Resources for Systems Biology Research

  • Kim Jin-Sik (Metabolic and Biomolecular Engineering National Research Laboratory) ;
  • Yun Hong-Seok (Metabolic and Biomolecular Engineering National Research Laboratory) ;
  • Kim Hyun-Uk (Metabolic and Biomolecular Engineering National Research Laboratory) ;
  • Choi Hyung-Seok (Metabolic and Biomolecular Engineering National Research Laboratory) ;
  • Kim Tae-Yong (Metabolic and Biomolecular Engineering National Research Laboratory) ;
  • Woo Han-Min (Metabolic and Biomolecular Engineering National Research Laboratory) ;
  • Lee Sang-Yup (Metabolic and Biomolecular Engineering National Research Laboratory)
  • Published : 2006.06.01

Abstract

Systems biology has recently become an important research paradigm that is anticipated to decipher the metabolic, regulatory, and signaling networks of complex living organisms on the whole organism level. Thus, various research outputs are being generated, along with the development of many tools and resources for systems biology research. Accordingly, this review provides a comprehensive summary of the current resources and tools for systems biology research that will hopefully be helpful to researchers involved in this field. The resources are categorized into the following five groups: genome information and analysis, transcriptome and proteome databases, metabolic profiling and metabolic control analysis, metabolic and regulatory information, and software for computational systems biology. A summary table and some future perspectives are also provided.

Keywords

References

  1. Bairoch, A. 2000. The ENZYME database in 2000. Nucleic Acids Res. 28: 304-305 https://doi.org/10.1093/nar/28.1.304
  2. Ball, C. A., I. A. Awad, J. Demeter, J. Gollub, J. M. Hebert, T. Hernandez-Boussard, H. Jin, J. C. Matese, M. Nitzberg, F. Wymore, Z. K. Zachariah, P. O. Brown, and G. Sherlock. 2005. The Stanford Microarray Database accommodates additional microarray platforms and data formats. Nucleic Acids Res. 33: D580-D582 https://doi.org/10.1093/nar/gki006
  3. Birney, E., D. Andrews, M. Caccamo, Y. Chen, L. Clarke, G. Coates, T. Cox, F. Cunningham, V. Curwen, T. Cutts, T. Down, R. Durbin, X. M. Fernandez-Suarez, P. Flicek, S. Graf, M. Hammond, J. Herrero, K. Howe, V. Iyer, K. Jekosch, A. Kahari, A. Kasprzyk, D. Keefe, F. Kokocinski, E. Kulesha, D. London, I. Longden, C. Melsopp, P. Meidl, B. Overduin, A. Parker, G. Proctor, A. Prlic, M. Rae, D. Rios, S. Redmond, M. Schuster, I. Sealy, S. Searle, J. Severin, G. Slater, D. Smedley, J. Smith, A. Stabenau, J. Stalker, S. Trevanion, A. Ureta-Vidal, J. Vogel, S. White, C. Woodwark, and T. J. Hubbard. 2006. Ensembl 2006. Nucleic Acids Res. 34: D556-D561 https://doi.org/10.1093/nar/gkj133
  4. Blake, J. A., J. T. Eppig, C. J. Bult, J. A. Kadin, J. E. Richardson, and Mouse Genome Database Group. 2006. The Mouse Genome Database (MGD): Updates and enhancements. Nucleic Acids Res. 34: D562-D567 https://doi.org/10.1093/nar/gkj085
  5. Blinov, M. L., J. R. Faeder, B. Goldstein, and W. S. Hlavacek. 2004. BioNetGen: Software for rule-based modeling of signal transduction based on the interactions of molecular domains. Bioinformatics 20: 3289-3291 https://doi.org/10.1093/bioinformatics/bth378
  6. Caspi, R., H. Foerster, C. A. Fulcher, R. Hopkinson, J. Ingraham, P. Kaipa, M. Krummenacker, S. Paley, J. Pick, S. Y. Rhee, C. Tissier, P. Zhang, and P. D. Karp. 2006. MetaCyc: A multiorganism database of metabolic pathways and enzymes. Nucleic Acids Res. 34: D511-D516 https://doi.org/10.1093/nar/gkj128
