• Genomics & Informatics
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• v.11 no.4
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• pp.174-179
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• 2013

The large amount of data on cancer genome research has contributed to our understanding of cancer biology. Indeed, the genomics approach has a strong advantage for analyzing multi-factorial and complicated problems, such as cancer. It is time to think about the actual usage of cancer genomics in the clinical field. The clinical cancer field has lots of unmet needs in the management of cancer patients, which has been defined in the pre-genomic era. Unmet clinical needs are not well known to bioinformaticians and even non-clinician cancer scientists. A personalized approach in the clinical field will bring potential additional challenges to cancer genomics, because most data to now have been population-based rather than individualbased. We can maximize the use of cancer genomics in the clinical field if cancer scientists, bioinformaticians, and clinicians think and work together in solving unmet clinical needs. In this review, we present one imaginary case of a cancer patient, with which we can think about unmet clinical needs to solve with cancer genomics in the diagnosis, prediction of prognosis, monitoring the status of cancer, and personalized treatment decision.

• Proceedings of the Korean Society of Potoscience Conference
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• 2002.06a
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• pp.41-41
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• 2002

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2000.11a
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• pp.45-52
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• 2000

Genomic approach produces massive amount of data within a short time period, New high-throughput automatic sequencers can generate over a million nucleotide sequence information overnight. A typical DNA chip experiment produces tens of thousands expression information, not to mention the tens of megabyte image files, These data must be handled automatically by computer and stored in electronic database, Thus there is a need for systematic approach of data collection, processing, and analysis. DNA sequence information is translated into amino acid sequence and is analyzed for key motif related to its biological and/or biochemical function. Functional genomics will play a significant role in identifying novel drug targets and diagnostic markers for serious diseases. As an enabling technology for functional genomics, bioinformatics is in great need worldwide, In Korea, a new functional genomics project has been recently launched and it focuses on identi☞ing genes associated with cancers prevalent in Korea, namely gastric and hepatic cancers, This involves gene discovery by high throughput sequencing of cancer cDNA libraries, gene expression profiling by DNA microarray and proteomics, and SNP profiling in Korea patient population, Our bioinformatics team will support all these activities by collecting, processing and analyzing these data.

• Proceedings of the Korean Society of Plant Biotechnology Conference
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• 2005.11a
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• pp.265-265
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• 2005

• BMB Reports
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• v.37 no.1
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• pp.53-58
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• 2004

With advances in determining the entire DNA sequence of the human genome, it is now critical to systematically identify the function of a number of genes in the human genome. These biological challenges, especially those in human diseases, should be addressed in human cells in which conventional (e.g. genetic) approaches have been extremely difficult to implement. To overcome this, several approaches have been initiated. This review will focus on the development of a novel 'chemical genetic/genomic approach' that uses small molecules to 'probe and identify' the function of genes in specific biological processes or pathways in human cells. Due to the close relationship of small molecules with drugs, these systematic and integrative studies will lead to the 'medicinal systems biology approach' which is critical to 'formulate and modulate' complex biological (disease) networks by small molecules (drugs) in human bio-systems.

• Plant Biotechnology Reports
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• v.2 no.2
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• pp.93-112
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• 2008

Medicinal and aromatic plants (MAPs) are important sources for plant secondary metabolites, which are important for human healthcare. Improvement of the yield and quality of these natural plant products through conventional breeding is still a challenge. However, recent advances in plant genomics research has generated knowledge leading to a better understanding of the complex genetics and biochemistry involved in biosynthesis of these plant secondary metabolites. This genomics research also concerned identification and isolation of genes involved in different steps of a number of metabolic pathways. Progress has also been made in the development of functional genomics resources (EST databases and micro-arrays) in several medicinal plant species, which offer new opportunities for improvement of genotypes using perfect markers or genetic transformation. This review article presents an overview of the recent developments and future possibilities in genetics and genomics of MAP species including use of transgenic approach for their improvement.

• Reproductive and Developmental Biology
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• v.37 no.4
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• pp.185-192
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• 2013

Many countries have implemented genetic evaluation for fertility traits in recent years. In particular, reproductive trait is a complex trait and need to require a system-level approach for identifying candidate genes related to the trait. To find the candidate gene associated with reproductive trait, we applied a weighted gene co-expression network analysis from expression value of bovine genes. We identified three co-expressed modules associated with reproductive trait from bovine microarray data. Hub genes (ZP4, FHL2 and EGR4) were determined in each module; they were topologically centered with statistically significant value in the gene co-expression network. We were able to find the highly co-expressed gene pairs with a correlation coefficient. Finally, the crucial functions of co-expressed modules were reported from functional enrichment analysis. We suggest that the network-based approach in livestock may an important method for analyzing the complex effects of candidate genes associated with economic traits like reproduction.

