A parallel algorithm for extracting transcriptional regulatory network motifs

Proceedings - BIBE 2005: 5th IEEE Symposium on Bioinformatics and Bioengineering

Volumn 2005, Issue , 2005, Pages 193-200

  Tie, Wang ^a   Touchman, Jeffrey W ^b,c   Weiyi, Zhang ^a   Suh, Edward B ^c   Guoliang, Xue ^a  

^a Arizona State University   (United States)

^b ARIZONA STATE UNIVERSITY   (United States)

^c TRANSLATIONAL GENOMICS RESEARCH INSTITUTE   (United States)

Author keywords

Network motifs; Systems biology; Transcriptional regulatory network

Indexed keywords

NETWORK MOTIFS; RUNNING TIME; SYSTEMS BIOLOGY; TRANSCRIPTIONAL REGULATORY NETWORKS;

COMPUTATIONAL METHODS; CORRELATION METHODS; ESCHERICHIA COLI; FUNCTIONS; GENES; GRAPHIC METHODS; MOLECULAR STRUCTURE;

PARALLEL ALGORITHMS;

EID: 33751163253     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/BIBE.2005.8     Document Type: Conference Paper

References (22)

1. N. Alon et al., Finding and counting given length cycles. Algorithimica,(1997).
2. T.H. Cormen et al., Introduction to Algorithms, second edition, McGraw Hill,(2001).
3. J. Huan et al., Accurate classification of protein structural families based on coherent subgraph analysis. PSB 2004, (2004).
4. Huan J, et al., Mining protein family specific residue packing patterns from protein structure graphs. RECOMB 2004, 308-315, (2004).
5. Huan J, et al., Mining maximal frequent subgraphs from graph databases. ACM SIGKDD 2004, (2004).
6. Inokuchi A, et al., An apriori-based alorithm for mining frequent substructures from graph data. Proceedings of PKDD2000,(2000).
7. Kashtan. N, et al., Efficient sampling algorithm for estimating subgraph concentrations and detecting network motifs. Bioinformatics, Vol 20 no.11.
8. Kuramochi M. et al., frequent subgraph discovery. Proceedings of 1st IEEE International conference on Data Mining, (2001).
9. Mangan. S, et al., Structure and function of the feed-forward loop network motif. PANS, (2003).
10. McAdams H, et al., A bacterial cell-cycle regulatory network operating in time nad space. Science, (2003).
11. Milo R, et al., Network motifs: simple building blocks of complex networks. Science, 298(5594), (2002).
12. Mota LJ, et al., Control of the arabinose regulon in Bacillus subtills by AraR in vivo: crucial roles of operators, cooperativity and DNA looping. Bacteriol, 183(14), (2001).
13. Nesetril J et al., On the complexity of the subgraph problem. Commen Math, 26, (1985).
14. Nitzan R., et al., Negative autoregulation speeds the response times of transcription networks. JMB, 323, (2003).
15. Ronen M, et al., Assigning numbers to the arrows: parameterizing a gene regulation network by using accurate expression kinetics. PANS, 99, (2002).
16. S. Ott, et al., Superiority of network motifs over optimal networks and an application to the revelation of gene network evolution. Bioinformatics, 21(2), (2005).
17. Shen-Orr S, et al., Network motifs in the transcriptional regulation network of E.coli. Nature Genetics, 31(1) (2002).
18. Yan B, et al., Separation of Ion Types in Tandem Mass Spectrometry Data Interpretation a Graph-Theoretic Approach. 2004 IEEE CSB, (2004).
19. Hyun S. Moon, et al., Architecture of basic building blocks in protein and domain structural interaction networks Bioinformatics. Vol 21 no. 8,(2005).
20. Michihiro Kuramochi et al., Finding Frequent Patterns in a Large Sparse Graph 2004 SIAM Data Mining Conference, (2004).
21. Yeger E, et al., Network motifs in integrated cellular networks of transcription-regulation and protein-protein interaction. PANS, vol 101 no. 16,(2004).
22. Zaslaver M, et al., Just in time transcription programs in metabolic pathways. Nat Genetics, 36, (2004).