• 검색어에 아래의 연산자를 사용하시면 더 정확한 검색결과를 얻을 수 있습니다.
  • 검색연산자
검색연산자 기능 검색시 예
() 우선순위가 가장 높은 연산자 예1) (나노 (기계 | machine))
공백 두 개의 검색어(식)을 모두 포함하고 있는 문서 검색 예1) (나노 기계)
예2) 나노 장영실
| 두 개의 검색어(식) 중 하나 이상 포함하고 있는 문서 검색 예1) (줄기세포 | 면역)
예2) 줄기세포 | 장영실
! NOT 이후에 있는 검색어가 포함된 문서는 제외 예1) (황금 !백금)
예2) !image
* 검색어의 *란에 0개 이상의 임의의 문자가 포함된 문서 검색 예) semi*
"" 따옴표 내의 구문과 완전히 일치하는 문서만 검색 예) "Transform and Quantization"
쳇봇 이모티콘
ScienceON 챗봇입니다.
궁금한 것은 저에게 물어봐주세요.

논문 상세정보


For the direct understanding of flow, pathway data are usually represented as directed graphs in biological journals and texts. Databases of metabolic pathways or signal transduction pathways inevitably contain these kinds of graphs to show the flow. KEGG, one of the representative pathway databases, uses the manually drawn figure which can not be easily maintained. Graph layout algorithms are applied for visualizing metabolic pathways in some databases, such as EcoCyc. Although these can express any changes of data in the real time, it exponentially increases the edge crossings according to the increase of nodes. For the understanding of genome scale flow of metabolism, it is very important to reduce the unnecessary edge crossings which exist in the automatic graph layout. We propose a metabolic pathway drawing algorithm for reducing the number of edge crossings by considering the fact that metabolic pathway graph is scale-free network. The experimental results show that the number of edge crossings is reduced about $37{\sim}40%$ by the consideration of scale-free network in contrast with non-considering scale-free network. And also we found that the increase of nodes do not always mean that there is an increase of edge crossings.

참고문헌 (11)

  1. Barabasi, A.L. and Albert, R. (1999). Emergence of Scaling in Random Networks. Science 286, 509-512 
  2. Becker, M.Y. and Rojas, I. (2001). A Graph Layout Algorithm for Drawing Metabolic Pathways. Bioinformatics 17, 461-467 
  3. BioCarta Team. (2001). Biocarta: Charting Pathways of Life. http://www.biocarta.com 
  4. Goh, K.I., Kahng, B., and Kim, D. (2001). Universal Behavior of Load Distribution in Scale-Free Networks. Physical Review Letters 87, 278701 
  5. Holme, P., Huss, M., and Jeong, H. (2003). Subnetwork Hierarchies of Biochemical Pathways. Bioinformatics 19, 532-538 
  6. Jeong, H., Tombor, B., Albert, R., Oltvai, Z.N., and Barabasi, A.L. (2000). The Large-scale Organization of Metabolic Networks. Nature 407, 651-654 
  7. Kanehisa, M., Goto, S., Kawashima, S., and Nakaya, A. (2002). The KEGG Databases at GenomeNet. Nucleic Acids Res. 30, 42-46 
  8. Karp, P.D. and Paley, S. (1994). Automated Drawing of Metabolic Pathways. Third International Conference on Bioinformatics and Genome Research. 225-238 
  9. Karp, P.D., Riley, M., Saier, M., Paulsen, I.T., Collado-Vides, J., Paley, S.M., Pellegrini-Toole, A., Bonavides, C., and Gama-Castro, S. (2002). The EcoCyc Database. Nucleic Acids Res. 30, 56-58 
  10. Lee, S.H., Song, E.H., Lee, S.H., and Park, H.S. (2004). An Algorithm for Drawing Metabolic Pathways based on Structural Characteristics, J. Korea Information Science Society 31, 1266-1275 
  11. Wiese, R., Eiglsperger, M., and Schabert, P. (2000). The Y-files Graph Library: Documentation and Code. http://www-pr.informatik.uni-tuebingen.de/yfiles 

이 논문을 인용한 문헌 (2)

  1. 2008. "" Genomics & informatics, 6(2): 68~71 
  2. 2008. "" Genomics & informatics, 6(3): 147~152 


원문 PDF 다운로드

  • ScienceON :

원문 URL 링크

원문 PDF 파일 및 링크정보가 존재하지 않을 경우 KISTI DDS 시스템에서 제공하는 원문복사서비스를 사용할 수 있습니다. (원문복사서비스 안내 바로 가기)

상세조회 0건 원문조회 0건

DOI 인용 스타일