메뉴 건너뛰기




Volumn , Issue , 2012, Pages 167-172

Aligning protein-protein interaction networks using random neural networks

Author keywords

protein interaction network alignment; random neural network

Indexed keywords

GLOBAL ALIGNMENT; PROTEIN INTERACTION NETWORKS; PROTEIN-PROTEIN INTERACTION NETWORKS; RANDOM NEURAL NETWORK; SEQUENCE HOMOLOGY;

EID: 84872545958     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/BIBM.2012.6392664     Document Type: Conference Paper
Times cited : (14)

References (46)
  • 1
    • 33748257786 scopus 로고    scopus 로고
    • Græmlin: General and robust alignment of multiple large interaction networks
    • J. Flannick, A. Novak, B. S. Srinivasan, H. H. McAdams, and S. Batzoglou, "Græmlin: General and robust alignment of multiple large interaction networks," Genome Res., vol. 16, no. 9, pp. 1169-1181, 2006.
    • (2006) Genome Res. , vol.16 , Issue.9 , pp. 1169-1181
    • Flannick, J.1    Novak, A.2    Srinivasan, B.S.3    McAdams, H.H.4    Batzoglou, S.5
  • 2
    • 47249149365 scopus 로고    scopus 로고
    • Automatic parameter learning for multiple network alignment
    • Proceedings of the 12th annual international conference on Research in computational molecular biology, ser. Springer- Verlag
    • J. Flannick, A. Novak, C. B. Do, B. S. Srinivasan, and S. Batzoglou, "Automatic parameter learning for multiple network alignment," in Proceedings of the 12th annual international conference on Research in computational molecular biology, ser. RECOMB'08. Springer-Verlag, 2008, pp. 214-231.
    • (2008) RECOMB'08 , pp. 214-231
    • Flannick, J.1    Novak, A.2    Do, C.B.3    Srinivasan, B.S.4    Batzoglou, S.5
  • 4
    • 77955499935 scopus 로고    scopus 로고
    • Optimal network alignment with graphlet degree vectors
    • [Online]. Available
    • T. Milenković, W. L. L. Ng, W. Hayes, and N. Przulj, "Optimal network alignment with graphlet degree vectors." Cancer informatics, vol. 9, pp. 121-137, 2010. [Online]. Available: http://www.ncbi.nlm.nih.gov/pmc/ articles/PMC2901631/
    • (2010) Cancer Informatics , vol.9 , pp. 121-137
    • Milenković, T.1    Ng, W.L.L.2    Hayes, W.3    Przulj, N.4
  • 5
    • 79955751671 scopus 로고    scopus 로고
    • Integrative network alignment reveals large regions of global network similarity in yeast and human
    • May
    • O. Kuchaiev and N. Pržulj, "Integrative network alignment reveals large regions of global network similarity in yeast and human," Bioinformatics, vol. 27, no. 10, pp. 1390-1396, May 2011.
    • (2011) Bioinformatics , vol.27 , Issue.10 , pp. 1390-1396
    • Kuchaiev, O.1    Pržulj, N.2
  • 6
    • 51349087811 scopus 로고    scopus 로고
    • Global alignment of multiple protein interaction networks with application to functional orthology detection
    • R. Singh, J. Xu, and B. Berger, "Global alignment of multiple protein interaction networks with application to functional orthology detection," PNAS, vol. 105, no. 35, pp. 12 763-12 768, 2008.
    • (2008) PNAS , vol.105 , Issue.35 , pp. 12763-12768
    • Singh, R.1    Xu, J.2    Berger, B.3
  • 7
    • 66349108229 scopus 로고    scopus 로고
    • Isorankn: Spectral methods for global alignment of multiple protein networks
    • C.-S. Liao, K. Lu, M. Baym, R. Singh, and B. Berger, "Isorankn: spectral methods for global alignment of multiple protein networks," Bioinformatics, vol. 25, no. 12, pp. i253-i258, 2009.
    • (2009) Bioinformatics , vol.25 , Issue.12
    • Liao, C.-S.1    Lu, K.2    Baym, M.3    Singh, R.4    Berger, B.5
  • 8
    • 66349124837 scopus 로고    scopus 로고
    • Domain-oriented edge-based alignment of protein interaction networks
    • X. Guo and A. J. Hartemink, "Domain-oriented edge-based alignment of protein interaction networks," Bioinformatics, vol. 25, no. 12, pp. i240-1246, 2009.
    • (2009) Bioinformatics , vol.25 , Issue.12
