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Default ordering is done according to Pathway Name.Table header can be used for changing the default ordering. indicates that ordering is done according to ascending or descending order.Entries are color tagged depending on Network or Pathway ![]() |
| Pathway Name Pathway No. | Accession Name![]() Accession No. | Accession Type | Pathway statistics | pkc statistics | Source Entry Date | ||||||||||||||||
| 1 | PKC Pathway No. 71 | Synaptic_ Network Accession No. 16 | Network | Molecule = 11 Enzyme = 0 Reaction = 10 | Molecule = 0 Enzyme = 0 Reaction = 0 | Bhalla US and Iyengar R. Science (1999) 283(5400):381-7. ( peer-reviewed publication )/ 2001-12-12 00:00:00 | |||||||||||||||
| Related Pathway: 2, 20, 34, 55, 60, 108, 123, 138, 147, 161, 181, 200, 207, 313, 330, 348, 364, 370, 376, 383, 389, 395, 401, 408, 414 420, 426, 431, 437, 443, 449, 455, 461, 467, 473, 479, 485, 491, 497, 503, 509, 515, 521, 527, 534, 540, 546, 552, 558 564, 570, 576, 582, 588, 594, 600, 606, 612, 618, 624, 630, 636, 642, 648, 654, 660, 666, 672, 678, 685, 691, 698, 703 709, 715, 721, 727, 733, 739, 745, 751, 757, 763, 769, 775, 781, 787, 793, 799, 805, 811, 817, 823, 829, 835, 841, 847 853, 859, 865, 871, 877, 883, 889, 895, 901, 907, 913, 919, 927, 932, 938, 944, 950, 956, 963, 969, 974, 981, 987, 993 999, 1004, 1010, 1016, 1022, 1028, 1034, 1040, 1046, 1052, 1058, 1064, 1104 | |||||||||||||||||||||
| Protein Kinase C. This module represents a weighted average of the alpha, beta and gamma isoforms. It takes inputs from Ca, DAG (Diacyl Glycerol) and AA (arachidonic acid). Regulation parameters are largely from Schaechter and Benowitz 1993 J Neurosci 13(10):4361 who use synaptosomes from mammalian brain and in one paper look at all three inputs. Shinomura et al 1991 PNAS 88:5149-5153 is also a useful source of data and helps to tighten the DAG inputs. General reviews include Azzi et al 1992 Eur J Bioch 208:541 and Nishizuka 1988, Nature 334:661 Concentration info from Kikkawa et al 1982 JBC 257(22):13341 The process of parameterization is described in detail in several places. See Supplementary notes to Bhalla and Iyengar 1999 Science 284:92-96, available at the site http://www.ncbs.res.in/~bhalla/ltploop/pkc_example.html The parameterization is also described in a book chapter: Bhalla, 2000: Simulations of Biochemical Signaling in Computational Neuroscience: Realistic Modeling for Experimentalists. Ed. E. De Schutter. CRC Press. | |||||||||||||||||||||
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| 2 | PKC Pathway No. 138 | PKC_turnover Accession No. 26 | Pathway | Molecule = 19 Enzyme = 1 Reaction = 17 | Molecule = 0 Enzyme = 0 Reaction = 0 | In-house
/ 2002-01-22 00:00:00 | |||||||||||||||
| Related Pathway: 2, 20, 34, 55, 60, 71, 108, 123, 147, 161, 181, 200, 207, 313, 330, 348, 364, 370, 376, 383, 389, 395, 401, 408, 414 420, 426, 431, 437, 443, 449, 455, 461, 467, 473, 479, 485, 491, 497, 503, 509, 515, 521, 527, 534, 540, 546, 552, 558 564, 570, 576, 582, 588, 594, 600, 606, 612, 618, 624, 630, 636, 642, 648, 654, 660, 666, 672, 678, 685, 691, 698, 703 709, 715, 721, 727, 733, 739, 745, 751, 757, 763, 769, 775, 781, 787, 793, 799, 805, 811, 817, 823, 829, 835, 841, 847 853, 859, 865, 871, 877, 883, 889, 895, 901, 907, 913, 919, 927, 932, 938, 944, 950, 956, 963, 969, 974, 981, 987, 993 999, 1004, 1010, 1016, 1022, 1028, 1034, 1040, 1046, 1052, 1058, 1064, 1104 | |||||||||||||||||||||
| This enzyme represents an averaged PKC activity, most closely based on the alpha, beta, and gamma forms. | |||||||||||||||||||||
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| 3 | PKC Pathway No. 200 | PKC_2003 Accession No. 48 | Pathway | Molecule = 11 Enzyme = 0 Reaction = 10 | Molecule = 0 Enzyme = 0 Reaction = 0 | Bhalla US. (2004) Biophys J. 87(2):733-44 .( peer-reviewed publication )/ 2003-04-28 00:00:00 | |||||||||||||||
