• 한국생물정보학회:학술대회논문집
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• 한국생물정보시스템생물학회 2000년도 International Symposium on Bioinformatics
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• pp.74-82
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• 2000

Prostate cancer initially responds and regresses in response to androgen depletion therapy, but most human prostate cancers will eventually recur, and re-grow as an androgen independent tumor. Once these tumors become hormone refractory, they usually are incurable leading to death for the patient. Little is known about the molecular details of how prostate cancer cells regress following androgen ablation and which genes are involved in the androgen independent growth following the development of resistance to therapy. Such knowledge would reveal putative drug targets useful in the rational therapeutic design to prevent therapy resistance and control androgen independent growth. The application of genome scale technologies have permitted new insights into the molecular mechanisms associated with these processes. Specifically, we have applied functional genomics using high density cDNA microarray analysis for parallel gene expression analysis of prostate cancer in an experimental xenograft system during androgen withdrawal therapy, and following therapy resistance, The large amount of expression data generated posed a formidable bioinformatics challenge. A novel template based gene clustering algorithm was developed and applied to the data to discover the genes that respond to androgen ablation. The data show restoration of expression of androgen dependent genes in the recurrent tumors and other signaling genes. Together, the discovered genes appear to be involved in prostate cancer cell growth and therapy resistance in this system. We have also developed and applied tissue microarray (TMA) technology for high throughput molecular analysis of hundreds to thousands of clinical specimens simultaneously. TMA analysis was used for rapid clinical translation of candidate genes discovered by cDNA microarray analysis to determine their clinical utility as diagnostic, prognostic, and therapeutic targets. Finally, we have developed a bioinformatic approach to combine pharmacogenomic data on the efficacy and specificity of various drugs to target the discovered prostate cancer growth associated candidate genes in an attempt to improve current therapeutics.

• 한국지능시스템학회논문지
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• 제22권6호
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• pp.786-792
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• 2012

마이크로어레이는 수만 가지 이상의 DNA 또는 RNA를 기판위에 배열해 놓은 것이며 이 기술을 이용하여 대량의 유전자 발현을 탐색할 수 있게 되었다. 그렇지만 마이크로어레이는 실험자가 탐색하려는 특정 표현형에 대해서 설계된 실험방법을 이용하므로 제한된 숫자의 유전자 발현만을 관찰할 수 있다. 본 논문에서는 MicroRNAs(miRNAs)와 Protein-Protein Interaction(PPI) 정보를 포함하고 있는 데이터베이스를 활용하여 마이크로어레이 데이터의 의미적 확장 방법을 제시하고자 한다. 또한 Online Mendelian Inheritance in Man(OMIM) 및 International Statistical Classification of Diseases and Related Health Problems, $10^{th}$ Revision(ICD-10)을 이용하여 질병 간 유전적 공통점 파악을 시도하였다. 이러한 접근방법을 통하여 새로운 생물학적 시각을 제공할 수 있을 것으로 기대된다.

• Genomics & Informatics
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• 제4권3호
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• pp.129-132
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• 2006

Toxicogenomics has recently emerged in the field of toxicology and the DNA microarray technique has become common strategy for predictive toxicology which studies molecular mechanism caused by exposure of chemical or environmental stress. Although microarray experiment offers extensive genomic information to the researchers, yet high dimensional characteristic of the data often makes it hard to extract meaningful result. Therefore we developed toxicant enrichment analysis similar to the common enrichment approach. We also developed web-based system graPT to enable considerable prediction of toxic endpoints of experimental chemical.

• 한국생물정보학회:학술대회논문집
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• 한국생물정보시스템생물학회 2001년도 제2회 생물정보 워크샵 (DNA Chip Bioinformatics)
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• pp.11-28
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• 2001

The Korean functional Genomics Project focuses on stomach and liver cancers. Specimens collected by six hospital teams are used in BNA microarray experiments. Experimental conditions, spot measurement data, and the associated clinical information are stored in a relational database. Microarray database schema was developed based on EBI's ArrayExpress. A diagrammatic representation of the schema is used to help navigate over marty tables in the database. Field description, table-to-table relationship, and other database features are also stored in the database and these are used by a PERL interface program to generate web-based input forms on the fly. As such, it is rather simple to modify the database definition and implement controlled vocabularies. This PERL program is a general-purpose utility which can be used for inputting and updating data in relational databases. It supports file upload and user-supplied filters of uploaded data. Joining related tables is implemented using JavaScripts, allowing this step to be deferred to a later stage. This feature alleviates the pain of inputting data into a multi-table database and promotes collaborative data input among several teams. Pathological finding, clinical laboratory parameters, demographical information, and environmental factors are also collected and stored in a separate database. The same PERL program facilitated developing this database and its user-interface.

• 한국유전체학회:학술대회논문집
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• 한국유전체학회 2003년도 The 12th Korea Genome Conference
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• pp.53.2-53.2
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• 2003

• 한국정보통신학회논문지
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• 제15권9호
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• pp.2032-2037
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• 2011

표지 유전자는 특정한 실험 조건의 특성을 나타내주는 발현수준의 유전자를 의미한다. 이 유전자들은 여러 집단간의 발현수준에서 유의한 차이를 보여주며, 실제로 집단 간의 차이를 유발하는 유전자일 확률이 높아 특정 생물학적 현상과 관련 있는 표지 유전자를 찾는 연구에 이용될 수 있다. 본 논문에서는, 먼저 그 동안 제안된 여러 표준화 방법들 중에서 가장 널리 사용되고 있는 방법들을 이용하여 데이터를 표준화 한 후 통계에 따라 유전자의 우선순위를 정함으로써 표지유전자를 추출할 수 있는 시스템을 제안하였다. 다층퍼셉트론 신경망 분류기를 이용하여 각 표준화 방법들의 성능을 비교분석하였다. 그 결과 Lowess 표준화 후 ANOVA를 이용하여 선택된 8개의 표지 유전자를 포함하는 마이크로어레이 데이터 셋에 MLP 알고리즘을 적용한 결과 99.32%의 가장 높은 분류 정확도와 가장 낮은 예측 에러 추정치를 나타내었다.

