scale genomic and postgenomic data means that many of the challenges in biomedical research are now challenges in computational sciences and information technology. The informatics revolutions both in clinical informatics and bioinformatics will change the current paradigm of biomedical sciences and practice of clinical medicine, including diagnostics, therapeutics, and prognostics. Postgenome informatics, powered by high throughput technologies and genomic-scale databases, is likely to transform our biomedical understanding forever much the same way that biochemistry did a generation ago. In this talk, 1 will describe how these technologies will in pact biomedical research and clinical care, emphasizing recent advances in biochip-based functional genomics. Basic data preprocessing with normalization and filtering, primary pattern analysis, and machine teaming algorithms will be presented. Issues of integrated biochip informatics technologies including multivariate data projection, gene-metabolic pathway mapping, automated biomolecular annotation, text mining of factual and literature databases, and integrated management of biomolecular databases will be discussed. Each step will be given with real examples from ongoing research activities in the context of clinical relevance. Issues of linking molecular genotype and clinical phenotype information will be discussed.

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.

DNA damage by physical insult including UV and g-radiation might provoke genetic alterations in cells, which is followed by either acute cell death or tumorigenesis. The responsiveness to g-radiation depends on cellular context of target cells. To understand the mechanisms of checkpoint control, repair and cell death following genotoxic stimu]i, cDNA microarray can provide the gene expression profile. To make a profile of gene expression in irradiated Jurkat T cells, we hybridized the cDNA microarray using cDNA from g-irradiated Jurkat T cells. Jurkat T cells were exposed to 4Gy to 16Gy, and total RNA were extracted at 4 to 24 hrs after irradiation. The hybridization of the microarray to fluorescence-labeled cDNA from treated and untreated cells was analyzed by bioinformatic analysis to address relative changes in expression levels of the genes present in the array. Responses varied widely in different time points, suggesting acute stress response and chronic restoration or cell death. From these results we could select 384 genes related to radiation response in Tcells, and radiation response might be different in various types of cells. Using Radchip, we could separate "the exposed" from control PBMCs. We propose that Radchip might be useful to check the radiation research as well as radiation carcinogenesis.

. Mediator of transcriptional regulation is the evolutionary conserved coactivator complex that plays He central role in the integration and recruitment of diverse regulatory signals and transcription machinery to certain promoters. In yeast, each Mediator subunit is required for transcriptional regulation of a distinct group of genes. In order to decipher the mechanistic roles of Mediator proteins in regulating developmental specific gene expression, we isolated, and analyzed a multiprotein complex containing Drosophila Mediate. homologs (dMediato.). dMediato. interacts with several sequence-sperific transcription factors and basal transcription machinery, and is critical for activated transcription in response to diverse transcriptional activators. In order to elucidate the function of Mediator in metazoan development, we isolated mutants of a conserved Mediate. subunit, Drosophila Med6 (dMed6). dMed6 null homozygotes failed to pupate and died in the third larval instar. Larval mitotic cells and most imaginal discs showed severe defects in proliferation, but no apparent morphological defect was observed in other larval tissues. Clonal analysis of dMed6 mutant cells revealed that dMed6 is essential for cell viability and proliferation of most adult cell types. Drosophila cDNA microarray, quantitative RT-PCR, and in situ expression analyses of developmentally regulated genes in dMed6 mutants showed that transcriptional activation of a subset of genes involved in neuroblast proliferation in the larval brain were most affected. Our results suggest that dMed6 is required in most for transcriptional regulation of a subset of genes important for cell proliferation and metabolism.

All cancers are caused by abnormalities in DNA sequence. Throughout life, the DNA in human cells is exposed to mutagens and suffers mistakes in replication, resulting in progressive, subtle changes in the DNA sequence in each cell. Since the development of conventional and molecular cytogenetic methods to the analysis of chromosomal aberrations in cancers, more than 1,800 recurring chromosomal breakpoints have been identified. These breakpoints and regions of nonrandom copy number changes typically point to the location of genes involved in cancer initiation and progression. With the introduction of molecular cytogenetic methodologies based on fluorescence in situ hybridization (FISH), namely, comparative genomic hybridization (CGH) and multicolor FISH (m-FISH) in carcinomas become susceptible to analysis. Conventional CGH has been widely applied for the detection of genomic imbalances in tumor cells, and used normal metaphase chromosomes as targets for the mapping of copy number changes. However, this limits the mapping of such imbalances to the resolution limit of metaphase chromosomes (usually 10 to 20 Mb). Efforts to increase this resolution have led to the "new"concept of genomic DNA chip (1 to 2 Mb), whereby the chromosomal target is replaced with cloned DNA immobilized on such as glass slides. The resulting resolution then depends on the size of the immobilized DNA fragments. We have completed the first draft of its Korean Genome Project. The project proceeded by end sequencing inserts from a library of 96,768 bacterial artificial chromosomes (BACs) containing genomic DNA fragments from Korean ethnicity. The sequenced BAC ends were then compared to the Human Genome Project′s publicly available sequence database and aligned according to known cancer gene sequences. These BAC clones were biotinylated by nick translation, hybridized to cytogenetic preparations of metaphase cells, and detected with fluorescein-conjugated avidin. Only locations of unique or low-copy Portions of the clone are identified, because high-copy interspersed repetitive sequences in the probe were suppressed by the addition of unlabelled Cotl DNA. Banding patterns were produced using DAPI. By this means, every BAC fragment has been matched to its appropriate chromosomal location. We have placed 86 (156 BAC clones) cytogenetically defined landmarks to help with the characterization of known cancer genes. Microarray techniques would be applied in CGH by replacement of metaphase chromosome to arrayed BAC confirming in oncogene and tumor suppressor gene: and an array BAC clones from the collection is used to perform a genome-wide scan for segmental aneuploidy by array-CGH. Therefore, the genomic DNA chip (arrayed BAC) will be undoubtedly provide accurate diagnosis of deletions, duplication, insertions and rearrangements of genomic material related to various human phenotypes, including neoplasias. And our tumor markers based on genetic abnormalities of cancer would be identified and contribute to the screening of the stage of cancers and/or hereditary diseases