| Related Pathway: 2, 20, 34, 55, 60, 71, 108, 123, 138, 147, 161, 181, 207, 313, 330, 348, 364, 370, 376, 383, 389, 395, 401, 408, 414 420, 426, 431, 437, 443, 449, 455, 461, 467, 473, 479, 485, 491, 497, 503, 509, 515, 521, 527, 534, 540, 546, 552, 558 564, 570, 576, 582, 588, 594, 600, 606, 612, 618, 624, 630, 636, 642, 648, 654, 660, 666, 672, 678, 685, 691, 698, 703 709, 715, 721, 727, 733, 739, 745, 751, 757, 763, 769, 775, 781, 787, 793, 799, 805, 811, 817, 823, 829, 835, 841, 847 853, 859, 865, 871, 877, 883, 889, 895, 901, 907, 913, 919, 927, 932, 938, 944, 950, 956, 963, 969, 974, 981, 987, 993 999, 1004, 1010, 1016, 1022, 1028, 1034, 1040, 1046, 1052, 1058, 1064, 1104 | |||||||||||||||||||||
| This model consists of receptor-ligand interaction, G-protein activation, Adenylyl cyclase mediated formation of cAMP and activation of PKA in the neuron. Demonstration programs using this model described in Bhalla US. (2004) Biophys J. 87(2):733-44 to generate a dose-response curve using stochastic calculations are available here. | |||||||||||||||||||||
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| 4 | PKC Pathway No. 123 | Osc_Ca_ IP3metabolism Accession No. 24 | Network | Molecule = 13 Enzyme = 1 Reaction = 10 | Molecule = 0 Enzyme = 0 Reaction = 0 | Mishra J, Bhalla US. Biophys J. 2002 Sep;83(3):1298-316. ( peer-reviewed publication )/ 2002-01-08 00:00:00 | |||||||||||||||
| Related Pathway: 2, 20, 34, 55, 60, 71, 108, 138, 147, 161, 181, 200, 207, 313, 330, 348, 364, 370, 376, 383, 389, 395, 401, 408, 414 420, 426, 431, 437, 443, 449, 455, 461, 467, 473, 479, 485, 491, 497, 503, 509, 515, 521, 527, 534, 540, 546, 552, 558 564, 570, 576, 582, 588, 594, 600, 606, 612, 618, 624, 630, 636, 642, 648, 654, 660, 666, 672, 678, 685, 691, 698, 703 709, 715, 721, 727, 733, 739, 745, 751, 757, 763, 769, 775, 781, 787, 793, 799, 805, 811, 817, 823, 829, 835, 841, 847 853, 859, 865, 871, 877, 883, 889, 895, 901, 907, 913, 919, 927, 932, 938, 944, 950, 956, 963, 969, 974, 981, 987, 993 999, 1004, 1010, 1016, 1022, 1028, 1034, 1040, 1046, 1052, 1058, 1064, 1104 | |||||||||||||||||||||
| Protein Kinase C. This module represents a weighted average of the alpha, beta and gamma isoforms. It takes inputs from Ca, DAG (Diacyl Glycerol) and AA (arachidonic acid). Regulation parameters are largely from Schaechter and Benowitz 1993 J Neurosci 13(10):4361 who use synaptosomes from mammalian brain and in one paper look at all three inputs. Shinomura et al 1991 PNAS 88:5149-5153 is also a useful source of data and helps to tighten the DAG inputs. General reviews include Azzi et al 1992 Eur J Bioch 208:541 and Nishizuka 1988, Nature 334:661 Concentration info from Kikkawa et al 1982 JBC 257(22):13341 The process of parameterization is described in detail in several places. See Supplementary notes to Bhalla and Iyengar 1999 Science 284:92-96, available at the site http://www.ncbs.res.in/~bhalla/ltploop/pkc_example.html The parameterization is also described in a book chapter: Bhalla, 2000: Simulations of Biochemical Signaling in Computational Neuroscience: Realistic Modeling for Experimentalists. Ed. E. De Schutter. CRC Press. | |||||||||||||||||||||
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| 5 | PKC Pathway No. 161 | Osc_Ca_ IP3metabolism Accession No. 32 | Network | Molecule = 13 Enzyme = 1 Reaction = 10 | Molecule = 0 Enzyme = 0 Reaction = 0 | Mishra J, Bhalla US. Biophys J. 2002 Sep;83(3):1298-316. ( peer-reviewed publication )/ 2002-04-03 00:00:00 | |||||||||||||||
| Related Pathway: 2, 20, 34, 55, 60, 71, 108, 123, 138, 147, 181, 200, 207, 313, 330, 348, 364, 370, 376, 383, 389, 395, 401, 408, 414 420, 426, 431, 437, 443, 449, 455, 461, 467, 473, 479, 485, 491, 497, 503, 509, 515, 521, 527, 534, 540, 546, 552, 558 564, 570, 576, 582, 588, 594, 600, 606, 612, 618, 624, 630, 636, 642, 648, 654, 660, 666, 672, 678, 685, 691, 698, 703 709, 715, 721, 727, 733, 739, 745, 751, 757, 763, 769, 775, 781, 787, 793, 799, 805, 811, 817, 823, 829, 835, 841, 847 853, 859, 865, 871, 877, 883, 889, 895, 901, 907, 913, 919, 927, 932, 938, 944, 950, 956, 963, 969, 974, 981, 987, 993 999, 1004, 1010, 1016, 1022, 1028, 1034, 1040, 1046, 1052, 1058, 1064, 1104 | |||||||||||||||||||||
