Scientific Publications

Genomic Object Net was the research version of Cell Illustrator in the University of Tokyo. When Cell Illustrator is cited, please cite the literature, Genomic Object Net:I. A platform for modeling and simulating biopathways, Applied Bioinformatics 2:181-184(2004).

• Nagasaki M, Saito A, Jeong E, Li C, Kojima K, Ikeda E, Miyano S, Cell Illustrator 4.0: A computational platform for systems biology, In Silico Biol, 2010; 10:0002

• Li C*, Nagasaki M*, Ueno K, Miyano S. Simulation-based model checking approach to cell fate specification during Caenorhabditis elegans vulval development by hybrid functional Petri net with extension. BMC Systems Biology 2009; 3:42. *Equal contributor Go to article
• Sato Y, Hashiguchi Y, Nishida M. Evolution of multiple phosphodiesterase isoforms in stickleback involved in cAMP signal transduction pathway. BMC Systems Biology 2009; 3:23

• Jeong E, Nagasaki M, Miyano S. Rule-based reasoning for system dynamics in cell systems. Genome Informatics 20: 25-36 (2008).
• Nagasaki M, Saito A, Li C, Jeong E, Miyano S. Systematic reconstruction of TRANSPATH data into Cell System Markup Language. BMC Systems Biology. 2008; 2:53.
• Kojima K, Nagasaki M, Miyano S. Fast grid layout algorithm for biological networks with sweep calculation. Bioinformatics. 2008; 24(12):1433-41.

• Jeong E*, Nagasaki M*, Saito A, Miyano S. Cell System Ontology: Representation for modeling, visualizing, and simulating biological pathways. In Silico Biology. 2007; 7(6):623-638. *Equal contributor
• Jeong E, Nagasaki M, Miyano S. Conversion from BioPAX to CSO for System Dynamics and Visualization of Biological Pathway. Genome Informatics. 2007; 18: 225-236.
• Kojima K*, Nagasaki M*, Jeong E, Kato M, Miyano S. An efficient grid layout algorithm for biological networks utilizing various biological attributes. BMC Bioinformatics. 2007; 8:76. *Equal contributor

