김광수 교수
Kwang Soo Kim
서울대학교 · 농업·생명과학
연구실 소개
김광수 교수의 연구실은 농업기후 및 병해충 예측 모델링을 핵심으로 하며, 특히 잎 습도 지속시간(LWD) 예측, 소이청피병 및 콩청피병의 병원균 전파 위험 평가에 초점을 맞추고 있습니다. 기계학습 기반의 분류 및 회귀 트리(CART), 퍼지 논리 시스템, 그리고 기상 데이터를 융합한 실시간 예측 모델을 개발하여 농업 생물학적 위험을 정량적으로 평가하고 있습니다. 또한 동물줄기세포를 이용한 신경세포 분화 및 이식 연구를 통해 파킨슨병 치료에 응용 가능한 세포 치료 전략도 함께 개발하고 있습니다.
연구 현황
연구 성과 추이
표시된 성과는 수집된 데이터 기준으로 산출되며, 일부 차이가 있을 수 있습니다.
주요 논문
15The ability of empirical models to enhance accuracy of site-specific estimates of leaf wetness duration (LWD) was assessed for 15 sites in Iowa, Nebraska, and Illinois during May to September of 1997, 1998, and 1999. Enhanced estimation of LWD was obtained by applying a 0.3-m height correction to SkyBit wind-speed estimates for input to the classification and regression tree/stepwise linear discriminant (CART/SLD) model (CART/SLD/Wind model), compared to either a proprietary model (SkyBit wetnes
Transplantation of mouse embryonic stem (mES) cells can restore function in Parkinson disease models, but can generate teratomas. Purification of dopamine neurons derived from embryonic stem cells by fluorescence-activated cell sorting (FACS) could provide a functional cell population for transplantation while eliminating the risk of teratoma formation. Here we used the tyrosine hydroxylase (TH) promoter to drive enhanced green fluorescent protein (eGFP) expression in mES cells. First, we evalua
Journal Article Rapid communication: linkage and physical mapping of the porcine melanocortin-4 receptor (MC4R) gene Get access K. S. Kim, K. S. Kim 4Department of Animal Science, Iowa State University, Ames 50011, USA Search for other works by this author on: Oxford Academic PubMed Google Scholar N. J. Larsen, N. J. Larsen 4Department of Animal Science, Iowa State University, Ames 50011, USA Search for other works by this author on: Oxford Academic PubMed Google Scholar M. F. Rothschild M. F. R
ABSTRACT Few biologically based models to assess the risk of soybean rust have been developed because of difficulty in estimating variables related to infection rate of the disease. A fuzzy logic system, however, can estimate apparent infection rate by combining meteorological variables and biological criteria pertinent to soybean rust severity. In this study, a fuzzy logic apparent infection rate (FLAIR) model was developed to simulate severity of soybean rust and validated using data from fiel
Empirical models based on classification and regression tree analysis (CART model) or fuzzy logic (FL model) were used to forecast leaf wetness duration (LWD) 24 h into the future, using site-specific weather data estimates as inputs. Forecasted LWD and air temperature then were used as inputs to simulate performance of the Melcast and TOM-CAST disease-warning systems. Overall, the CART and FL models underpredicted LWD with a mean error (ME) of 2.3 and 3.9 h day<sup>-1</sup>, respectively. The C
We propose a weighted ensemble approach using a surrogate variable. As a case study, the degree of agreement (DOA) statistics for potential evapotranspiration (PET) was determined to compare the ordinary arithmetic mean ensemble (OAME) method and the surrogate weighted mean ensemble (SWME) method for three domains. Solar radiation was used as the surrogate variable to determine the weight values for the ensemble members. Singular vector decomposition with truncation values was used to select fiv
The genus Jeffersonia, which contains only two species, has a trans-Atlantic disjunct distribution. The aims of this study were to determine the requirements for breaking dormancy and germination of J. dubia seeds and to compare its dormancy characteristics with those of the congener in eastern North America. Ripe seeds of J. dubia contain an underdeveloped embryo and were permeable to water. In nature, seeds were dispersed in May, while embryos began to grow in September, and were fully elongat
It has recently been shown that genomic integrity (with respect to copy number variants [CNVs]) is compromised in human induced pluripotent stem cells (iPSCs) generated by viral-based ectopic expression of specific transcription factors (e.g., Oct4, Sox2, Klf4, and c-Myc). However, it is unclear how different methods for iPSC generation compare with one another with respect to CNV formation. Because array-based methods remain the gold standard for detecting unbalanced structural variants (i.e.,
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