| Protein Kinase C. This module represents a weighted average of the alpha, beta and gamma isoforms. It takes inputs from Ca, DAG (Diacyl Glycerol) and AA (arachidonic acid). Regulation parameters are largely from Schaechter and Benowitz 1993 J Neurosci 13(10):4361 who use synaptosomes from mammalian brain and in one paper look at all three inputs. Shinomura et al 1991 PNAS 88:5149-5153 is also a useful source of data and helps to tighten the DAG inputs. General reviews include Azzi et al 1992 Eur J Bioch 208:541 and Nishizuka 1988, Nature 334:661 Concentration info from Kikkawa et al 1982 JBC 257(22):13341 The process of parameterization is described in detail in several places. See Supplementary notes to Bhalla and Iyengar 1999 Science 284:92-96, available at the site http://www.ncbs.res.in/~bhalla/ltploop/pkc_example.html The parameterization is also described in a book chapter: Bhalla, 2000: Simulations of Biochemical Signaling in Computational Neuroscience: Realistic Modeling for Experimentalists. Ed. E. De Schutter. CRC Press. | |||||||||||||||||||||
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| 6 | PKC Pathway No. 108 | NonOsc_Ca_ IP3metabolism Accession No. 23 | Network | Molecule = 13 Enzyme = 1 Reaction = 10 | Molecule = 0 Enzyme = 0 Reaction = 0 | Mishra J, Bhalla US. Biophys J. 2002 Sep;83(3):1298-316. ( peer-reviewed publication )/ 2002-01-07 00:00:00 | |||||||||||||||
| Related Pathway: 2, 20, 34, 55, 60, 71, 123, 138, 147, 161, 181, 200, 207, 313, 330, 348, 364, 370, 376, 383, 389, 395, 401, 408, 414 420, 426, 431, 437, 443, 449, 455, 461, 467, 473, 479, 485, 491, 497, 503, 509, 515, 521, 527, 534, 540, 546, 552, 558 564, 570, 576, 582, 588, 594, 600, 606, 612, 618, 624, 630, 636, 642, 648, 654, 660, 666, 672, 678, 685, 691, 698, 703 709, 715, 721, 727, 733, 739, 745, 751, 757, 763, 769, 775, 781, 787, 793, 799, 805, 811, 817, 823, 829, 835, 841, 847 853, 859, 865, 871, 877, 883, 889, 895, 901, 907, 913, 919, 927, 932, 938, 944, 950, 956, 963, 969, 974, 981, 987, 993 999, 1004, 1010, 1016, 1022, 1028, 1034, 1040, 1046, 1052, 1058, 1064, 1104 | |||||||||||||||||||||
| Protein Kinase C. This module represents a weighted average of the alpha, beta and gamma isoforms. It takes inputs from Ca, DAG (Diacyl Glycerol) and AA (arachidonic acid). Regulation parameters are largely from Schaechter JD, Benowitz LI J Neurosci. 1993 Oct;13(10):4361-71 who use synaptosomes from mammalian brain and in one paper look at all three inputs. Shinomura T et al Proc Natl Acad Sci U S A. 1991 Jun 15;88(12):5149-53 is also a useful source of data and helps to tighten the DAG inputs. General reviews include Azzi A et. al Eur J Biochem. 1992 Sep 15;208(3):547-57 and Nishizuka Y.Nature. 1988 Aug 25;334(6184):661-5. Concentration info from Kikkawa U.et al J Biol Chem. 1982 Nov 25;257(22):13341-8. The process of parameterization is described in detail in several places. See Supplementary notes to Weng G et al, Science. 1999 Apr 2;284(5411):92-6 available at the site http://www.ncbs.res.in/~bhalla/ltploop/ltploop/pkc_example.html. The parameterization is also described in a book chapter: Bhalla, 2000: Simulations of Biochemical Signaling in Computational Neuroscience: Realistic Modeling for Experimentalists. Ed. E. De Schutter. CRC Press. | |||||||||||||||||||||
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| 7 | PKC Pathway No. 147 | NonOsc_Ca_ IP3metabolism Accession No. 31 | Network | Molecule = 13 Enzyme = 1 Reaction = 10 | Molecule = 0 Enzyme = 0 Reaction = 0 | Mishra J, Bhalla US. Biophys J. 2002 Sep;83(3):1298-316. ( peer-reviewed publication )/ 2002-04-03 00:00:00 | |||||||||||||||
