K-Neighborhood decentralization: A comprehensive solution to index the UMLS for large scale knowledge discovery

Journal of Biomedical Informatics

Volumn 45, Issue 2, 2012, Pages 323-336

  Xiang, Yang ^a   Lu, Kewei ^b   James, Stephen L ^a   Borlawsky, Tara B ^a   Huang, Kun ^a   Payne, Philip R O ^a  

^a OHIO STATE UNIVERSITY   (United States)

^b The Ohio State University   (United States)

Author keywords

Disease gene prioritization; Fold enrichment; Graph database; Knowledge discovery; UMLS

Indexed keywords

BIOMEDICAL INFORMATICS; GRAPH DATABASE; INDEXING SCHEME; LABELING SCHEME; LARGE SIZES; MEDICAL INFORMATICS APPLICATIONS; PRIORITIZATION; UMLS; UNIFIED MEDICAL LANGUAGE SYSTEMS;

DATA MINING; GENES; INDEXING (OF INFORMATION);

MEDICAL EDUCATION;

ARTICLE; DECENTRALIZATION; GENOME; HUMAN; HYPOTHESIS; INFORMATION PROCESSING; INFORMATION RETRIEVAL; KNOWLEDGE DISCOVERY; MEDICAL INFORMATION SYSTEM; PRIORITY JOURNAL; SEMANTICS;

ABSTRACTING AND INDEXING AS TOPIC; ALGORITHMS; MEDICAL INFORMATICS; POLITICS; UNIFIED MEDICAL LANGUAGE SYSTEM;

EID: 84858285777     PISSN: 15320464     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jbi.2011.11.012     Document Type: Article

References (39)

