• Genomics & Informatics
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• v.6 no.4
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• pp.202-209
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• 2008

Biological pathways are known as collections of knowledge of certain biological processes. Although knowledge about a pathway is quite significant to further analysis, it covers only tiny portion of genes that exists. In this paper, we suggest a model to extend each individual pathway using a microarray expression data based on the known knowledge about the pathway. We take the Rosetta compendium dataset to extend pathways of Saccharomyces cerevisiae obtained from KEGG (Kyoto Encyclopedia of genes and genomes) database. Before applying our model, we verify the underlying assumption that microarray data reflect the interactive knowledge from pathway, and we evaluate our scoring system by introducing performance function. In the last step, we validate proposed candidates with the help of another type of biological information. We introduced a pathway extending model using its intrinsic structure and microarray expression data. The model provides the suitable candidate genes for each single biological pathway to extend it.

• Genomics & Informatics
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• v.3 no.2
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• pp.47-51
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• 2005

Molecular mechanisms of biological processes are typically represented as 'pathways' that have a graph­analogical network structure. However, due to the diversity of topics that pathways cover, their constituent biological entities are highly diverse and the semantics is embedded implicitly. The kinds of interactions that connect biological entities are likewise diverse. Consequently, how to model or process pathway data is not a trivial issue. In this review article, we give an overview of the challenges in pathway database development by taking the INOH project as an example.

• Proceedings of the Korean Information Science Society Conference
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• 2003.04c
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• pp.407-409
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• 2003

최근 바이오인포메틱스 분야는 IT의 발전과 더불어 급속한 발전을 이루어 왔다. 또한 기존의 분자생물학분야의 연구들을 컴퓨터의 첨단 기술을 이용하여 자동화, 전산화하는 것으로 생명정보의 데이터베이스 구축을 시작으로 서열정보의 주석처리 둥이 발전되어 왔다. 또한 분자생물학의 오랜 연구결과들 중 수많은 문헌들을 토대로 한 분석인 텍스트마이닝, 정보추출은 전산학의 방법으로 데이터를 추출, 수집하여 분자생물학 데이터의 양적 팽창을 더욱 가속화하고 있다. 본 논문에서는 수집된 biological Pathway 정보의 효율적인 저장, 재사용 그리고 활용을 위해 바이오 온톨로지 기반의 XML DB를 설계하고자 한다. XML 스키마를 이용해 표현한 온톨로지를 기반으로 다양한 포맷의 생물학 데이터를 수집하고 수집된 데이터들로 XML DB를 구축한 후 Biological Pathway 정보 표현과 재사용. 나아가 생명정보학 응용분야에 활용하려 한다.

• Genomics & Informatics
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• v.5 no.4
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• pp.200-202
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• 2007

For the past several years, we have built various tools for automatic construction of biopathways to help biological experts, especially in the field of agriculture. We integrated several systems for constructing web applications for analyzing biological pathway information for agricultural species, constructing optimized pathway maps. In addition to building web applications for agricultural pathway information, we developed several stand-alone software tools, which are publicly downloadable under proper license agreements.

• Molecular & Cellular Toxicology
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• v.3 no.3
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• pp.208-213
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• 2007

With the help of a development and popularization of microarray technology that enable to us to simultaneously investigate the expression pattern of thousands of genes, the toxicogenomics experimenters can interpret the genome-scale interaction between genes exposed in toxicant or toxicant-related environment. The ultimate and primary goal of toxicogenomics identifies functional context among the group of genes that are differentially or similarly coexpressed under the specific toxic substance. On the other side, public reference databases with transcriptom, proteom, and biological pathway information are needed for the analysis of these complex omics data. However, due to the heterogeneous and independent nature of these databases, it is hard to individually analyze a large omics annotations and their pathway information. Fortunately, several web sites of the public database provide information linked to other. Nevertheless it involves not only approriate information but also unnecessary information to users. Therefore, the systematically integrated database that is suitable to a demand of experimenters is needed. For these reasons, we propose SOP (Search of Omics Pathway) database system which is constructed as the integrated biological database converting heterogeneous feature of public databases into combined feature. In addition, SOP offers user-friendly web interfaces which enable users to submit gene queries for biological interpretation of gene lists derived from omics experiments. Outputs of SOP web interface are supported as the omics annotation table and the visualized pathway maps of KEGG PATHWAY database. We believe that SOP will appear as a helpful tool to perform biological interpretation of genes or proteins traced to omics experiments, lead to new discoveries from their pathway analysis, and design new hypothesis for a next toxicogenomics experiments.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.22
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• pp.9791-9795
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• 2014