| Related Pathway: 2, 20, 34, 55, 60, 71, 108, 123, 138, 161, 181, 200, 207, 313, 330, 348, 364, 370, 376, 383, 389, 395, 401, 408, 414 420, 426, 431, 437, 443, 449, 455, 461, 467, 473, 479, 485, 491, 497, 503, 509, 515, 521, 527, 534, 540, 546, 552, 558 564, 570, 576, 582, 588, 594, 600, 606, 612, 618, 624, 630, 636, 642, 648, 654, 660, 666, 672, 678, 685, 691, 698, 703 709, 715, 721, 727, 733, 739, 745, 751, 757, 763, 769, 775, 781, 787, 793, 799, 805, 811, 817, 823, 829, 835, 841, 847 853, 859, 865, 871, 877, 883, 889, 895, 901, 907, 913, 919, 927, 932, 938, 944, 950, 956, 963, 969, 974, 981, 987, 993 999, 1004, 1010, 1016, 1022, 1028, 1034, 1040, 1046, 1052, 1058, 1064, 1104 | |||||||||||||||||||||
| Protein Kinase C. This module represents a weighted average of the alpha, beta and gamma isoforms. It takes inputs from Ca, DAG (Diacyl Glycerol) and AA (arachidonic acid). Regulation parameters are largely from Schaechter and Benowitz 1993 J Neurosci 13(10):4361 who use synaptosomes from mammalian brain and in one paper look at all three inputs. Shinomura et al 1991 PNAS 88:5149-5153 is also a useful source of data and helps to tighten the DAG inputs. General reviews include Azzi et al 1992 Eur J Bioch 208:541 and Nishizuka 1988, Nature 334:661 Concentration info from Kikkawa et al 1982 JBC 257(22):13341 The process of parameterization is described in detail in several places. See Supplementary notes to Bhalla and Iyengar 1999 Science 284:92-96, available at the site http://www.ncbs.res.in/~bhalla/ltploop/pkc_example.html The parameterization is also described in a book chapter: Bhalla, 2000: Simulations of Biochemical Signaling in Computational Neuroscience: Realistic Modeling for Experimentalists. Ed. E. De Schutter. CRC Press. | |||||||||||||||||||||
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| 8 | PKC Pathway No. 1104 | mTOR_pathway Accession No. 92 | Network | Molecule = 11 Enzyme = 0 Reaction = 10 | Molecule = 0 Enzyme = 0 Reaction = 0 | Jain P, and Bhalla, U.S. PLoS Comput Biol. 2009 Feb;5(2). ( Peer-reviewed publication )/ 2009-02-13 00:00:00 | |||||||||||||||
| Related Pathway: 2, 20, 34, 55, 60, 71, 108, 123, 138, 147, 161, 181, 200, 207, 313, 330, 348, 364, 370, 376, 383, 389, 395, 401, 408 414, 420, 426, 431, 437, 443, 449, 455, 461, 467, 473, 479, 485, 491, 497, 503, 509, 515, 521, 527, 534, 540, 546, 552 558, 564, 570, 576, 582, 588, 594, 600, 606, 612, 618, 624, 630, 636, 642, 648, 654, 660, 666, 672, 678, 685, 691, 698 703, 709, 715, 721, 727, 733, 739, 745, 751, 757, 763, 769, 775, 781, 787, 793, 799, 805, 811, 817, 823, 829, 835, 841 847, 853, 859, 865, 871, 877, 883, 889, 895, 901, 907, 913, 919, 927, 932, 938, 944, 950, 956, 963, 969, 974, 981, 987 993, 999, 1004, 1010, 1016, 1022, 1028, 1034, 1040, 1046, 1052, 1058, 1064 | |||||||||||||||||||||
| This model consists of various sub-modules. They are as follows: 1) BDNF receptor signaling 2) AKT signaling 3) 4E-BP model 4) S6 Kinase model 5) CaMKIII model 6) Protein synthesis model 7) CaM 8) PKC 9) MAPK model. | |||||||||||||||||||||
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| 9 | PKC Pathway No. 34 | mkp1_feedback_ effects Accession No. 4 | Network | Molecule = 11 Enzyme = 0 Reaction = 10 | Molecule = 0 Enzyme = 0 Reaction = 0 | Bhalla US et al. Science (2002) 297(5583):1018-23. ( peer-reviewed publication )/ 2001-11-07 00:00:00 | |||||||||||||||
| Related Pathway: 2, 20, 55, 60, 71, 108, 123, 138, 147, 161, 181, 200, 207, 313, 330, 348, 364, 370, 376, 383, 389, 395, 401, 408, 414 420, 426, 431, 437, 443, 449, 455, 461, 467, 473, 479, 485, 491, 497, 503, 509, 515, 521, 527, 534, 540, 546, 552, 558 564, 570, 576, 582, 588, 594, 600, 606, 612, 618, 624, 630, 636, 642, 648, 654, 660, 666, 672, 678, 685, 691, 698, 703 709, 715, 721, 727, 733, 739, 745, 751, 757, 763, 769, 775, 781, 787, 793, 799, 805, 811, 817, 823, 829, 835, 841, 847 853, 859, 865, 871, 877, 883, 889, 895, 901, 907, 913, 919, 927, 932, 938, 944, 950, 956, 963, 969, 974, 981, 987, 993 999, 1004, 1010, 1016, 1022, 1028, 1034, 1040, 1046, 1052, 1058, 1064, 1104 | |||||||||||||||||||||