    • Guo, X.1    Hartemink, A.J.2
  • 9
    • 34547840254 scopus 로고    scopus 로고
    • Identification of functional modules from conserved ancestral protein protein interactions
    • J. Dutkowski and J. Tiuryn, "Identification of functional modules from conserved ancestral protein protein interactions," Bioinformatics, vol. 23, no. 13, pp. i149-158, 2007.
    • (2007) Bioinformatics , vol.23 , Issue.13
    • Dutkowski, J.1    Tiuryn, J.2
  • 10
    • 84860471091 scopus 로고    scopus 로고
    • PINALOG: A novel approach to align protein interaction networksimplications for complex detection and function prediction
    • May
    • H. T. T. Phan and M. J. E. Sternberg, "PINALOG: a novel approach to align protein interaction networksimplications for complex detection and function prediction," Bioinformatics, vol. 28, no. 9, pp. 1239-1245, May 2012.
    • (2012) Bioinformatics , vol.28 , Issue.9 , pp. 1239-1245
    • Phan, H.T.T.1    Sternberg, M.J.E.2
  • 11
    • 0001373628 scopus 로고
    • Random neural networks with positive and negative signals and product form solution
    • E. Gelenbe, "Random neural networks with positive and negative signals and product form solution," Neural Computation, vol. 1, no. 4, pp. 502-510, 1989.
    • (1989) Neural Computation , vol.1 , Issue.4 , pp. 502-510
    • Gelenbe, E.1
  • 13
    • 0033871374 scopus 로고    scopus 로고
    • Video quality and traffic qos in learning-based subsampled and receiver-interpolated video sequences
    • C. Cramer and E. Gelenbe, "Video quality and traffic qos in learning-based subsampled and receiver-interpolated video sequences," IEEE Journal on Selected Areas in Communications, vol. 18, no. 2, pp. 150-167, 2000.
    • (2000) IEEE Journal on Selected Areas in Communications , vol.18 , Issue.2 , pp. 150-167
    • Cramer, C.1    Gelenbe, E.2
  • 14
    • 0031999425 scopus 로고    scopus 로고
    • Learning neural networks for detection and classification of synchronous recurrent transient signals
    • E. Gelenbe, K. Harmanci, and J. Krolik, "Learning neural networks for detection and classification of synchronous recurrent transient signals," Signal processing, vol. 64, no. 3, pp. 233-247, 1998.
    • (1998) Signal Processing , vol.64 , Issue.3 , pp. 233-247
    • Gelenbe, E.1    Harmanci, K.2    Krolik, J.3
  • 15
    • 0030270952 scopus 로고    scopus 로고
    • Neural network methods for volumnetric magnetic resonance imaging of the human brain
    • E. Gelenbe, T. Feng, and K. Krishnan, "Neural network methods for volumnetric magnetic resonance imaging of the human brain," Proceedings of the IEEE, vol. 84, no. 10, pp. 1488-1496, 1996.
    • (1996) Proceedings of the IEEE , vol.84 , Issue.10 , pp. 1488-1496
    • Gelenbe, E.1    Feng, T.2    Krishnan, K.3
  • 16
    • 55449106994 scopus 로고    scopus 로고
    • Synchronized interactions in spiked neuronal networks
    • E. Gelenbe and S. Timotheou, "Synchronized interactions in spiked neuronal networks," The Computer Journal, vol. 51, no. 6, pp. 723-730, 2008.
    • (2008) The Computer Journal , vol.51 , Issue.6 , pp. 723-730
    • Gelenbe, E.1    Timotheou, S.2
  • 17
    • 67650079730 scopus 로고    scopus 로고
    • Steps toward self-aware networks
    • E. Gelenbe, "Steps toward self-aware networks," Communications ACM, vol. 52, no. 7, pp. 66-75, 2009.
    • (2009) Communications ACM , vol.52 , Issue.7 , pp. 66-75
    • Gelenbe, E.1
  • 18
    • 0026243013 scopus 로고
    • Global behavior of homogeneous random neural systems
    • E. Gelenbe and A. Stafylopatis, "Global behavior of homogeneous random neural systems," Applied Mathematical Modelling, vol. 15, no. 10, pp. 534-541, 1991.
    • (1991) Applied Mathematical Modelling , vol.15 , Issue.10 , pp. 534-541
    • Gelenbe, E.1    Stafylopatis, A.2
  • 19
    • 34548854836 scopus 로고    scopus 로고
