NAR Molecular Biology Database Collection entry number 393

http://angiodb.snu.ac.kr/

Tae-Kwon Sohn¹, Jaehyuk Cha², Yong S. Choi³, Youjip Won⁴, Seok-Ki Lee¹, Sung-yong You¹, Sangback Ma⁵, Eun Bae Kong⁶, Hwangu Lee³, Seung-Hui Kang¹ and Kyu-Won Kim¹

¹Angiogenesis Research Laboratory, Research Institute of Pharmaceutical Sciences and College of Pharmacy, Seoul National University, Seoul 151-742, Korea
²College of Information and Communications, ³Department of Computer Science Education, ⁴Division of Electrical and Computer Engineering, Hanyang University, Seoul 133-791, Korea
⁵School of Electrical and Computer Engineering, Hanyang University, Ansan 425-791, Korea
⁶Department of Computer Engineering, Chungnam National University, Daejon 305-764, Korea

Contact qwonkim@plaza.snu.ac.kr

AngioDB is a secondary database which brought data sources for a specific topic as angiogenesis from primary database and additional literature resources. We firstly constructed AngioDB as Web-accessible database in 2000. It was remodelled with the integrated information according to the function from public databases. The current AngioDB contained 277 genes and 159 chemicals classified into 12 fields. The first version of AngioDB provided imagemap based-retrieving and database-derived information of a signaling network of angiogenesis-related biomolecules.

For the update of AngioDB, we have focused on the construction of a system for automatic detection of protein-protein interactions extracted from angiogenesis-related abstracts. To do this, we developed the design and implementation of a system which extracts protein-protein interactions directly from PubMed database and constructs a protein interaction network database. We retrieved abstracts related to 197 proteins (and also its synonyms ones) of AngioDB from PubMed server using NCBI public API. Total number of angiogenesis-related abstracts is 749,931. Then we extracted the raw protein-protein interaction information from these abstracts using Protein Interaction Information Extractor (PIIE). PIIE parses each abstract into sentences containing any of two different proteins (or synonyms) and a set of 27 pre-specified interaction verbs are selected as prone to contain protein interactions. Since raw information of protein interactions is produced high number of false positives, all produced information is provided to Protein Interaction Verification Tool (PIVT) through which the researchers verify, correct and refine raw interaction information semi-automatically.

This research was supported by the National Research Laboratory Fund and 21C Frontier Functional Human Genome Project(FG03-21-01) from the Ministry of Science and Technology, Korea.

1. Sohn, T.K., Moon, E.J., Lee, S.K., Cho, H.G. and Kim, K.W. AngioDB: Database of angiogenesis and angiogenesis-related molecules. Nucleic Acids Res. 2002; 30; 369-371.
2. Blaschke, C., Andrade, M.A., Ouzounis, C. and Valencia, A. Automatic extraction of biological information from scientific text: protein-protein interactions. Proc. Int. Conf. Intell. Syst. Mol. Biol. 1999; 60-67
3. Jeong, J.W., Bae, M.K., Ahn, M.Y., Kim, S.H., Sohn, T.K., Yoo, M.A., Song, E.J., Lee, K.J. and Kim, K.W. Regulation and destabilization of HIF-1alpha by ARD1-mediated acetylation. Cell 2002; 111(5); 709-720
4. Lee, S.W., Kim, W.J., Choi, Y.K., Song, H.S., Son, M.J., Gelman, I.H., Kim, Y.J. and Kim, K.W. SSeCKS regulates angiogenesis and tight junction formation in blood-brain barrier. Nature Medicine 2003; 9(7); 900-906
5. Kim, M.S., Kwon, H.J., Lee, Y.M., Baek, J.H., Jang, J.E., Lee, S.W., Moon, E.J., Kim, H.S., Lee, S.K., Chung, H.Y., Kim, C.W. and Kim, K.W. Histone deacetylases induce angiogenesis by negative regulation of tumour suppressor genes. Nature Medicine 2001; 7; 437-443

Go to the abstract in the NAR 2002 Database Issue.

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