| Protein Kinase C. This module represents a weighted average of the alpha, beta and gamma isoforms. It takes inputs from Ca, DAG (Diacyl Glycerol) and AA (arachidonic acid). Regulation parameters are largely from Schaechter and Benowitz 1993 J Neurosci 13(10):4361 who use synaptosomes from mammalian brain and in one paper look at all three inputs. Shinomura et al 1991 PNAS 88:5149-5153 is also a useful source of data and helps to tighten the DAG inputs. General reviews include Azzi et al 1992 Eur J Bioch 208:541 and Nishizuka 1988, Nature 334:661 Concentration info from Kikkawa et al 1982 JBC 257(22):13341 The process of parameterization is described in detail in several places. See Supplementary notes to Bhalla and Iyengar 1999 Science 284:92-96, available at the site http://www.ncbs.res.in/~bhalla/ltploop/pkc_example.html The parameterization is also described in a book chapter: Bhalla, 2000: Simulations of Biochemical Signaling in Computational Neuroscience: Realistic Modeling for Experimentalists. Ed. E. De Schutter. CRC Press. | |||||||||||||||||||||
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| 10 | PKC Pathway No. 207 | MAPK_network_ 2003 Accession No. 50 | Network | Molecule = 11 Enzyme = 0 Reaction = 10 | Molecule = 0 Enzyme = 0 Reaction = 0 | Bhalla US Biophys J. 2004 Aug;87(2):745-53. ( peer-reviewed publication )/ 2003-04-28 00:00:00 | |||||||||||||||
| Related Pathway: 2, 20, 34, 55, 60, 71, 108, 123, 138, 147, 161, 181, 200, 313, 330, 348, 364, 370, 376, 383, 389, 395, 401, 408, 414 420, 426, 431, 437, 443, 449, 455, 461, 467, 473, 479, 485, 491, 497, 503, 509, 515, 521, 527, 534, 540, 546, 552, 558 564, 570, 576, 582, 588, 594, 600, 606, 612, 618, 624, 630, 636, 642, 648, 654, 660, 666, 672, 678, 685, 691, 698, 703 709, 715, 721, 727, 733, 739, 745, 751, 757, 763, 769, 775, 781, 787, 793, 799, 805, 811, 817, 823, 829, 835, 841, 847 853, 859, 865, 871, 877, 883, 889, 895, 901, 907, 913, 919, 927, 932, 938, 944, 950, 956, 963, 969, 974, 981, 987, 993 999, 1004, 1010, 1016, 1022, 1028, 1034, 1040, 1046, 1052, 1058, 1064, 1104 | |||||||||||||||||||||
| This is a network model of many pathways present at the neuronal synapse. The network has properties of temporal tuning as well as steady-state computational properties. In its default form the network is bistable.Bhalla US Biophys J. 2004 Aug;87(2):745-53 | |||||||||||||||||||||
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| 11 | PKC Pathway No. 60 | MAPK_MKP1_ oscillation Accession No. 9 | Network | Molecule = 11 Enzyme = 0 Reaction = 10 | Molecule = 0 Enzyme = 0 Reaction = 0 | Bhalla US, Iyengar R. Chaos (2001) 11(1):221-226. ( peer-reviewed publication )/ 2001-11-08 00:00:00 | |||||||||||||||
| Related Pathway: 2, 20, 34, 55, 71, 108, 123, 138, 147, 161, 181, 200, 207, 313, 330, 348, 364, 370, 376, 383, 389, 395, 401, 408, 414 420, 426, 431, 437, 443, 449, 455, 461, 467, 473, 479, 485, 491, 497, 503, 509, 515, 521, 527, 534, 540, 546, 552, 558 564, 570, 576, 582, 588, 594, 600, 606, 612, 618, 624, 630, 636, 642, 648, 654, 660, 666, 672, 678, 685, 691, 698, 703 709, 715, 721, 727, 733, 739, 745, 751, 757, 763, 769, 775, 781, 787, 793, 799, 805, 811, 817, 823, 829, 835, 841, 847 853, 859, 865, 871, 877, 883, 889, 895, 901, 907, 913, 919, 927, 932, 938, 944, 950, 956, 963, 969, 974, 981, 987, 993 999, 1004, 1010, 1016, 1022, 1028, 1034, 1040, 1046, 1052, 1058, 1064, 1104 | |||||||||||||||||||||
| This model relates to figure 5 in Bhalla US, Iyengar R. Chaos (2001) 11(1):221-226. It includes the model used for figures 2-4 and also has MKP-1 induction by MAPK activity in the synapse. PP2A is set to 0.16 uM and MKP synthesis is varied from 5x to 40 x basal to get a range of interesting behaviours. | |||||||||||||||||||||