    • Steady-state solution of probabilistic gene regulatory networks
    • E. Gelenbe, "Steady-state solution of probabilistic gene regulatory networks," Physical Review E, vol. 76, no. 3, pp. 031 903+, 2007.
    • (2007) Physical Review E , vol.76 , Issue.3 , pp. 031903
    • Gelenbe, E.1
  • 20
    • 71549166029 scopus 로고    scopus 로고
    • Anomaly detection in gene expression via stochastic models of gene regulatory networks
    • H. Kim and E. Gelenbe, "Anomaly detection in gene expression via stochastic models of gene regulatory networks," BMC Genomics, vol. 10, no. Suppl 3, p. S26, 2009.
    • (2009) BMC Genomics , vol.10 , Issue.SUPPL. 3
    • Kim, H.1    Gelenbe, E.2
  • 21
    • 0033369033 scopus 로고    scopus 로고
    • Exploiting the past and the future in protein secondary structure prediction
    • Nov.
    • P. Baldi, S. Brunak, P. Frasconi, G. Soda, and G. Pollastri, "Exploiting the past and the future in protein secondary structure prediction," Bioinformatics, vol. 15, no. 11, pp. 937-946, Nov. 1999.
    • (1999) Bioinformatics , vol.15 , Issue.11 , pp. 937-946
    • Baldi, P.1    Brunak, S.2    Frasconi, P.3    Soda, G.4    Pollastri, G.5
  • 22
    • 0036568279 scopus 로고    scopus 로고
    • Improving the prediction of protein secondary structure in three and eight classes using recurrent neural networks and profiles
    • G. Pollastri, D. Przybylski, B. Rost, and P. Baldi, "Improving the prediction of protein secondary structure in three and eight classes using recurrent neural networks and profiles," Proteins, vol. 47, no. 2, pp. 228-235, 2002.
    • (2002) Proteins , vol.47 , Issue.2 , pp. 228-235
    • Pollastri, G.1    Przybylski, D.2    Rost, B.3    Baldi, P.4
  • 23
    • 17844392864 scopus 로고    scopus 로고
    • Combining prediction of secondary structure and solvent accessibility in proteins
    • May
    • R. Adamczak, A. Porollo, and J. Meller, "Combining prediction of secondary structure and solvent accessibility in proteins," Proteins: Structure, Function, and Bioinformatics, vol. 59, no. 3, pp. 467-475, May 2005.
    • (2005) Proteins: Structure, Function, and Bioinformatics , vol.59 , Issue.3 , pp. 467-475
    • Adamczak, R.1    Porollo, A.2    Meller, J.3
  • 24
    • 33745610096 scopus 로고    scopus 로고
    • A two-stage approach for improved prediction of residue contact maps
    • Mar.
    • A. Vullo, I. Walsh, and G. Pollastri, "A two-stage approach for improved prediction of residue contact maps." BMC Bioinformatics, vol. 7, no. 1, Mar. 2006.
    • (2006) BMC Bioinformatics , vol.7 , Issue.1
    • Vullo, A.1    Walsh, I.2    Pollastri, G.3
  • 25
    • 0010357963 scopus 로고
    • Dynamical random neural approach to the traveling salesman problem
    • E. Gelenbe, V. Koubi, and F. Pekegrin, "Dynamical random neural approach to the traveling salesman problem," ELEKTRIK, vol. 2, no. 2, pp. 1-10, 1994.
    • (1994) ELEKTRIK , vol.2 , Issue.2 , pp. 1-10
    • Gelenbe, E.1    Koubi, V.2    Pekegrin, F.3
  • 27
    • 0343266993 scopus 로고
    • Une généralisation probabiliste du problème sat
    • E. Gelenbe, "Une généralisation probabiliste du problème sat," Comptes-Rendus Acad. Sci., vol. 313, no. II, pp. 339- 342, 1992.
    • (1992) Comptes-Rendus Acad. Sci. , vol.313 , Issue.2 , pp. 339-342
    • Gelenbe, E.1
  • 28
    • 0000428263 scopus 로고
    • Learning in the recurrent random network
    • E. Gelenbe, "Learning in the recurrent random network," Neural Computation, no. 4, pp. 154-164, 1993.
    • (1993) Neural Computation , Issue.4 , pp. 154-164
    • Gelenbe, E.1
  • 29
    • 21344486418 scopus 로고
    • G-networks: A unifying model for neural and queueing networks
    • E. Gelenbe, "G-networks: A unifying model for neural and queueing networks," Annals of Operations Research, vol. 48, no. 5, pp. 433-461, 1994.
    • (1994) Annals of Operations Research , vol.48 , Issue.5 , pp. 433-461
