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BiingFeng Wang, ChungChin Kuo, ShangJu Liu, ChienHsin Lin, "A New Efficient Algorithm for the GeneTeam Problem on General Sequences," IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 9, no. 2, pp. 330344, March/April, 2012.  
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@article{ 10.1109/TCBB.2011.96, author = {BiingFeng Wang and ChungChin Kuo and ShangJu Liu and ChienHsin Lin}, title = {A New Efficient Algorithm for the GeneTeam Problem on General Sequences}, journal ={IEEE/ACM Transactions on Computational Biology and Bioinformatics}, volume = {9}, number = {2}, issn = {15455963}, year = {2012}, pages = {330344}, doi = {http://doi.ieeecomputersociety.org/10.1109/TCBB.2011.96}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }  
RefWorks Procite/RefMan/Endnote  x  
TY  JOUR JO  IEEE/ACM Transactions on Computational Biology and Bioinformatics TI  A New Efficient Algorithm for the GeneTeam Problem on General Sequences IS  2 SN  15455963 SP330 EP344 EPD  330344 A1  BiingFeng Wang, A1  ChungChin Kuo, A1  ShangJu Liu, A1  ChienHsin Lin, PY  2012 KW  Algorithms KW  data structures KW  gene teams KW  comparative genomics KW  conserved gene clusters. VL  9 JA  IEEE/ACM Transactions on Computational Biology and Bioinformatics ER   
[1] R. Agrawal and R. Srikant, “Fast Algorithms for Mining Association Rules in Large Databases,” Proc. 20th Int'l Conf. Very Large Data Bases, pp. 487499, 1994.
[2] M.P. Béal, A. Bergeron, S. Corteel, and M. Raffinot, “An Algorithmic View of Gene Teams,” Theoretical Computer Science, vol. 320, nos. 2/3, pp. 395418, 2004.
[3] A. Bergeron, Y. Gingras, and C. Chauve, “Formal Models of Gene Clusters,” Bioinformatics Algorithms: Techniques and Applications, I. Mandoiu and A. Zelikovskym, ed., Chapter 8, pp. 177202, Wiley, 2008.
[4] A. Bergeron and J. Stoye, “On the Similarity of Sets of Permutations and Its Applications to Genome Comparison,” J. Computational Biology, vol. 13, pp. 13401354, 2006.
[5] G. Blin and J. Stoye, “Finding Nested Common Intervals Efficiently,” J. Computational Biology, vol. 17, no. 9, pp. 11831194, 2010.
[6] T. Dandekar, B. Snel, M. Huynen, and P. Bork, “Conservation of Gene Order: A Fingerprint for Proteins that Physically Interact,” Trends in Biochemical Sciences, vol. 23, pp. 324328, 1998.
[7] G. Didier, “Common Intervals of Two Sequences,” Proc. Third Int'l Workshop Algorithms in Bioinformatics, pp. 1724, 2003.
[8] M.D. Ermolaeva, O. White, and S.L. Salzberg, “Prediction of Operons in Microbial Genomes,” Nucleic Acids Research, vol. 29, no. 5, pp. 12161221, 2001.
[9] X. He and M.H. Goldwasser, “Identifying Conserved Gene Clusters in the Presence of Homology Families,” J. Computational Biology, vol. 12, no. 6, pp. 638656, 2005.
[10] S. Heber and J. Stoye, “Finding All Common Intervals of $k$ Permutations,” Proc. 12th Ann. Symp. Combinatorial Pattern Matching, pp. 207218, 2001.
[11] C.C. Kuo, GeneralGTF, http://venus.cs.nthu.edu.tw/~superiorGeneralGTF.html , 2010.
[12] S. Kim, J.H. Choi, A. Saple, and J. Yang, “A Hybrid Gene Team Model and Its Application to Genome Analysis,” J. Bioinformatics and Computational Biology, vol. 4, no. 2, pp. 171196, 2006.
[13] W.C. Lathe III, B. Snel, and P. Bork, “Gene Context Conservation of a Higher Order than Operons,” Trends in Biochemical Sciences, vol. 25, pp. 474479, 2000.
[14] J. Lawrence, “Selfish Operons: The Evolutionary Impact of Gene Clustering in Prokaryotes and Eukaryotes,” Current Opinion in Genetics & Development, vol. 9, no. 6, pp. 642648, 1999.
[15] X. Lin, X. He, and D. Xin, “Detecting Gene Clusters under Evolutionary Constraint in a Large Number of Genomes,” Bioinformatics, vol. 25, no. 5, pp. 571577, 2009.
[16] N. Luc, J.L. Risler, A. Bergeron, and M. Raffinot, “Gene Teams: A New Formalization of Gene Clusters for Comparative Genomics,” Computational Biology and Chemistry, vol. 27, no. 1, pp. 5967, 2003.
[17] R. Overbeek, M. Fonstein, M. D'Souza, G.D. Pusch, and N. Maltsev, “The Use of Gene Clusters to Infer Functional Coupling,” Proc. Nat'l Academy of Sciences USA, vol. 96, no. 6, pp. 28962901, 1999.
[18] S. Rahmann and G.W. Klau, “Integer Linear Programs for Discovering Approximate Gene Clusters,” Proc. Sixth Workshop Algorithms in Bioinformatics, pp. 298309, 2006.
[19] T. Schmidt and J. Stoye, “Quadratic Time Algorithms for Finding Common Intervals in Two and More Sequences,” Proc. 15th Ann. Symp. Combinatorial Pattern Matching, pp. 347359, 2004.
[20] B. Snel, P. Bork, and M.A. Huynen, “The Identification of Functional Modules from the Genomic Association of Genes,” Proc. Nat'l Academy of Sciences USA, vol. 99, no. 9, pp. 58905895, 2002.
[21] T. Uno and M. Yagiura, “Fast Algorithms to Enumerate All Common Intervals of Two Permutations,” Algorithmica, vol. 26, no. 2, pp. 290309, 2000.
[22] B.F. Wang and C.H. Lin, “Improved Algorithms for Finding Gene Teams and Constructing Gene Team Trees,” IEEE/ACM Trans. Computational Biology and Bioinformatics, vol. 8, no. 5, pp. 12581272, Sept./Oct. 2011.
[23] M. Zhang and H.W. Leong, “Gene Team Tree: A Hierarchical Representation of Gene Teams for All Gap Lengths,” J. Computational Biology, vol. 16, no. 10, pp. 13831398, 2009.