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| 12 | PKC Pathway No. 181 | MAPK-bistability -fig1c Accession No. 35 | Network | Molecule = 11 Enzyme = 0 Reaction = 10 | Molecule = 0 Enzyme = 0 Reaction = 0 | Bhalla US et al. Science (2002) 297(5583):1018-23 ( peer-reviewed publication )./ 2002-11-07 00:00:00 | |||||||||||||||
| Related Pathway: 2, 20, 34, 55, 60, 71, 108, 123, 138, 147, 161, 200, 207, 313, 330, 348, 364, 370, 376, 383, 389, 395, 401, 408, 414 420, 426, 431, 437, 443, 449, 455, 461, 467, 473, 479, 485, 491, 497, 503, 509, 515, 521, 527, 534, 540, 546, 552, 558 564, 570, 576, 582, 588, 594, 600, 606, 612, 618, 624, 630, 636, 642, 648, 654, 660, 666, 672, 678, 685, 691, 698, 703 709, 715, 721, 727, 733, 739, 745, 751, 757, 763, 769, 775, 781, 787, 793, 799, 805, 811, 817, 823, 829, 835, 841, 847 853, 859, 865, 871, 877, 883, 889, 895, 901, 907, 913, 919, 927, 932, 938, 944, 950, 956, 963, 969, 974, 981, 987, 993 999, 1004, 1010, 1016, 1022, 1028, 1034, 1040, 1046, 1052, 1058, 1064, 1104 | |||||||||||||||||||||
| Protein Kinase C. This module represents a weighted average of the alpha, beta and gamma isoforms. It takes inputs from Ca, DAG (Diacyl Glycerol) and AA (arachidonic acid). Regulation parameters are largely from Schaechter and Benowitz 1993 J Neurosci 13(10):4361 who use synaptosomes from mammalian brain and in one paper look at all three inputs. Shinomura et al 1991 PNAS 88:5149-5153 is also a useful source of data and helps to tighten the DAG inputs. General reviews include Azzi et al 1992 Eur J Bioch 208:541 and Nishizuka 1988, Nature 334:661 Concentration info from Kikkawa et al 1982 JBC 257(22):13341 The process of parameterization is described in detail in several places. See Supplementary notes to Bhalla and Iyengar 1999 Science 284:92-96, available at the site http://www.ncbs.res.in/~bhalla/ltploop/pkc_example.html The parameterization is also described in a book chapter: Bhalla, 2000: Simulations of Biochemical Signaling in Computational Neuroscience: Realistic Modeling for Experimentalists. Ed. E. De Schutter. CRC Press. | |||||||||||||||||||||
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| 13 | PKC Pathway No. 20 | fig4_synapse Accession No. 3 | Network | Molecule = 11 Enzyme = 0 Reaction = 10 | Molecule = 0 Enzyme = 0 Reaction = 0 | Bhalla US and Iyengar R. Science (1999) 283(5400):381-7. ( peer-reviewed publication )/ 2001-11-07 00:00:00 | |||||||||||||||
| Related Pathway: 2, 34, 55, 60, 71, 108, 123, 138, 147, 161, 181, 200, 207, 313, 330, 348, 364, 370, 376, 383, 389, 395, 401, 408, 414 420, 426, 431, 437, 443, 449, 455, 461, 467, 473, 479, 485, 491, 497, 503, 509, 515, 521, 527, 534, 540, 546, 552, 558 564, 570, 576, 582, 588, 594, 600, 606, 612, 618, 624, 630, 636, 642, 648, 654, 660, 666, 672, 678, 685, 691, 698, 703 709, 715, 721, 727, 733, 739, 745, 751, 757, 763, 769, 775, 781, 787, 793, 799, 805, 811, 817, 823, 829, 835, 841, 847 853, 859, 865, 871, 877, 883, 889, 895, 901, 907, 913, 919, 927, 932, 938, 944, 950, 956, 963, 969, 974, 981, 987, 993 999, 1004, 1010, 1016, 1022, 1028, 1034, 1040, 1046, 1052, 1058, 1064, 1104 | |||||||||||||||||||||
| This is the composite model of 4 kinases: PKC, MAPK, PKA and CaMKII and numerous regulatory pathways involved in synaptic signaling. From Bhalla US and Iyengar R. Science (1999) 283(5400):381-7.This model comes from figure 4 of that paper. Demonstration script files for generating the figures in the paper, including figure 4, are available here. | |||||||||||||||||||||
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| 14 | PKC Pathway No. 2 | fig2_egfr Accession No. 1 | Network | Molecule = 11 Enzyme = 0 Reaction = 10 | Molecule = 0 Enzyme = 0 Reaction = 0 | Bhalla US and Iyengar R. Science (1999) 283(5400):381-7. ( peer-reviewed publication )/ 2001-11-07 00:00:00 | |||||||||||||||
