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Over the past decade, microarray experiments have become popular with a common method of high-throughput omics technologies for understanding of gene expression patterns at the genome level. The objective of microarray experiments is to identify differentially expressed genes (DEGs) or similarly patterned genes groups from microarray experiments. For these reasons, several preprocessing methods for correction of experimental or systemic bias of microarray experiments have been proposed, and a number of statistical algorithms for selection of specially expressed genes within all genes on a microarray have been developed in order to support more reliable and significant results. With the results produced by these useful tools, researchers have examined common biological features, such as functional interactions in shared biological processes, direct-indirect regulation at the molecular level, or disease relation in a biological pathway or network. Of these biological identification analyses, pathway analysis has been mainly used for functional detection of biological features between these co-expressed genes. An advantage of pathway analysis is a visualization that has an important role in understanding of the intricate phenomena of pathways containing biochemical reactions or functional relations among a gene’s products, enzymes, substrates, activators, inhibitors, or other biological molecular elements. For these reasons, several bioinformatics tools for pathway analysis based on external pathway data sources, such as KEGG or BIOCARTA, have been developed. These tools have offered user-friendly and powerful interfaces, visual and graphical functions of pathway diagrams, and biological annotations. However, the problems encountered by users remain unresolved in certain respects that are a complicated input file format derived from gene expression profiles, a time-consuming work for collection of information on pathways that contain several genes identified as interesting genes, or a restriction in picturing a pathway image map that included more than two interesting genes. In an attempt to overcome these problems, we have developed Array2KEGG as a web-based tool for finding pathway diagrams from the KEGG PATHWAY database. Array2KEGG has focused on simplicity in user interface, integration in heterogeneous biological databases, and visualization in depiction of a pathway diagram that includes more than two interesting genes. Array2KEGG is freely available for use at http://www.koreagene.co.kr/cgi-bin/service/service1.pl.

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기사명 저자명 페이지 원문 목차
Genome-wide expression profiling of carbaryl and vinclozolin in human thyroid follicular carcinoma(FTC-238) cells Mee Song, Youn Jung Kim, Ji-Na Lee, Jae Chun Ryu pp.89-98

TOXPO : TOXicogenomics knowledgebase for inferring toxicity based on POlymorphism Yunju Jo, In Song Koh, Hyunsu Bae, Moo-Chang Hong, Min-Kyu Shin, Yang Seok Kim pp.99-104

An oligonucleotide microarray to detect pathogens causing a sexually transmitted disease Hyun Kyu Yoon, Jun Sub Kim, In Hyuk Chung, Seung Yong Lee, JaeRyul Han, Chansoo Park, Seung Yong Hwang pp.105-109

Optical enzyme-linked immunosorbent assay on a strip for detection of Salmonella typhimurium Sojung Park, Yong Tae Kim, Young-Kee Kim pp.110-116

Integration of movable structures in PDMS microfluidic channels Zhenkai Hu, Gu Han Kwon, Chang-Beom Kim, DongPyo Kim, Sang-Hoon Lee pp.117-122

Genetic analysis of gene expression for pigmentation in Chinese cabbage (Brassica rapa) ChangKug Kim, SungHan Park, Shoshi Kikuchi, SooJin Kwon, Suhyoung Park, UngHan Yoon, DongSuk Park, YoungJoo Seol, JangHo Hahn, SooChul Park … [et al.] pp.123-128

Simple route for the detection of Escherichia coli using quantum dots Pan Kee Bae, Hye-Mi So, Kyung Nam Kim, Hwa Sung You, Kang Sik Choi, Chang Hae Kim, Jeong-Kyu Park, Jeong-O Lee pp.129-133

Array2KEGG : web-based tool of KEGG pathway analysis for gene expression profile Jun-Sub Kim, Seung-Jun Kim, Hye-Won Park, Jong-Pil Youn, Yu Ri An, Hyunseok Cho, Seung Yong Hwang pp.134-140