• 한국지능시스템학회논문지
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• 제18권4호
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• pp.471-475
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• 2008

생명과학분야에서 마이크로어레이 기술은 세포에서의 RNA 발현 프로파일을 관찰할 수 있도록 함으로써 생명현상의 규명 및 약물개발 등에서 분자수준의 생명현상에 대한 관찰과 분석이 가능해지고 있다. 마이크로어레이 데이터분석에서는 특정한 처리나 과정에서 현저한 특성을 보이는 유전자를 식별하기 위한 분석뿐만 아니라 유전자 전체인 게놈수준에서의 분석도 이루어진다. 약물반응 실험에서는 약물에 대한 게놈수준의 발현 프로파일을 관찰하는 것도 많은 정보를 제공할 수 있다. 약물실험에서는 대조군과 실험군들간에 관심있는 상대적인 발현특성을 갖는 유전자군을 전체적으로 추출하는 것이 필요한 경우가 있다. 예를 들면 정상군은 두개의 실험군에 대해서 중간정도의 발현정도를 갖는 유전자군을 식별하는 분석을 하는 경우, 생물학적인 데이터의 특성상 절대값을 비교하는 방법으로는 유용한 유전자들을 효과적으로 식별해 낼 수 없다. 이 논문에서는 정상군과 실험군들의 발현정도값의 경향을 판단하기 위해서 각 유전자에 대해서 집단별 대표값을 선정하여 퍼지집합으로 집단의 값의 범위를 결정하고, 이를 이용하여 특성 패턴을 갖는 유전자들을 식별해내는 방법을 제안하고, 실제 데이터를 통해서 실험한 결과를 보인다.

• Biotechnology and Bioprocess Engineering:BBE
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• 제10권5호
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• pp.432-443
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• 2005

Microarray technology has contributed Significantly to the understanding of bacterial genetics and transcriptional regulation. One neglected aspect of this technology has been optimization of microarray-generated signals and quality of generated information. Full genome microarrays were developed for Clostridium acetobutylicum through spotting of PCR products that were designed with minimal homology with all other genes within the genome. Using statistical analyses it is demonstrated that Signal quality is significantly improved by increasing the hybridization volume. possibly increasing the effective number of transcripts available to bind to a given spot, while changes in labeled probe amounts were found to be less sensitive to improving signal quality. In addition to Q-RT-PCR, array validation was tested by examining the transcriptional program of a mutant (M5) strain lacking the pSOL1 178-gene megaplasmid relative to the wildtype (WT) strain. Under optimal conditions, it is demonstrated that the fraction of false positive genes is 1% when considering differentially expressed genes and 7% when considering all genes with signal above background. To enhance genomic-scale understanding of organismal physiology, using data from these microarrays we estimated that $40{\sim}55%$ of the C. acetobutylicum genome is expressed at any time during batch culture, similar to estimates made for Bacillus subtilis.

• BMB Reports
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• 제41권9호
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• pp.670-677
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• 2008

A cDNA microarray composed of 2,028 different ESTs from two shrimp species, Penaeus monodon and Masupenaeus japonicus, was employed to identify yellow head virus (YHV)-responsive genes in hemocytes of P. monodon. A total of 105 differentially expressed genes were identified and grouped into five different clusters according to their expression patterns. One of these clusters, which comprised five genes including cathepsin L-like cysteine peptidase, hypothetical proteins and unknown genes, was of particular interest because the transcripts increased rapidly ($\leq$ 0.25 hours) and reached high expression levels in response to YHV injection. Microarray data were validated by realtime RT-PCR analyses of selected differentially expressed transcripts. In addition, comparative analysis of the hemocyte transcription levels of three of these genes between surviving and non-surviving shrimp revealed significantly higher expression levels in surviving shrimp.

• The Korean Journal of Physiology and Pharmacology
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• 제7권5호
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• pp.279-282
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• 2003

To investigate the effect of fluoxetine, one of selective serotonin reuptake inhibitors (SSRIs), on the immune system, human peripheral blood mononuclear cells (PBMC) were treated with fluoxetine $(10^{-7}\;M)$ for 24 h, and immune-related genes were analyzed by cDNA microarray. Expression of the immunerelated genes such as CD107b (LAMP-2), CD47 receptor (thrombospondin receptor), CD5 antigen-like (scavenger receptor cysteine rich family), copine III (CPNE3), interleukin (IL)-18 (interferon-gammainducing factor), integrin alpha 4 (CD49d), integrin alpha L subunit (CD11a), IL-3 receptor alpha subunit, L apoferritin, and small inducible cytokine subfamily A (Cys-Cys) member 13 (SCYA13) was induced by fluoxetine. This result suggests that fluoxetine may affect the immune system, and provides fundamental data for the involvement of SSRIs on immunoregulation.