| Related Pathway: 20, 34, 55, 60, 71, 108, 123, 138, 147, 161, 181, 200, 207, 313, 330, 348, 364, 370, 376, 383, 389, 395, 401, 408 414, 420, 426, 431, 437, 443, 449, 455, 461, 467, 473, 479, 485, 491, 497, 503, 509, 515, 521, 527, 534, 540, 546, 552 558, 564, 570, 576, 582, 588, 594, 600, 606, 612, 618, 624, 630, 636, 642, 648, 654, 660, 666, 672, 678, 685, 691, 698 703, 709, 715, 721, 727, 733, 739, 745, 751, 757, 763, 769, 775, 781, 787, 793, 799, 805, 811, 817, 823, 829, 835, 841 847, 853, 859, 865, 871, 877, 883, 889, 895, 901, 907, 913, 919, 927, 932, 938, 944, 950, 956, 963, 969, 974, 981, 987 993, 999, 1004, 1010, 1016, 1022, 1028, 1034, 1040, 1046, 1052, 1058, 1064, 1104 | |||||||||||||||||||||
| This network was used to generate figure 2 in Bhalla US and Iyengar R. Science (1999) 283(5400):381-7. It consists of the MAPK cascade in a feedback loop with PKC, and receives input from the EGFR in the synapse. Demonstration script files for generating the figures in the paper, including figure 2, are available here. | |||||||||||||||||||||
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| 15 | PKC Pathway No. 919 | Ajay_Bhalla_ 2007_ReacDiff3 Accession No. 84 | Network | Molecule = 11 Enzyme = 0 Reaction = 10 | Molecule = 0 Enzyme = 0 Reaction = 0 | Ajay_Bhalla_bistable_model. HFSP Journal. 2007 May;1(1):1-87/ 2006-12-08 00:00:00 | |||||||||||||||
| Related Pathway: 2, 20, 34, 55, 60, 71, 108, 123, 138, 147, 161, 181, 200, 207, 313, 330, 348, 364, 370, 376, 383, 389, 395, 401, 408 414, 420, 426, 431, 437, 443, 449, 455, 461, 467, 473, 479, 485, 491, 497, 503, 509, 515, 521, 527, 534, 540, 546, 552 558, 564, 570, 576, 582, 588, 594, 600, 606, 612, 618, 624, 630, 636, 642, 648, 654, 660, 666, 672, 678, 685, 691, 698 703, 709, 715, 721, 727, 733, 739, 745, 751, 757, 763, 769, 775, 781, 787, 793, 799, 805, 811, 817, 823, 829, 835, 841 847, 853, 859, 865, 871, 877, 883, 889, 895, 901, 907, 913, 927, 932, 938, 944, 950, 956, 963, 969, 974, 981, 987, 993 999, 1004, 1010, 1016, 1022, 1028, 1034, 1040, 1046, 1052, 1058, 1064, 1104 | |||||||||||||||||||||
| This is a 25-compartment reaction-diffusion version of the Ajay_Bhalla_2007_bistable model. The original single-compartment model is repeated 25 times.
In addition, a subset (33 out of 50) molecules can diffuse between compartments. Diffusion is implemented as a reaction between corresponding molecules in neighboring compartments. Here D = 1e-13 m^2/sec (i.e., 0.1 micron^2/sec ) so the kf and kb of this reaction for these 10 micron compartments are both 0.001/sec. The basal calcium level in this model is held at 95 nM which is rather close to threshold for the flip to the active state. This is necessary to sustain active propagation of activation. The stimulus file bis6-propgn_D1e-13_FigEF which was used for the model to replicate Figure 4E and 4F from the paper. | |||||||||||||||||||||
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| 16 | PKC Pathway No. 927 | Ajay_Bhalla_ 2007_ReacDiff3 Accession No. 84 | Network | Molecule = 11 Enzyme = 0 Reaction = 10 | Molecule = 0 Enzyme = 0 Reaction = 0 | Ajay_Bhalla_bistable_model. HFSP Journal. 2007 May;1(1):1-87/ 2006-12-08 00:00:00 | |||||||||||||||
| Related Pathway: 2, 20, 34, 55, 60, 71, 108, 123, 138, 147, 161, 181, 200, 207, 313, 330, 348, 364, 370, 376, 383, 389, 395, 401, 408 414, 420, 426, 431, 437, 443, 449, 455, 461, 467, 473, 479, 485, 491, 497, 503, 509, 515, 521, 527, 534, 540, 546, 552 558, 564, 570, 576, 582, 588, 594, 600, 606, 612, 618, 624, 630, 636, 642, 648, 654, 660, 666, 672, 678, 685, 691, 698 703, 709, 715, 721, 727, 733, 739, 745, 751, 757, 763, 769, 775, 781, 787, 793, 799, 805, 811, 817, 823, 829, 835, 841 847, 853, 859, 865, 871, 877, 883, 889, 895, 901, 907, 913, 919, 932, 938, 944, 950, 956, 963, 969, 974, 981, 987, 993 999, 1004, 1010, 1016, 1022, 1028, 1034, 1040, 1046, 1052, 1058, 1064, 1104 | |||||||||||||||||||||
| This is a 25-compartment reaction-diffusion version of the Ajay_Bhalla_2007_bistable model. The original single-compartment model is repeated 25 times.