  7. Chalkley, R. J., P. R. Baker, L. Huang, K. C. Hansen, N. P. Allen, M. Rexach, and A. L. Burlingame. 2005. Comprehensive analysis of a multidimensional liquid chromatography mass spectrometry dataset acquired on a quadrupole selecting, quadrupole collision cell, time-offlight mass spectrometer: II. New developments in Protein Prospector allow for reliable and comprehensive automatic analysis of large datasets. Mol. Cell Proteomics 4: 1194-1204 https://doi.org/10.1074/mcp.D500002-MCP200
  8. Cheung, K. H., K. White, J. Hager, M. Gerstein, V. Reinke, K. Nelson, P. Masiar, R. Srivastava, Y. Li, J. Li, H. Zhao, J. Li, D. B. Allison, M. Snyder, P. Miller, and K. Williams. 2002. YMD: A microarray database for large-scale gene expression analysis. Proc. AMIA Symp. 140-144
  9. Dhar, P., T. C. Meng, S. Somani, L. Ye, A. Sairam, M. Chitre, Z. Hao, and K. Sakharkar. 2004. Cellware -- A multi-algorithmic software for computational systems biology. Bioinformatics 20: 1319-1321 https://doi.org/10.1093/bioinformatics/bth067
  10. Edgar, R., M. Domrachev, and A. E. Lash. 2002. Gene expression omnibus: NCBI gene expression and hybridization array data repository. Nucleic Acids Res. 30: 207-210 https://doi.org/10.1093/nar/30.1.207
  11. Finn, R. D., J. Mistry, B. Schuster-Bockler, S. Griffiths- Jones, V. Hollich, T. Lassmann, S. Moxon, M. Marshall, A. Khanna, R. Durbin, S. R. Eddy, E. L. Sonnhammer, and A. Bateman. 2006. Pfam: Clans, Web tools and services. Nucleic Acids Res. 34: D247-D251 https://doi.org/10.1093/nar/gkj149
  12. Fleischmann, R. D., M. D. Adams, O. White, R. A. Clayton, E. F. Kirkness, A. R. Kerlavage, C. J. Bult, J. F. Tomb, B. A. Dougherty, J. M. Merrick, et al. 1995. Whole-genome random sequencing and assembly of Haemophilus influenzae Rd. Science 269: 496-512 https://doi.org/10.1126/science.7542800
  13. Garvey, T. D., P. Lincoln, C. J. Pedersen, D. Martin, and M. Johnson. 2003. BioSPICE: Access to the most current computational tools for biologists. OMICS 7: 411-420 https://doi.org/10.1089/153623103322637715
  14. Gasteiger, E., A. Gattiker, C. Hoogland, I. Ivanyi, R. D. Appel, and A. Bairoch. 2003. ExPASy: The proteomics server for in-depth protein knowledge and analysis. Nucleic Acids Res. 31: 3784-3788 https://doi.org/10.1093/nar/gkg563
  15. Gene Ontology Consortium. 2006. The Gene Ontology (GO) project in 2006. Nucleic Acids Res. 34: D322-D326 https://doi.org/10.1093/nar/gkj021
  16. Goto, S., Y. Okuno, M. Hattori, T. Nishioka, and M. Kanehisa. 2002. LIGAND: Database of chemical compounds and reactions in biological pathways. Nucleic Acids Res. 30: 402-404 https://doi.org/10.1093/nar/30.1.402
  17. Hattne, J., D. Fange, and J. Elf. 2005. Stochastic reactiondiffusion simulation with MesoRD. Bioinformatics 21: 2923-2924 https://doi.org/10.1093/bioinformatics/bti431
  18. Hirschman, J. E., R. Balakrishnan, K. R. Christie, M. C. Costanzo, S. S. Dwight, S. R. Engel, D. G. Fisk, E. L. Hong, M. S. Livstone, R. Nash, J. Park, R. Oughtred, M. Skrzypek, B. Starr, C. L. Theesfeld, J. Williams, R. Andrada, G. Binkley, Q. Dong, C. Lane, S. Miyasato, A. Sethuraman, M. Schroeder, M. K. Thanawala, S. Weng, K. Dolinski, D. Botstein, and J. M. Cherry. 2006. Genome Snapshot: A new resource at the Saccharomyces Genome Database (SGD) presenting an overview of the Saccharomyces cerevisiae genome. Nucleic Acids Res. 34: D442-D445 https://doi.org/10.1093/nar/gkj117