    • Gelenbe, E.1
  • 31
    • 0033561945 scopus 로고    scopus 로고
    • Random neural networks with multiple classes of signals
    • E. Gelenbe and J. Fourneau, "Random neural networks with multiple classes of signals," Neural Computation, vol. 11, no. 4, pp. 953-963, 1999.
    • (1999) Neural Computation , vol.11 , Issue.4 , pp. 953-963
    • Gelenbe, E.1    Fourneau, J.2
  • 32
    • 0000428263 scopus 로고
    • Learning in the Recurrent Random Neural Network
    • Jan.
    • E. Gelenbe, "Learning in the Recurrent Random Neural Network," Neural Computation, vol. 5, no. 1, pp. 154-164, Jan. 1993.
    • (1993) Neural Computation , vol.5 , Issue.1 , pp. 154-164
    • Gelenbe, E.1
  • 35
    • 33645821454 scopus 로고    scopus 로고
    • Assessing semantic similarity measures for the characterization of human regulatory pathways
    • X. Guo, R. Liu, C. D. Shriver, H. Hu, and M. N. Liebman, "Assessing semantic similarity measures for the characterization of human regulatory pathways," Bioinformatics, vol. 22, no. 8, pp. 967-973, 2006.
    • (2006) Bioinformatics , vol.22 , Issue.8 , pp. 967-973
    • Guo, X.1    Liu, R.2    Shriver, C.D.3    Hu, H.4    Liebman, M.N.5
  • 36
    • 33748335463 scopus 로고    scopus 로고
    • A new measure for functional similarity of gene products based on gene ontology
    • A. Schlicker, F. Domingues, J. Rahnenfuhrer, and T. Lengauer, "A new measure for functional similarity of gene products based on gene ontology," BMC Bioinformatics, vol. 7, no. 1, p. 302, 2006.
    • (2006) BMC Bioinformatics , vol.7 , Issue.1 , pp. 302
    • Schlicker, A.1    Domingues, F.2    Rahnenfuhrer, J.3    Lengauer, T.4
  • 37
    • 58149312546 scopus 로고    scopus 로고
    • Evaluation of go-based functional similarity measures using s. cerevisiae protein interaction and expression profile data
    • T. Xu, L. Du, and Y. Zhou, "Evaluation of go-based functional similarity measures using s. cerevisiae protein interaction and expression profile data," BMC Bioinformatics, vol. 9, no. 1, p. 472, 2008.
    • (2008) BMC Bioinformatics , vol.9 , Issue.1 , pp. 472
    • Xu, T.1    Du, L.2    Zhou, Y.3
  • 42
    • 38549159946 scopus 로고    scopus 로고
    • FunSimMat: A comprehensive functional similarity database
    • A. Schlicker and M. Albrecht, "FunSimMat: a comprehensive functional similarity database," Nucleic Acids Research, vol. 36, no. suppl 1, pp. D434-439, 2008.
    • (2008) Nucleic Acids Research , vol.36 , Issue.SUPPL. 1
    • Schlicker, A.1    Albrecht, M.2
  • 43
  • 44
    • 79551587720 scopus 로고    scopus 로고
    • Cytoscape 2.8: New features for data integration and network visualization
    • Feb.
    • M. E. Smoot, K. Ono, J. Ruscheinski, P.-L. L. Wang, and T. Ideker, "Cytoscape 2.8: new features for data integration and network visualization." Bioinformatics, vol. 27, no. 3, pp. 431-432, Feb. 2011.
    • (2011) Bioinformatics , vol.27 , Issue.3 , pp. 431-432
    • Smoot, M.E.1    Ono, K.2    Ruscheinski, J.3    Wang, P.-L.L.4    Ideker, T.5
  • 45
    • 84941871856 scopus 로고
    • The Kolmogorov-Smirnov test for goodness of fit
    • F. J. Massey, "The Kolmogorov-Smirnov test for goodness of fit," Journal of the American Statistical Association, vol. 46, no. 253, pp. 68-78, 1951.
    • (1951) Journal of the American Statistical Association , vol.46 , Issue.253 , pp. 68-78
    • Massey, F.J.1
  • 46
    • 70349193233 scopus 로고    scopus 로고
    • Fast and Accurate Alignment of Multiple Protein Networks
    • M. Kalaev, V. Bafna, and R. Sharan, " Fast and Accurate Alignment of Multiple Protein Networks," Journal of Computational Biology, vol. 16, pp. 989-999, 2009.
    • (2009) Journal of Computational Biology , vol.16 , pp. 989-999
    • Kalaev, M.1    Bafna, V.2    Sharan, R.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.