• BMB Reports
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• v.42 no.6
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• pp.315-323
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• 2009

In order to elucidate ultimate biological function of the genome, the model animal system carrying mutations is indispensable. Recently, large-scale mutagenesis projects have been launched in various species. Especially, the mouse is considered to be an ideal model to human because it is a mammalian species accompanied with well-established genetic as well as embryonic technologies. In 1990', large-scale mouse mutagenesis projects firstly initiated with a potent chemical mutagen, N-ethyl-N-nitrosourea (ENU) by the phenotype-driven approach or forward genetics. The knockout mouse mutagenesis projects with trapping/conditional mutagenesis have then followed as Phase II since 2006 by the gene-driven approach or reverse genetics. Recently, the next-generation gene targeting system has also become available to the research community, which allows us to establish and analyze mutant mice carrying an allelic series of base substitutions in target genes as another reverse genetics. Overall trends in the large-scale mouse mutagenesis will be reviewed in this article particularly focusing on the new advancement of the next-generation gene targeting system. The drastic expansion of the mutant mouse resources altogether will enhance the systematic understanding of the life. The construction of the mutant mouse resources developed by the forward and reverse genetic mutagenesis is just the beginning of the annotation of mammalian genome. They provide basic infrastructure to understand the molecular mechanism of the gene and genome and will contribute to not only basic researches but also applied sciences such as human disease modelling, genomic medicine and personalized medicine.

• Plant Biotechnology Reports
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• v.5 no.4
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• pp.331-344
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• 2011

The well-conserved NBS domain of resistance (R) genes cloned from many plants allows the use of a PCR-based approach to isolate resistance gene analogs (RGAs). In this study, we isolated an RGA (CapRGC) from Capsicum annuum "CM334" using a PCR-based approach. This sequence encodes a protein with very high similarity to Rx genes, the Potato Virus X (PVX) R genes from potato. An evolutionary analysis of the CapRGC gene and its homologs retrieved by an extensive search of a Solanaceae database provided evidence that Rx-like genes (eight ESTs or genes that show very high similarity to Rx) appear to have diverged from R1 [an NBS-LRR R gene against late blight (Phytophthora infestans) from potato]-like genes. Structural comparison of the NBS domains of all the homologs in Solanaceae revealed that one novel motif, 14, is specific to the Rx-like genes, and also indicated that several other novel motifs are characteristic of the R1-like genes. Our results suggest that Rx-like genes are ancient but conserved. Furthermore, the novel conserved motifs can provide a basis for biochemical structural. function analysis and be used for degenerate primer design for the isolation of Rx-like sequences in other plant species. Comparative mapping study revealed that the position of CapRGC is syntenic to the locations of Rx and its homolog genes in the potato and tomato, but cosegregation analysis showed that CapRGC may not be the R gene against PVX in pepper. Our results confirm previous observations that the specificity of R genes is not conserved, while the structure and function of R genes are conserved. It appears that CapRGC may function as a resistance gene to another pathogen, such as the nematode to which the structure of CapRGC is most similar.

• Genomics & Informatics
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• v.10 no.1
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• pp.33-39
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• 2012

High-throughput genomic technologies (HGTs), including next-generation DNA sequencing (NGS), microarray, and serial analysis of gene expression (SAGE), have become effective experimental tools for cancer genomics to identify cancer-associated somatic genomic alterations and genes. The main hurdle in cancer genomics is to identify the real causative mutations or genes out of many candidates from an HGT-based cancer genomic analysis. One useful approach is to refer to known cancer genes and associated information. The list of known cancer genes can be used to determine candidates of cancer driver mutations, while cancer gene-related information, including gene expression, protein-protein interaction, and pathways, can be useful for scoring novel candidates. Some cancer gene or mutation databases exist for this purpose, but few specialized tools exist for an automated analysis of a long gene list from an HGT-based cancer genomic analysis. This report presents a new web-accessible bioinformatic tool, called CaGe, a cancer genome annotation system for the assessment of candidates of cancer genes from HGT-based cancer genomics. The tool provides users with information on cancer-related genes, mutations, pathways, and associated annotations through annotation and browsing functions. With this tool, researchers can classify their candidate genes from cancer genome studies into either previously reported or novel categories of cancer genes and gain insight into underlying carcinogenic mechanisms through a pathway analysis. We show the usefulness of CaGe by assessing its performance in annotating somatic mutations from a published small cell lung cancer study.