1. Bodenreider O. The unified medical language system (UMLS): integrating biomedical terminology. Nucleic Acids Res 2004, 32(suppl. 1):D267.
2. Sioutos N., Coronado S., Haber M., Hartel F., Shaiu W., Wright L. NCI Thesaurus: a semantic model integrating cancer-related clinical and molecular information. J Biomed Inform 2007, 40(1):30-43.
3. Hamosh A., Scott A., Amberger J., Bocchini C., McKusick V. Online Mendelian Inheritance in Man (OMIM), a knowledgebase of human genes and genetic disorders. Nucleic Acids Res 2005, 33(suppl. 1):D514.
4. Stearns M, Price C, Spackman K, Wang A. SNOMED clinical terms: overview of the development process and project status. In: Proceedings of the AMIA symposium, American Medical Informatics Association, 2001. p. 662.
5. Payne P, Borlawsky T, Kwok A, Dhaval R, Greaves A. Ontology-anchored approaches to conceptual knowledge discovery in a multi-dimensional research data repository. In: Summit on translational bioinformatics, American Medical Informatics Association, 2008. p. 85.
6. Payne P, Borlawsky T, Kwok A, Greaves A. Supporting the design of translational clinical studies through the generation and verification of conceptual knowledge-anchored hypotheses. In: AMIA annual symposium proceedings, American Medical Informatics Association, 2008. p. 566.
7. Payne P, Kwok A, Dhaval R, Borlawsky T. Conceptual dissonance: evaluating the efficacy of natural language processing techniques for validating translational knowledge constructs. In: Summit on translational bioinformatics, American Medical Informatics Association, 2009. p. 95.
8. Jin R, Xiang Y, Ruan N, Fuhry D. 3-Hop: a high-compression indexing scheme for reachability query. in: Proceedings of the 35th SIGMOD international conference on management of data, SIGMOD '09, ACM, 2009. p. 813-26.
9. Cohen E., Halperin E., Kaplan H., Zwick U. Reachability and distance queries via 2-Hop labels. SIAM J Comput 2003, 32(5):1338-1355.
10. Schenkel R, Theobald A, Weikum G. HOPI: an efficient connection index for complex XML document collections. In: EDBT, 2004. p. 237-55.
11. Schenkel R, Theobald A, Weikum G. Efficient creation and incremental maintenance of the HOPI index for complex XML document collections. In: ICDE, 2005. p. 360-71.
12. Cheng J, Yu JX. On-line exact shortest distance query processing. In: Proceedings of the 12th international conference on extending database technology: advances in database technology, EDBT '09, ACM, 2009. p. 481-92.
13. Aerts S., Lambrechts D., Maity S., Van Loo P., Coessens B., De Smet F., et al. Gene prioritization through genomic data fusion. Nat Biotechnol 2006, 24(5):537-544.
14. Franke L., Bakel H., Fokkens L., de Jong E., Egmont-Petersen M., Wijmenga C., et al. Reconstruction of a functional human gene network, with an application for prioritizing positional candidate genes. Am J Hum Genet 2006, 78(6):1011-1025.
15. Lage K., Karlberg E., Størling Z., ólason P., Pedersen A., Rigina O., et al. A human phenome-interactome network of protein complexes implicated in genetic disorders. Nat Biotechnol 2007, 25(3):309-316.
16. Gaulton K., Mohlke K., Vision T. A computational system to select candidate genes for complex human traits. Bioinformatics 2007, 23(9):1132.
17. Wu X., Jiang R., Zhang M., Li S. Network-based global inference of human disease genes. Mol Syst Biol 2008, 4. [article number 189].
18. Linghu B., Snitkin E., Hu Z., Xia Y., DeLisi C. Genome-wide prioritization of disease genes and identification of disease-disease associations from an integrated human functional linkage network. Genome Biol 2009, 10(9):R91.
19. Chen J., Aronow B., Jegga A. Disease candidate gene identification and prioritization using protein interaction networks. BMC Bioinform 2009, 10(1):73.
20. Xiang Y., Payne P.R., Huang K. Transactional database transformation and its application in prioritizing human disease genes. IEEE/ACM Trans Comput Biol Bioinformat 2012, 9(1):294-304.
21. Vargova K., Curik N., Burda P., Basova P., Kulvait V., Pospisil V., et al. Myb transcriptionally regulates the MIR-155 host gene in chronic lymphocytic leukemia. Blood 2011, 117(14):3816.
22. Gavoille C., Peleg D., Pérennes S., Raz R. Distance labeling in graphs. J Algorithms 2004, 53:85-112.
23. Lee W, Shah N, Sundlass K, Musen M. Comparison of ontology-based semantic-similarity measures. In: AMIA annual symposium proceedings, vol. 2008, American Medical Informatics Association, 2008. p. 384.
24. McInnes B, Pedersen T, Pakhomov S. UMLS-interface and UMLS-similarity: open source software for measuring paths and semantic similarity. In: AMIA annual symposium proceedings, American Medical Informatics Association, 2009. p. 431.
25. Melton G., Parsons S., Morrison F., Rothschild A., Markatou M., Hripcsak G. Inter-patient distance metrics using SNOMED CT defining relationships. J Biomed Inform 2006, 39(6):697-705.
26. Nguyen H, Al-Mubaid H. New ontology-based semantic similarity measure for the biomedical domain. In: IEEE International Conference on Granular Computing, 2006, IEEE, 2006. p. 623-8.
27. Rada R., Mili H., Bicknell E., Blettner M. Development and application of a metric on semantic nets. IEEE Trans Syst Man Cybern 1989, 19(1):17-30.
28. R. Jin, H. Hong, H. Wang, N. Ruan, Y. Xiang, Computing label-constraint reachability in graph databases, in: Proceedings of the 2010 international conference on Management of data, ACM, 2010, pp. 123-134.
29. Fonseca R, Ratnasamy S, Zhao J, Ee CT, Culler D, Shenker S, et al. Beacon vector routing: scalable point-to-point routing in wireless sensornets. In: Proceedings of the 2nd conference on symposium on networked systems design & implementation, vol. 2, 2005. p. 329-42.
30. Simon K. An improved algorithm for transitive closure on acyclic digraphs. Theor Comput Sci 1988, 58:325-346.
31. Agrawal R, Borgida A, Jagadish HV. Efficient management of transitive relationships in large data and knowledge bases. In: Proceedings of the 1989 ACM SIGMOD international conference on management of data, 1989. p. 253-62.
32. Jagadish H. A compression technique to materialize transitive closure. ACM Trans Database Syst (TODS) 1990, 15(4):558-598.
33. Wang H, He H, Yang J, Yu PS, Yu JX. Dual labeling: answering graph reachability queries in constant time. In: Proceedings of the 22nd international conference on data engineering, 2006. p. 75.
34. Cheng J, Yu JX, Lin X, Wang H, Yu PS. Fast computing reachability labelings for large graphs with high compression rate. In: EDBT, 2008; p. 193-204.
35. Trißl S, Leser U. Fast and practical indexing and querying of very large graphs. In: Proceedings of the 2007 ACM SIGMOD international conference on management of data, SIGMOD '07, ACM, 2007. p. 845-56.
36. Jin R., Ruan N., Xiang Y., Wang H. Path tree: An efficient reachability indexing scheme for large directed graphs. ACM Trans Database Syst (TODS) 2011, 36(1):7:1-7:44.
37. Yildirim H., Chaoji V., Zaki M. GRAIL: scalable reachability index for large graphs. Proc VLDB Endowment 2010, 3(1-2):276-284.
38. Xiao Y, Wu W, Pei J, Wang W, He Z. Efficiently indexing shortest paths by exploiting symmetry in graphs. In: Proceedings of the 12th international conference on extending database technology: advances in database technology, EDBT '09, ACM, 2009. p. 493-504.
39. Wei F. TEDI: efficient shortest path query answering on graphs. In: Proceedings of the 2010 international conference on management of data, SIGMOD '10, ACM, 2010. p. 99-110.