• Tasaki S, Nagasaki M, Oyama M, Hata H, Ueno K, Yoshida R, Higuchi T, Sugano S, Miyano S.
  Modeling and Estimation of Dynamic EGFR Pathway by Data Assimilation Approach Using Time Series Proteomic Data.
  Genome Informatics. 2006; 17(2): 226-238.(.pdf)
• Matsuno H, Li C, Miyano S.
  Petri Net based description for systematic understanding of biological pathways.
  IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences. 2006; 89-A: 3166-3174.
• Nagasaki M, Yamaguchi R, Yoshida R, Imoto S, Doi A, Tamada Y, Matsuno H, Miyano S, Higuchi T.
  Genomic data assimilation for estimating hybrid functional Petri net from time-course gene expression data.
  Genome Informatics. 2006; 17(1): 46-61.(.pdf)
• Doi A, Nagasaki M, Ueno K, Matsuno H, Miyano S.
  A combined pathway to simulate CDK-dependent phosphorylation and ARF-dependent stabilization for p53 transcriptional activity.
  Genome Informatics. 2006; 17(1): 112-23.(.pdf)
• Saito A, Nagasaki M, Doi A, Ueno K, Miyano S.
  Cell fate simulation model of gustatory neurons with microRNAs double-negative feedback loop by hybrid function Petri net with extension.
  Genome Informatics. 2006; 17(1): 100-11.(.pdf)
• Matsuno H, Inouye ST, Okitsu Y, Fujii Y, Miyano S.
  A new regulatory interaction suggested by simulations for circadian genetic control mechanism in mammals.
  Journal of bioinformatics and computational biology. 2006; 4(1): 139-53.(PubMed_16568547)
• Doi A, Nagasaki M, Matsuno H, Miyano S.
  Simulation-based validation of the p53 transcriptional activity with hybrid functional Petri net.
  In Silico Biology. 2006; 6(1-2): 0001.(PubMed_16789909)(.html)
• Nagasaki M, Doi A, Matsuno H, Miyano S.
  Computational modeling of biological processes with Petri Net-based architecture.
  Bioinformatics Technologies (Yi-Ping Phoebe Chen (Ed.)). Springer. 2005; 179-242.
• Nagasaki M, Doi A, Matsuno H, Miyano S.
  Petri Net Based Description and Modeling of Biologinal Pathways.
  Algebraic Biology 2005 - Computer Algebra in Biology, H. Anai and K. Horimoto, eds., Universal Academy Press, Inc., Tokyo. 2005; 19-31.
• Nagasaki M, Doi A, Matsuno H, Miyano S.
  Software for Pathway Modeling and Simulation – From Bench to Computer.
  Asia Pacific Biotech News, World Scientific Publishing Co., Singapore. 2005.
• Kato M, Nagasaki M, Doi A , Miyano S.
  Automatic Drawing of Biological Networks Using Cross Cost and Subcomponent Data.
  Genome Informatics. 2005; 16(2): 22-31.(PubMed_16901086)(.pdf)
• Kitakaze H, Matsuno H, Ikeda N.
  Prediction of debacle points for robustness of biological pathways by using recurrent neural networks.
  Genome Informatics. 2005; 16(1): 192-202.(PubMed_16362922)(.pdf)
• Li C, Suzuki S, Ge Qi-Wei, Nakata M, Matsuno H, Miyano S.
  On modeling and analyzing signaling pathways with inhibitory interactions based on Petri net, Proc.
  The 2005 Internatinal Joint Conference of InCoB, AASBi and KSBI (BIOINFO2005). 2005; 348-53.
• Nagasaki M, Doi A, Matsuno H, Miyano S.
  A versatile Petri net based architecture for modeling and simulation of complex biological processes.
  Genome Informatics. 2004; 15(1): 180-97.(PubMed_15712121)(.pdf)
• Nagasaki M.
  A Platform for Biopathway Modeling/Simulation and Recreating biopathway databases towards simulation.
  Ph.D Thesis, The University of Tokyo. 2004.
• Nagasaki M, Doi A, Matsuno H, Miyano S.
  Integrating biopathway databases for large-scale modeling and simulation.
  The Second Asia-Pacific Bioinformatics Conferences, Volume 29 of Conferences in Research and Practice in Information Technology, Australian Computer Society. 2004; 43-52.
• Doi A, Fujita S, Matsuno H, Nagasaki M, Miyano S.
  Constructing biological pathway models with hybrid functional Petri nets.
  In Silico Biology. 2004; 4(3): 271-91.(PubMed_15724280)(.html)
• Matsui M, Fujita S, Suzuki S, Matsuno H, Miyano S.
  Simulated Cell Division Processes of the Xenopus Cell Cycle Pathway by Genomic Object Net.
  Journal of Integrative Bioinformatics. 2004; 0001.(.pdf)
• Fujita S, Matsui M, Matsuno H, Miyano S.
  Modeling and simulation of fission yeast cell cycle on hybrid functional Petri net.
  IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences. 2004; E87-A(11): 2919-28.
• Matsuno H, Murakami R, Yamane R, Yamasaki N, Fujita S, Yoshimori H, Miyano S.
  Boundary formation by notch signaling in Drosophila multicellular systems: experimental observations and a gene network modeling by Genomic Object Net.
  Pacific Symposium on Biocomputing. 2003: 152-63.(PubMed_12603025)(.pdf)
• Nagasaki M, Doi A, Matsuno H, Miyano S.
  Recreating biopathway databases towards simulation. In: Computational Methods in Systems Biology.
  Lecture Notes in Computer Science. 2003; 2602: 191-2.
• Matsuno H, Tanaka Y, Aoshima H, Doi A, Matsui M, Miyano S.
  Biopathways Representation and Simulation on Hybrid Functional Petri Net.
  In Silico Biology. 2003; 3(3): 389-404.(PubMed_12954096)(.html)
• Nagasaki M, Doi A, Matsuno H, Miyano S.
  Genomic Object Net: a platform for modeling and simulating biopathways.
  Applied Bioinformatics. 2003; 2: 181-4.(PubMed_15130806)
• Doi A, Nagasaki M, Fujita S, Matsuno H, Miyano S.
  Genomic Object Net: II. Modeling biopathways by hybrid functional Petri net with extension.
  Applied Bioinformatics. 2003; 2: 185-8.
• Doi A, Matsuno H, Matsui M, Hirata Y, Miyano S.
  Simulation of biological systems by hybrid Petri net with an enhancement. Proc.
  The International Conference on Fundamentals of Electronics, Communications and Computer Science 2002. 2002; S5: 13-8.
• Matsuno H, Doi A, Hirata Y, Miyano S.
  XML Documentation of Biopathways and Their Simulations in Genomic Object Net.
  Genome Informatics. 2001; 12: 54-62.(.pdf)
• Matsuno H, Doi A, Drath R, Miyano S.
  Genomic Object Net: Hybrid Petri net for describing biological systems.
  Currents in Computational Molecular Biology. 2001; 233-4.
• Matsuno H, Doi A, Nagasaki M, Miyano S.
  Hybrid Petri net representation of gene regulatory network.
  Pacific Symposium on Biocomputing 5. 2000; 341-52.
• Matsuno H, Doi A, Tanaka A, Aoshima H, Hirata Y, Miyano S.
  Genomic Object Net: basic architecture for representing and simulating biopathways.
  

• Wu J, Voit E, Integrative biological systems modeling: challenges and opportunities. Frontiers of Computer Science in China 2009 3(1): 92-100.
• Wu J, Voit E, Hybrid modeling in biochemical systems theory by means of functional petri nets. J Bioinform Comput Biol. 2009 7(1):107-34.
• Hardy S, Robillard PN, Petri net-based method for the analysis of the dynamics of signal propagation in signaling pathways. Bioinformatics, 2008; 209-217
• Troncale S, Thai F, Camprad D, Vannier JP, Guespin J
  Modeling and simulation with Hybrid Functional Petri Nets of the role of interleukin-6 in human early haematopoiesis.
  Pac Symp Biocomput. 2006; 427-438.
• Koh G, Teong HF, Clement MV, Hsu D, Thiagarajan PS.
  A decompositional approach to parameter estimation in pathway modeling: a case study of the Akt and MAPK pathways and their crosstalk.
  Bioinformatics. 2006; 22(14): e271-80.

Please email to csmlweb at edelweiss.hgc.jp, if you know other publications.