  19. Hou, B. K., J. S. Kim, J. H. Jun, D. Y. Lee, Y. W. Kim, S. Chae, M. Roh, Y. H. In, and S. Y. Lee. 2004. BioSilico: An integrated metabolic database system. Bioinformatics 20: 3270-3272 https://doi.org/10.1093/bioinformatics/bth363
  20. Hucka, M., A. Finney, H. M. Sauro, H. Bolouri, J. C. Doyle, H. Kitano, A. P. Arkin, B. J. Bornstein, D. Bray, A. Cornish- Bowden, A. A. Cuellar, S. Dronov, E. D. Gilles, M. Ginkel, V. Gor, I. I. Goryanin, W. J. Hedley, T. C. Hodgman, J. H. Hofmeyr, P. J. Hunter, N. S. Juty, J. L. Kasberger, A. Kremling, U. Kummer, N. Le Novere, L. M. Loew, D. Lucio, P. Mendes, E. Minch, E. D. Mjolsness, Y. Nakayama, M. R. Nelson, P. F. Nielsen, T. Sakurada, J. C. Schaff, B. E. Shapiro, T. S. Shimizu, H. D. Spence, J. Stelling, K. Takahashi, M. Tomita, J. Wagner, J. Wang, and SBML Forum. 2003. The systems biology markup language (SBML): A medium for representation and exchange of biochemical network models. Bioinformatics 19: 524-531 https://doi.org/10.1093/bioinformatics/btg015
  21. Jaiswal, P., J. Ni, I. Yap, D. Ware, W. Spooner, K. Youens- Clark, L. Ren, C. Liang, W. Zhao, K. Ratnapu, B. Faga, P. Canaran, M. Fogleman, C. Hebbard, S. Avraham, S. Schmidt, T. M. Casstevens, E. S. Buckler, L. Stein, and S. McCouch. 2006. Gramene: A bird's eye view of cereal genomes. Nucleic Acids Res. 34: D717-D723 https://doi.org/10.1093/nar/gkj154
  22. Joshi-Tope, G., M. Gillespie, I. Vastrik, P. D'Eustachio, E. Schmidt, B. de Bono, B. Jassal, G. R. Gopinath, G. R. Wu, L. Matthews, S. Lewis, E. Birney, and L. Stein. 2005. Reactome: A knowledge base of biological pathways. Nucleic Acids Res. 33: D428-D432 https://doi.org/10.1093/nar/gki072
  23. Kahraman, A., A. Avramov, L. G. Nashev, D. Popov, R. Ternes, H. D. Pohlenz, and B. Weiss. PhenomicDB: A multi-species genotype/phenotype database for comparative phenomics. Bioinformatics 21: 418-420 https://doi.org/10.1093/bioinformatics/bti010
  24. Kanehisa, M., S. Goto, M. Hattori, K. F. Aoki-Kinoshita, M. Itoh, S. Kawashima, T. Katayama, M. Araki, and M. Hirakawa. 2006. From genomics to chemical genomics: New developments in KEGG. Nucleic Acids Res. 34: D354-D357 https://doi.org/10.1093/nar/gkj102
  25. Kanehisa, M., S. Goto, S. Kawashima, Y. Okuno, and M. Hattori. 2004. The KEGG resource for deciphering the genome. Nucleic Acids Res. 32: D277-D280 https://doi.org/10.1093/nar/gkh063
  26. Keseler, I. M., J. Collado-Vides, S. Gama-Castro, J. Ingraham, S. Paley, I. T. Paulsen, M. Peralta-Gil, and P. D. Karp. 2005. EcoCyc: A comprehensive database resource for Escherichia coli. Nucleic Acids Res. 33: D334-D337 https://doi.org/10.1093/nar/gki108
  27. Kierzek, A. M. 2002. STOCKS: STOChastic kinetic simulations of biochemical systems with Gillespie algorithm. Bioinformatics 18: 470-481 https://doi.org/10.1093/bioinformatics/18.3.470
  28. Klamt, S., J. Stelling, M. Ginkel, and E. D. Gilles. 2003. FluxAnalyzer: Exploring structure, pathways, and flux distributions in metabolic networks on interactive flux maps. Bioinformatics 19: 261-269 https://doi.org/10.1093/bioinformatics/19.2.261
  29. Krummenacker, M., S. Paley, L. Mueller, T. Yan, and P. D. Karp. 2005. Querying and computing with BioCyc databases. Bioinformatics 21: 3454-3455 https://doi.org/10.1093/bioinformatics/bti546
  30. Kurata, H., K. Masaki, Y. Sumida, and R. Iwasaki. 2005. CADLIVE dynamic simulator: Direct link of biochemical networks to dynamic models. Genome Res. 15: 590-600 https://doi.org/10.1101/gr.3463705
  31. Le Novere, N. and T. S. Shimizu. 2001. STOCHSIM: Modelling of stochastic biomolecular processes. Bioinformatics 17: 575-576 https://doi.org/10.1093/bioinformatics/17.6.575
