Express is loaded with predefined multi-omics data analysis pipelines, which are divided into genome, transcriptome, epigenome, and metagenome pipelines. Users can employ predefined pipelines or create a new pipeline for analyzing their own omics data. We also developed several web-based services for facilitating downstream analysis of genome data. Bio-Express web service is freely available at https://www. bioexpress.re.kr/.