Open Access
Issue |
MATEC Web Conf.
Volume 173, 2018
2018 International Conference on Smart Materials, Intelligent Manufacturing and Automation (SMIMA 2018)
|
|
---|---|---|
Article Number | 03025 | |
Number of page(s) | 5 | |
Section | Digital Signal and Image Processing | |
DOI | https://doi.org/10.1051/matecconf/201817303025 | |
Published online | 19 June 2018 |
- Von M C, Krause R, Snel B, et al. Comparative assessment of large-scale data sets of protein-protein interactions.[J]. Nature, 2002, 417(6887):399. [CrossRef] [PubMed] [Google Scholar]
- Rual J F, Venkatesan K, Hao T, et al. Towards a proteome-scale map of the human protein¿protein interaction network[J]. Nature, 2005, 437(7062):1173-8. [CrossRef] [PubMed] [Google Scholar]
- Szklarczyk D, Franceschini A, Kuhn M, et al. The STRING database in 2011: functional interaction networks of proteins, globally integrated and scored[J]. Nucleic Acids Research, 2011, 39(Database issue):561-8. [Google Scholar]
- Leskovec J, Sosič R. SNAP: A General Purpose Network Analysis and Graph Mining Library.[J]. Acm Transactions on Intelligent Systems & Technology, 2016, 8(1):1. [CrossRef] [Google Scholar]
- Robinson I, Webber J, Eifrem E. Graph Databases: New Opportunities for Connected Data[M]. O'Reilly Media, Inc. 2015. [Google Scholar]
- Willett P, Barnard J M, Downs G M. Chemical Similarity Searching[J]. J.chem.inf.comput.sci, 1998, 38(6):983--996. [CrossRef] [Google Scholar]
- Kanehisa,M. and Goto,S.Kegg: kyoto encyclopedia of genes and gen-omes. Nucleic Acids Res. 2000, 28, 27–30. [CrossRef] [PubMed] [Google Scholar]
- Raymond,J.W. et al.Rascal: Calculation of graph similarity using max-imum common edge subgraphs. Comput. J. 2002, 45, 631–644. [CrossRef] [Google Scholar]
- Panni,S. and Rombo,S.E. Searching for repetitions in biological networks: methods, resources and tools. Brief. Bioinf. 2015, 16, 118–136. [CrossRef] [Google Scholar]
- Xu K, Schadt E E, Pollard K S, et al. Genomic and network patterns of schizophrenia genetic variation in human evolutionary accelerated regions.[J]. Molecular Biology & Evolution, 2015, 32(5):1148-60. [CrossRef] [Google Scholar]
- He H, Singh A K. Closure-Tree: An Index Structure for Graph Queries[C]// International Conference on Data Engineering. IEEE, 2006:38. [Google Scholar]
- Jiang H, Wang H, Yu P S, et al. GString: A Novel Approach for Efficient Search in Graph Databases[C]// IEEE, International Conference on Data Engineering. IEEE, 2007:566-575. [Google Scholar]
- Bonnici V, Ferro A, Giugno R, et al. Enhancing Graph Database Indexing by Suffix Tree Structure[C]// Pattern Recognition in Bioinformatics -, Iapr International Conference, Prib 2010, Nijmegen, the Netherlands, September 22-24, 2010. Proceedings. DBLP, 2010:195-203. [Google Scholar]
- MISAEL Mongiovu00cc, RAFFAELE Di Natale, ROSALBA Giugno, et al. SIGMA: A SET-COVER-BASED INEXACT GRAPH MATCHING ALGORITHM[J]. Journal of Bioinformatics & Computational Biology, 2010, 8(02):199-218. [CrossRef] [Google Scholar]
- Günhan G, Tamer K. RINQ: Reference-based Indexing for Network Queries[J]. Bioinformatics, 2011, 27(13):i149-i158. [CrossRef] [Google Scholar]
- Khan A, Wu Y, Aggarwal C C, et al. NeMa: fast graph search with label similarity[C]// International Conference on Very Large Data Bases. VLDB Endowment, 2013:181-192. [Google Scholar]
- Pienta R, Tamersoy A, Tong H, et al. MAGE: Matching Approximate Patterns in Richly-Attributed Graphs[C]// IEEE International Conference on Big Data. IEEE, 2014:585-590. [Google Scholar]
- Soylev A, Abul O. REFBSS: Reference based similarity search in biological network databases[C]// Computational Intelligence in Bioinformatics and Computational Biology. IEEE, 2015:1-8. [Google Scholar]
- Kashtan N, Itzkovitz S, Milo R, et al. Efficient sampling algorithm for estimating subgraph concentrations and detecting network motifs[J]. Bioinformatics, 2004, 20(11):1746-1758. [CrossRef] [PubMed] [Google Scholar]
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