  32. Lee, D. Y., C. Yun, A. Cho, B. K. Hou, S. Park, and S. Y. Lee. 2006. WebCell: A Web-based environment for kinetic modeling and dynamic simulation of cellular networks. Bioinformatics [in press]
  33. Lee, D. Y., H. Yun, S. Park, and S. Y. Lee. 2003. MetaFluxNet: The management of metabolic reaction information and quantitative metabolic flux analysis. Bioinformatics 19: 2144-2146 https://doi.org/10.1093/bioinformatics/btg271
  34. Lee, S. Y., D. Y. Lee, and T. Y. Kim. 2005. Systems biotechnology for strain improvement. Trends Biotechnol. 23: 349-358 https://doi.org/10.1016/j.tibtech.2005.05.003
  35. Lee, Y., J. Tsai, S. Sunkara, S. Karamycheva, G. Pertea, R. Sultana, V. Antonescu, A. Chan, F. Cheung, and J. Quackenbush. 2005. The TIGR gene indices: Clustering and assembling EST and known genes and integration with eukaryotic genomes. Nucleic Acids Res. 33: D71-D74 https://doi.org/10.1093/nar/gni070
  36. Lemer, C., E. Antezana, F. Couche, F. Fays, X. Santolaria, R. Janky, Y. Deville, J. Richelle, and S. J. Wodak. 2004. The aMAZE LightBench: A Web interface to a relational database of cellular processes. Nucleic Acids Res. 32: D443-D448 https://doi.org/10.1093/nar/gkh139
  37. Lloyd, C. M., M. D. Halstead, and P. F. Nielsen. 2004. CellML: Its future, present and past. Prog. Biophys. Mol. Biol. 85: 433-450 https://doi.org/10.1016/j.pbiomolbio.2004.01.004
  38. Lok, L. and R. Brent. 2005. Automatic generation of cellular reaction networks with Moleculizer 1.0. Nat. Biotechnol. 23: 131-136 https://doi.org/10.1038/nbt1054
  39. Ludemann, A., D. Weicht, J. Selbig, and J. Kopka. 2004. PaVESy: Pathway visualization and editing system. Bioinformatics 20: 2841-2844 https://doi.org/10.1093/bioinformatics/bth278
  40. Maglott, D., J. Ostell, K. D. Pruitt, and T. Tatusova. 2005. Entrez gene: Gene-centered information at NCBI. Nucleic Acids Res. 33: D54-D58 https://doi.org/10.1093/nar/gni052
  41. McCarthy, A. A. 2005. Broad Institute: Bringing genomics to real-world medicine. Chem. Biol. 12: 717-718 https://doi.org/10.1016/j.chembiol.2005.07.003
  42. McGinnis, S. and T. L. Madden. 2004. BLAST: At the core of a powerful and diverse set of sequence analysis tools. Nucleic Acids Res. 32: W20-W25 https://doi.org/10.1093/nar/gkh435
  43. Mendes, P. 1997. Biochemistry by numbers: Simulation of biochemical pathways with Gepasi 3. Trends Biochem. Sci. 22: 361-363 https://doi.org/10.1016/S0968-0004(97)01103-1
  44. Mi, H., B. Lazareva-Ulitsky, R. Loo, A. Kejariwal, J. Vandergriff, S. Rabkin, N. Guo, A. Muruganujan, O. Doremieux, M. J. Campbell, H. Kitano, and P. D. Thomas. 2005. The PANTHER database of protein families, subfamilies, functions and pathways. Nucleic Acids Res. 33: D284-D288 https://doi.org/10.1093/nar/gki418
  45. Olivier, B. G. and J. L. Snoep. 2004. Web-based kinetic modelling using JWS online. Bioinformatics 20: 2143-2144 https://doi.org/10.1093/bioinformatics/bth200
  46. Parkinson, H., U. Sarkans, M. Shojatalab, N. Abeygunawardena, S. Contrino, R. Coulson, A. Farne, G. G. Lara, E. Holloway, M. Kapushesky, P. Lilja, G. Mukherjee, A. Oezcimen, T. Rayner, P. Rocca-Serra, A. Sharma, S. Sansone, and A. Brazma. 2005. ArrayExpress -- A public repository for microarray gene expression data at the EBI. Nucleic Acids Res. 33: D553-D555 https://doi.org/10.1093/nar/gki494
  47. Ramsey, S., D. Orrell, and H. Bolouri. 2005. Dizzy: Stochastic simulation of large-scale genetic regulatory networks. J. Bioinform. Comput. Biol. 3: 415-436 https://doi.org/10.1142/S0219720005001132