삼성종합기술원에서는 인간의 genomic DNA의 이상을 발견하여 이와 연관된 질병을 진단하는 DNA chip을 개발하고 있다. 이를 위하여 특정한 염기서열의 변화에 따라 민감하게 hybridization strength가 변화하는 oligomer를 선택해야 한다. 따라서, specificity가 가장 큰 probe를 골라내야 한다. 여기에는 열역학적인 고려와 여러가지 물리화학적인 approximation이 사용되며, DNA chip 생산 공정에 의존하는 요소도 포함되어 있다 모든 생산용 data와 결과의 분석은 database를 기반으로 이루어지며, 자동화된 통계적 분석법과 최적화 방법이 함께 사용된다.

cDNA microarray technology allows the monitoring of expression levels for thousands of genes simultaneously. Many statistical analysis tools become widely applicable to the analysis of cDNA microarray data. In this talk, we consider a two-way ANOVA model to differentiate genes that have high variability and ones that do not. Using this model, we detect genes that have different gene expression profiles among experimental groups. The two-way ANOVA model is illustrated using cDNA microarrays of 3,800 genes obtained in an experiment to search for changes in gene expression profiles during neuronal differentiation of cortical stem cells.

cDNA Microarray 처리를 위한 시스템 개발에 관하여 개발시의 주요 착안점과 이전의 시스템에 비해서 개선된 몇 가지 기술에 대하여 본 연구팀의 실제적인 개발경험을 중심으로 설명한다. 렬 연구팀에서 만든 시스템의 기능은 이미지 처리부터 군집화(Clustering)에 이르는 전 과정을 통합적으로 처리될 수 있는데, 이 각 과정에 대하여 개략적으로 설명한다. 그리고 이 시스템을 활용하여 Macroarray라고 불릴 수 있는 새로운 형식의 array 실험장치에 어떻게 본 시스템이 적용되는지에 대하여도 설명을 한다.

- Overview of Bioinformatics and vision of Samsung SDS on it - Overview of Bio Chip and its market - Product roadmap with "Expert system for DNA chip data " - "UniBIO "as an integrated package of DNA chip data analysis - Demo of UniBIO

DNA chip 또는 microarray는 다수의 유전자 또는 유전자 조각을 (보통 수천내지 수만 개)칩상에 고정시켜 놓고 DNA hybridization 반응을 이용하여 유전자들의 발현 양상을 분석할 수 있는 기술이다. 이러한 high-throughput기술은 예전에는 생각하지 못했던 여러가지 분자생물학의 문제에 대한 해답을 제시해 줄 수 있을 뿐 만 아니라, 분자수준에서의 질병 진단, 신약 개발, 환경 오염 문제의 해결 등 그 응용 가능성이 무한하다. 이 기술의 실용적인 적용을 위해서는 DNA chip을 제작하기 위한 하드웨어/웻웨어 기술 외에도 이러한 데이터로부터 최대한 유용하고 새로운 지식을 창출하기 위한 bioinformatics 기술이 핵심이라고 할 수 있다. 유전자 발현 패턴을 데이터마이닝하는 문제는 크게 clustering, classification, dependency analysis로 구분할 수 있으며 이러한 기술은 통계학과인공지능 기계학습에 기반을 두고 있다. 주로 사용된 기법으로는 principal component analysis, hierarchical clustering, k-means, self-organizing maps, decision trees, multilayer perceptron neural networks, association rules 등이다. 본 세미나에서는 이러한 기본적인 기계학습 기술 외에 최근에 연구되고 있는 새로운 학습 기술로서 probabilistic graphical model (PGM)을 소개하고 이를 DNA chip 데이터 분석에 응용하는 연구를 살펴본다. PGM은 인공신경망, 그래프 이론, 확률 이론이 결합되어 형성된 기계학습 모델로서 인간 두뇌의 기억과 학습 기작에 기반을 두고 있으며 다른 기계학습 모델과의 큰 차이점 중의 하나는 generative model이라는 것이다. 즉 일단 모델이 만들어지면 이것으로부터 새로운 데이터를 생성할 수 있는 능력이 있어서, 만들어진 모델을 검증하고 이로부터 새로운 사실을 추론해 낼 수 있어 biological data mining 문제에서와 같이 새로운 지식을 발견하는 exploratory analysis에 적합하다. 또한probabilistic graphical model은 기존의 신경망 모델과는 달리 deterministic한의사결정이 아니라 확률에 기반한 soft inference를 하고 학습된 모델로부터 관련된 요인들간의 인과관계(causal relationship) 또는 상호의존관계(dependency)를 분석하기에 적합한 장점이 있다. 군체적인 PGM 모델의 예로서, Bayesian network, nonnegative matrix factorization (NMF), generative topographic mapping (GTM)의 구조와 학습 및 추론알고리즘을소개하고 이를 DNA칩 데이터 분석 평가 대회인 CAMDA-2000과 CAMDA-2001에서 사용된cancer diagnosis 문제와 gene-drug dependency analysis 문제에 적용한 결과를 살펴본다.