• 산업기술연구
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• 제42권1호
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• pp.29-36
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• 2022

The CRISPR system has revolutionized gene editing field. Cas9-mediated gene editing such as Indel induction or HDR enable targeted gene disruption or precise correction of mutation. Moreover, CRISPR-based new editing tools have been developed such as base editors. In this review, we focus on gene editing in human pluripotent stem cells, which is principal technique for gene correction therapy and disease modeling. Pluripotent stem cell-specific drug YM155 enabled selection of target gene-edited pluripotent stem cells. Also, we discussed base editing for treatment of congenital retina disease. Adenine base editor delivery as RNP form provide an approach for genetic disease treatment with safe and precise in vivo gene correction.

• Interdisciplinary Bio Central
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• 제3권2호
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• pp.8.1-8.6
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• 2011

Background: Thanks to the development of the mathematical/statistical reverse engineering and the high-throughput measuring biotechnology, lots of biologically meaningful genegene interaction networks have been revealed. Steady-state analysis of these systems provides an important clue to understand and to predict the systematic behaviours of the biological system. However, modeling such a complex and large-scale system is one of the challenging difficulties in systems biology. Results: We introduce a new stochastic modeling approach that can describe gene regulatory mechanisms by dividing two (DNA and protein) layers. Simple queuing system is employed to explain the DNA layer and the protein layer is modeled using G-networks which enable us to account for the post-translational protein interactions. Our method is applied to a transcription repression system and an active protein degradation system. The steady-state results suggest that the active protein degradation system is more sensitive but the transcription repression system might be more reliable than the transcription repression system. Conclusions: Our two layer stochastic model successfully describes the long-run behaviour of gene regulatory networks which consist of various mRNA/protein processes. The analytic solution of the G-networks enables us to extend our model to a large-scale system. A more reliable modeling approach could be achieved by cooperating with a real experimental study in synthetic biology.

• 한국생물정보학회:학술대회논문집
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• 한국생물정보시스템생물학회 2005년도 BIOINFO 2005
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• pp.191-196
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• 2005

Genetic networks are a key to unraveling dynamic properties of biological processes and regulation of genes plays an essential role in dynamic behavior of the genetic networks. A popular characterization of regulation of the gene is a kinetic model. However, many kinetic parameters in the genetic regulation have not been available. To overcome this difficulty, in this report, state-space approach to modeling gene regulation is presented. Second-order systems are used to characterize gene regulation. Interpretation of coefficients in the second order systems as resistance, capacitance and inductance is studied. The mathematical methods for transient response analysis of gene regulation to external perturbation are investigated. Criterion for classifying gene into three categories: underdamped, overdamped and critical damped is discussed. The proposed models are applied to yeast cell cycle gene expression data.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2019년도 춘계학술대회
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• pp.265-267
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• 2019

이 논문에서는 유전자 알고리즘을 이용하여 기존 이미지와 유사한 흑백 이미지를 자동으로 생성하는 기법을 제안한다. 유전자 알고리즘을 현실 문제에 적용하기 위해 가장 중요한 설계 요소인 유전자 모델링을 어떻게 할 것인지에 대하여 2가지 기법을 제안하였다. 제안한 각 기법을 이용하여 2가지 크기의 흑백 영상으로 실험을 진행하였다. 실험 결과, 이미지 생성을 위한 유전자 모델링에 있어서 각 기법의 진화 성능에 큰 차이가 있음을 확인하였다. 따라서 향후 기존 이미지와 유사한 이미지를 생성하거나, 서로 다른 이미지를 합성한 이미지를 생성하기 위해 빠르고 자연스럽게 학습시키기 위해서는 유전자 모델링을 신중하게 결정해야 함을 파악할 수 있다.

• 한국생물정보학회:학술대회논문집
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• 한국생물정보시스템생물학회 2003년도 제2차 연례학술대회 발표논문집
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• pp.147-154
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• 2003

Microarray information system is a complex system to manage, analyze and interpretate microarray gene expression data. Establishment of well-defined development process is very essential for understanding the complexity and organization of the system. We performed object-oriented analysis using Unified Modeling Language (UML) in specifying, visualizing and documenting microarray information system. The object-oriented analysis consists of three major steps: (i) use case modeling to describe various functionalities from the user's perspective (ii) dynamic modeling to illustrate behavioral aspects of the system (iii) object modeling to represent structural aspects of the system. As a result of our modeling activities we provide the UML diagrams showing various views of the microarray information system. We believe that the object-oriented analysis ensures effective documentations and communication of information system requirements. Another useful feature of object-oriented technique is structural continuity to standard microarray data model MAGE-OM (Microarray Gene Expression Object Model). The proposed modeling e(forts can be applicable for integration of biomedical information system.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2004년도 춘계학술대회 학술발표 논문집 제14권 제1호
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• pp.273-276
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• 2004

Genome-scale expression data provides us with valuable insights about organisms, but the biological validation of in-silico analysis is difficult and often controversial. Here we present a new approach for integrating previously established knowledge with computational analysis. Based on the known biological evidences, IGAM (Integrated Gene Association Matrix) automatically estimates the relatedness between a pair of genes. We combined this association knowledge to the regulatory network modeling and fuzzy clustering in yeast 5. Cerevisiae. The result was found to be more effective for extracting biological meanings from in-silico inferences for gene expression data.