  48. Rhee, S. Y., W. Beavis, T. Z. Berardini, G. Chen, D. Dixon, A. Doyle, M. Garcia-Hernandez, E. Huala, G. Lander, M. Montoya, N. Miller, L. A. Mueller, S. Mundodi, L. Reiser, J. Tacklind, D. C. Weems, Y. Wu, I. Xu, D. Yoo, J. Yoon, and P. Zhang. 2003. The Arabidopsis Information Resource (TAIR): A model organism database providing a centralized, curated gateway to Arabidopsis biology, research materials and community. Nucleic Acids Res. 31: 224-228 https://doi.org/10.1093/nar/gkg076
  49. Salgado, H., S. Gama-Castro, M. Peralta-Gil, E. Diaz-Peredo, F. Sanchez-Solano, A. Santos-Zavaleta, I. Martinez-Flores, V. Jimenez-Jacinto, C. Bonavides-Martinez, J. Segura-Salazar, A. Martinez-Antonio, and J. Collado-Vides. 2006. RegulonDB (version 5.0): Escherichia coli K-12 transcriptional regulatory network, operon organization, and growth conditions. Nucleic Acids Res. 34: D394-D397 https://doi.org/10.1093/nar/gkj156
  50. Sauro, H. M., M. Hucka, A. Finney, C. Wellock, H. Bolouri, J. Doyle, and H. Kitano. 2003. Next generation simulation tools: The systems biology workbench and BioSPICE integration. OMICS 7: 355-372 https://doi.org/10.1089/153623103322637670
  51. Schomburg, I., A. Chang, C. Ebeling, M. Gremse, C. Heldt, G. Huhn, and D. Schomburg. 2004. BRENDA, the enzyme database: Updates and major new developments. Nucleic Acids Res. 32: D431-D433 https://doi.org/10.1093/nar/gkh081
  52. Shannon, P., A. Markiel, O. Ozier, N. S. Baliga, J. T. Wang, D. Ramage, N. Amin, B. Schwikowski, and T. Ideker. 2003. Cytoscape: A software environment for integrated models of biomolecular interaction networks. Genome Res. 13: 2498-2504 https://doi.org/10.1101/gr.1239303
  53. Shapiro, B. E., A. Levchenko, E. M. Meyerowitz, B. J. Wold, and E. D. Mjolsness. 2003. Cellerator: Extending a computer algebra system to include biochemical arrows for signal transduction simulations. Bioinformatics 19: 677-678 https://doi.org/10.1093/bioinformatics/btg042
  54. Slepchenko, B. M., J. C. Schaff, I. Macara, and L. M. Loew. 2003. Quantitative cell biology with the virtual cell. Trends Cell Biol. 13: 570-576 https://doi.org/10.1016/j.tcb.2003.09.002
  55. Steinhauser, D., B. Usadel, A. Luedemann, O. Thimm, and J. Kopka. 2004. CSB.DB: A comprehensive systemsbiology database. Bioinformatics 20: 3647-3651 https://doi.org/10.1093/bioinformatics/bth398
  56. Takahashi, K., N. Ishikawa, Y. Sadamoto, H. Sasamoto, S. Ohta, A. Shiozawa, F. Miyoshi, Y. Naito, Y. Nakayama, and M. Tomita. 2003. E-Cell 2: Multi-platform E-Cell simulation system. Bioinformatics 19: 1727-1729 https://doi.org/10.1093/bioinformatics/btg221
  57. Tatusov, R. L., D. A. Natale, I. V. Garkavtsev, T. A. Tatusova, U. T. Shankavaram, B. S. Rao, B. Kiryutin, M. Y. Galperin, N. D. Fedorova, and E. V. Koonin. 2001. The COG database: New developments in phylogenetic classification of proteins from complete genomes. Nucleic Acids Res. 29: 22-28 https://doi.org/10.1093/nar/29.1.22
  58. Whetzel, P. L., H. Parkinson, H. C. Causton, L. Fan, J. Fostel, G. Fragoso, L. Game, M. Heiskanen, N. Morrison, P. Rocca-Serra, S. A. Sansone, C. Taylor, J. White, and C. J. Stoeckert Jr. 2006. The MGED Ontology; A resource for semantics-based description of microarray experiments. Bioinformatics [in press]
  59. Wu, C. H., L. S. Yeh, H. Huang, L. Arminski, J. Castro- Alvear, Y. Chen, Z. Hu, P. Kourtesis, R. S. Ledley, B. E. Suzek, C. R. Vinayaka, J. Zhang, and W. C. Barker. 2003. The Protein Information Resource. Nucleic Acids Res. 31: 345-347 https://doi.org/10.1093/nar/gkg040