Comparison of the sensitivity of thiolated aptamer based biosensor according to the condition of electrode substrates Se Hoon Jeong, Changsung Sean Kim, Jeongsuong Yang pp.141-147

The optimization of PDMS-PMMA bonding process using silane primer Kangil Kim, Sin Wook Park, Sang Sik Yang pp.148-154

Highly sensitive rapid test with chemiluminescent signal bands Hyung-Seok Kim, Hyuk Ko, Min-Jung Kang, Jae-Chul Pyun pp.155-160

A study on cancer-cell invasion based on multi-physics analysis technology Zhang Linan, Jihwan Song, Dongchoul Kim pp.161-165

참고문헌 (26건) : 자료제공( 네이버학술정보 )

참고문헌 목록에 대한 테이블로 번호, 참고문헌, 국회도서관 소장유무로 구성되어 있습니다.
번호 참고문헌 국회도서관 소장유무
1 DNA microarray applications in functional genomics. 네이버 미소장
2 Analysis and management of microarray gene expression data. 네이버 미소장
3 Daniel, P.B., Werner, D. & Martin, G. A practical approach to microarray data analysis. Kluwer Academic publishers. 25-38 (2003). 미소장
4 Daniel, P.B., Werner, D. & Martin, G. A practical approach to microarray data analysis. Kluwer Academic publishers. 16-18 (2003). 미소장
5 Robert, G., Vincent, J.C., Wolfgang, H., Rafael, A.I. & Sandrine, D. Bioinformatics and computational biology solutions using R and bioconductor. Springer. 229-248 (2005). 미소장
6 Xiao, J., Wang, X. & Xu, C. Gene clustering analysis of DNA microarray data. Jun;25, 729-733 (2008). 미소장
7 Jarno, T. & Laine, M.M. DNA Microarray Data Analysis. CSC-Scientific Computing Ltd., 108-112 (2003). 미소장
8 http://www.bioconductor.org/workshops/2003/Milan/Lectures/classif.pdf. 미소장
9 cPath: open source software for collecting, storing, and querying biological pathways. 네이버 미소장
10 Curtis, R.K., Oresic, M. & Vidal-Puig, A. Pathways to the analysis of microarray data. Trends Biotechnol. Aug;23, 429-435 (2005). 미소장
11 Computational Systems Bioinformatics and Bioimaging for Pathway Analysis and Drug Screening 네이버 미소장
12 Identification of differential gene pathways with principal component analysis 네이버 미소장
13 Inferring pathways from gene lists using a literature-derived network of biological relationships. 네이버 미소장
14 KEGG-based pathway visualization tool for complex omics data. 네이버 미소장
15 KEGGanim: pathway animations for high-throughput data. 네이버 미소장
16 KEGG spider: interpretation of genomics data in the context of the global gene metabolic network. 네이버 미소장
17 Li, S., Wu, L. & Zhang, Z. Constructing biological networks through combined literature mining and microarray analysis: a LMMA approach. Bioinormatics. Sep 1;22, 2143-2150 (2006). 미소장
18 KEGG for representation and analysis of molecular networks involving diseases and drugs. 네이버 미소장
19 GenMAPP 2: new features and resources for pathway analysis. 네이버 미소장
20 Pan, D. et al. PathMAPA: a tool for displaying gene expression and performing statistical tests on metabolic pathways at multiple levels for Arabidopsis. BMC Bioinformatics. Nov 7;4, 56 (2007). 미소장
21 KEGG Atlas mapping for global analysis of metabolic pathways 네이버 미소장
22 GS2PATH: a web-based integrated analysis tool for finding functional relationships using gene ontology and biochemical pathway data. 네이버 미소장
23 PathwayVoyager: pathway mapping using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. 네이버 미소장
24 MySQL [http://www.mysql.com] 미소장
25 Apache [http://www.apache.org] 미소장
26 Fedora [http://fedoraproject.org/] 미소장