To study the gene expression change and possible signal pathway during androgen-dependent prostate cancer (ADPC) becoming androgen-independent prostate cancer (AIPC), an LNCaP cell model of AIPC was established using flutamide in combination with androgen-free environment inducement, and differential expression genes were screened by microarray. Then the biological process, molecular function and KEGG pathway of differential expression genes are analyzed by Molecule Annotation System (MAS). By comparison of 12,207 expression genes, 347 expression genes were acquired, of which 156 were up-ragulated and 191 down-regulated. After analyzing the biological process and molecule function of differential expression genes, these genes are found to play crucial roles in cell proliferation, differntiation, cell cycle control, protein metabolism and modification and other biological process, serve as signal molecules, enzymes, peptide hormones, cytokines, cytoskeletal proteins and adhesion molecules. The analysis of KEGG show that the relevant genes of AIPC transformation participate in glutathione metabolism, cell cycle, P53 signal pathway, cytochrome P450 metabolism, Hedgehog signal pathway, MAPK signal pathway, adipocytokines signal pathway, PPAR signal pathway, TGF-${\beta}$ signal pathway and JAK-STAT signal pathway. In conclusion, during the process of ADPC becoming AIPC, it is not only one specific gene or pathway, but multiple genes and pathways that change. The findings above lay the foundation for study of AIPC mechanism and development of AIPC targeting drugs.

• Genomics & Informatics
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• v.3 no.1
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• pp.30-34
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• 2005

Microarray technology makes it possible to measure the expressions of tens of thousands of genes simultaneously under various experimental conditions. Identifying differentially expressed genes in each single experimental condition is one of the most common first steps in microarray gene expression data analysis. Reasonable choices of thresholds for determining differentially expressed genes are used for the next-stap-analysis with suitable statistical significances. We present a supervised model for identifying DEGs using pathway information based on the global connectivity structure. Pathway information can be regarded as a collection of biological knowledge, thus we are trying to determine the optimal threshold so that the consequential connectivity structure can be the most compatible with the existing pathway information. The significant feature of our model is that it uses established knowledge as a reference to determine the direction of analyzing microarray dataset. In the most of previous work, only intrinsic information in the miroarray is used for the identifying DEGs. We hope that our proposed method could contribute to construct biologically meaningful structure from microarray datasets.

• Journal of Microbiology and Biotechnology
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• v.33 no.10
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• pp.1370-1375
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• 2023

In this study, we aimed to enhance the accumulation of chorismate (CHR) and anthranilate (ANT), key intermediates in the shikimate pathway, by modifying a shikimate over-producing recombinant strain of Corynebacterium glutamicum [19]. To achieve this, we utilized a CRISPR-driven genome engineering approach to compensate for the deletion of shikimate kinase (AroK) as well as ANT synthases (TrpEG) and ANT phosphoribosyltransferase (TrpD). In addition, we inhibited the CHR metabolic pathway to induce CHR accumulation. Further, to optimize the shikimate pathway, we overexpressed feedback inhibition-resistant Escherichia coli AroG and AroH genes, as well as C. glutamicum AroF and AroB genes. We also overexpressed QsuC and substituted shikimate dehydrogenase (AroE). In parallel, we optimized the carbon metabolism pathway by deleting the gntR family transcriptional regulator (IolR) and overexpressing polyphosphate/ATP-dependent glucokinase (PpgK) and glucose kinase (Glk). Moreover, acetate kinase (Ack) and phosphotransacetylase (Pta) were eliminated. Through our CRISPR-driven genome re-design approach, we successfully generated C. glutamicum cell factories capable of producing up to 0.48 g/l and 0.9 g/l of CHR and ANT in 1.3 ml miniature culture systems, respectively. These findings highlight the efficacy of our rational cell factory design strategy in C. glutamicum, which provides a robust platform technology for developing high-producing strains that synthesize valuable aromatic compounds, particularly those derived from the shikimate pathway metabolites.

• Genomics & Informatics
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• v.16 no.4
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• pp.39.1-39.3
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• 2018

The rapid increase in genetic dataset volume has demanded extensive adoption of biological knowledge to reduce the computational complexity, and the biological pathway is one well-known source of such knowledge. In this regard, we have introduced a novel statistical method that enables the pathway-based association study of large-scale genetic dataset-namely, PHARAOH. However, researcher-level application of the PHARAOH method has been limited by a lack of generally used file formats and the absence of various quality control options that are essential to practical analysis. In order to overcome these limitations, we introduce our integration of the PHARAOH method into our recently developed all-in-one workbench. The proposed new PHARAOH program not only supports various de facto standard genetic data formats but also provides many quality control measures and filters based on those measures. We expect that our updated PHARAOH provides advanced accessibility of the pathway-level analysis of large-scale genetic datasets to researchers.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.12
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• pp.5087-5094
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• 2016

mTOR, the mammalian target of rapamycin, is a conserved serine/threonine kinase which belongs to the phosphatidyl-linositol kinase-related kinase (PIKK) family. It has two complexes called mTORC1 and mTORC2. It is well established that mTOR plays important roles in cell growth, proliferation and differentiation. Over-activation of the mTOR pathway is considered to have a relationship with the development of many types of diseases, including polycystic ovary syndrome (PCOS) and ovarian cancer (OC). mTOR pathway inhibitors, such as rapamycin and its derivatives, can directly or indirectly treat or relieve the symptoms of patients suffering from PCOS or OC. Moreover, mTOR inhibitors in combination with other chemical-molecular agents may have extraordinary efficacy. This paper will discuss links between mTOR signaling and PCOS and OC, and explore the mechanisms of mTOR inhibitors in treating these two diseases, with conclusions regarding the most effective therapeutic approaches.