• Molecular & Cellular Toxicology
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• 제1권4호
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• pp.281-283
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• 2005

Extraction of biologically meaningful data and their validation are very important for toxicogenomics study because it deals with huge amount of heterogeneous data. BINGO is an annotation mining tool for biological interpretation of gene groups. Several statistical modeling approaches using Gene Ontology (GO) have been employed in many programs for that purpose. The statistical methodologies are useful in investigating the most significant GO attributes in a gene group, but the coherence of the resultant GO attributes over the entire group is rarely assessed. BINGO complements the statistical methods with graph-theoretic measures using the GO directed acyclic graph (DAG) structure. In addition, BINGO visualizes the consistency of a gene group more intuitively with a group-based GO subgraph. The input group can be any interesting list of genes or gene products regardless of its generation process if the group is built under a functional congruency hypothesis such as gene clusters from DNA microarray analysis.

• Genomics & Informatics
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• 제12권1호
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• pp.35-41
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• 2014

Single-nucleotide polymorphisms (SNPs) have been emerging out of the efforts to research human diseases and ethnic disparities. A semantic network is needed for in-depth understanding of the impacts of SNPs, because phenotypes are modulated by complex networks, including biochemical and physiological pathways. We identified ethnicity-specific SNPs by eliminating overlapped SNPs from HapMap samples, and the ethnicity-specific SNPs were mapped to the UCSC RefGene lists. Ethnicity-specific genes were identified as follows: 22 genes in the USA (CEU) individuals, 25 genes in the Japanese (JPT) individuals, and 332 genes in the African (YRI) individuals. To analyze the biologically functional implications for ethnicity-specific SNPs, we focused on constructing a semantic network model. Entities for the network represented by "Gene," "Pathway," "Disease," "Chemical," "Drug," "ClinicalTrials," "SNP," and relationships between entity-entity were obtained through curation. Our semantic modeling for ethnicity-specific SNPs showed interesting results in the three categories, including three diseases ("AIDS-associated nephropathy," "Hypertension," and "Pelvic infection"), one drug ("Methylphenidate"), and five pathways ("Hemostasis," "Systemic lupus erythematosus," "Prostate cancer," "Hepatitis C virus," and "Rheumatoid arthritis"). We found ethnicity-specific genes using the semantic modeling, and the majority of our findings was consistent with the previous studies - that an understanding of genetic variability explained ethnicity-specific disparities.

• 한국정보통신학회논문지
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• 제23권8호
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• pp.896-902
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• 2019

본 논문에서는 유전자 알고리즘을 이용하여 기존 영상과 유사한 영상을 자동으로 생성하는 두 가지 방법을 제안하였다. 실험은 각각의 제안된 방법을 사용하여 두 가지 크기 ($256{\times}256$, $512{\times}512$)의 흑백 영상과 컬러 영상에서 수행되었다. 실험 결과, 전체 영상을 분할된 서브 영상으로 구분하여 모델링한 후 진화하는 기법이 전체 영상을 단일 유전자로 모델링하여 진화한다는 것보다 훨씬 정교하고 진화 속도도 빠르다는 것을 확인할 수 있었다. 따라서 향후 기존 영상과 유사한 영상을 생성하거나 다른 영상으로부터 합성된 영상을 신속하고 자연스럽게 학습하기 위해서는 영상을 분할하여 유전자를 모델링 하는 기법을 이용하여 유전자 모델링, 선택, 교차, 돌연변이 기법 등을 신중하게 결정해야 할 필요가 있다.

• 한국생물정보학회:학술대회논문집
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• 한국생물정보시스템생물학회 2005년도 BIOINFO 2005
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• pp.427-430
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• 2005

Studies on cellular pathways and networks are now one of the most actively researched topics in all fields of biomedicine ranging from developmental biology to etiology. Many databases have been developed and quantitative simulation models have been proposed. One of the eventual goals of pathway/network studies is to integrate different types of pathway/network models and databases to simulate overall cellular responses. A bottleneck to this goal is modeling gene expression since the mechanism of this process is not yet fully unveiled. We are developing a small scale computer program called CiRMU (Cis-Regulatory Machinery Unit model) for describing, viewing, analyzing, and modeling the process of gene expression. A prototype system is being designed and implemented for analyzing functions of nuclear receptors.