In addition, a subset (33 out of 50) molecules can diffuse between compartments. Diffusion is implemented as a reaction between corresponding molecules in neighboring compartments. Here D = 1e-13 m^2/sec (i.e., 0.1 micron^2/sec ) so the kf and kb of this reaction for these 10 micron compartments are both 0.001/sec. The basal calcium level in this model is held at 95 nM which is rather close to threshold for the flip to the active state. This is necessary to sustain active propagation of activation. The stimulus file bis6-propgn_D1e-13_FigEF which was used for the model to replicate Figure 4E and 4F from the paper. | |||||||||||||||||||||
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| 17 | PKC Pathway No. 932 | Ajay_Bhalla_ 2007_ReacDiff3 Accession No. 84 | Network | Molecule = 11 Enzyme = 0 Reaction = 10 | Molecule = 0 Enzyme = 0 Reaction = 0 | Ajay_Bhalla_bistable_model. HFSP Journal. 2007 May;1(1):1-87/ 2006-12-08 00:00:00 | |||||||||||||||
| Related Pathway: 2, 20, 34, 55, 60, 71, 108, 123, 138, 147, 161, 181, 200, 207, 313, 330, 348, 364, 370, 376, 383, 389, 395, 401, 408 414, 420, 426, 431, 437, 443, 449, 455, 461, 467, 473, 479, 485, 491, 497, 503, 509, 515, 521, 527, 534, 540, 546, 552 558, 564, 570, 576, 582, 588, 594, 600, 606, 612, 618, 624, 630, 636, 642, 648, 654, 660, 666, 672, 678, 685, 691, 698 703, 709, 715, 721, 727, 733, 739, 745, 751, 757, 763, 769, 775, 781, 787, 793, 799, 805, 811, 817, 823, 829, 835, 841 847, 853, 859, 865, 871, 877, 883, 889, 895, 901, 907, 913, 919, 927, 938, 944, 950, 956, 963, 969, 974, 981, 987, 993 999, 1004, 1010, 1016, 1022, 1028, 1034, 1040, 1046, 1052, 1058, 1064, 1104 | |||||||||||||||||||||
| This is a 25-compartment reaction-diffusion version of the Ajay_Bhalla_2007_bistable model. The original single-compartment model is repeated 25 times.
In addition, a subset (33 out of 50) molecules can diffuse between compartments. Diffusion is implemented as a reaction between corresponding molecules in neighboring compartments. Here D = 1e-13 m^2/sec (i.e., 0.1 micron^2/sec ) so the kf and kb of this reaction for these 10 micron compartments are both 0.001/sec. The basal calcium level in this model is held at 95 nM which is rather close to threshold for the flip to the active state. This is necessary to sustain active propagation of activation. The stimulus file bis6-propgn_D1e-13_FigEF which was used for the model to replicate Figure 4E and 4F from the paper. | |||||||||||||||||||||
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| 18 | PKC Pathway No. 938 | Ajay_Bhalla_ 2007_ReacDiff3 Accession No. 84 | Network | Molecule = 11 Enzyme = 0 Reaction = 10 | Molecule = 0 Enzyme = 0 Reaction = 0 | Ajay_Bhalla_bistable_model. HFSP Journal. 2007 May;1(1):1-87/ 2006-12-08 00:00:00 | |||||||||||||||
| Related Pathway: 2, 20, 34, 55, 60, 71, 108, 123, 138, 147, 161, 181, 200, 207, 313, 330, 348, 364, 370, 376, 383, 389, 395, 401, 408 414, 420, 426, 431, 437, 443, 449, 455, 461, 467, 473, 479, 485, 491, 497, 503, 509, 515, 521, 527, 534, 540, 546, 552 558, 564, 570, 576, 582, 588, 594, 600, 606, 612, 618, 624, 630, 636, 642, 648, 654, 660, 666, 672, 678, 685, 691, 698 703, 709, 715, 721, 727, 733, 739, 745, 751, 757, 763, 769, 775, 781, 787, 793, 799, 805, 811, 817, 823, 829, 835, 841 847, 853, 859, 865, 871, 877, 883, 889, 895, 901, 907, 913, 919, 927, 932, 944, 950, 956, 963, 969, 974, 981, 987, 993 999, 1004, 1010, 1016, 1022, 1028, 1034, 1040, 1046, 1052, 1058, 1064, 1104 | |||||||||||||||||||||
| This is a 25-compartment reaction-diffusion version of the Ajay_Bhalla_2007_bistable model. The original single-compartment model is repeated 25 times.
In addition, a subset (33 out of 50) molecules can diffuse between compartments. Diffusion is implemented as a reaction between corresponding molecules in neighboring compartments. Here D = 1e-13 m^2/sec (i.e., 0.1 micron^2/sec ) so the kf and kb of this reaction for these 10 micron compartments are both 0.001/sec. The basal calcium level in this model is held at 95 nM which is rather close to threshold for the flip to the active state. This is necessary to sustain active propagation of activation. The stimulus file bis6-propgn_D1e-13_FigEF which was used for the model to replicate Figure 4E and 4F from the paper. | |||||||||||||||||||||
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| 19 | PKC Pathway No. 944 | Ajay_Bhalla_ 2007_ReacDiff3 Accession No. 84 | Network | Molecule = 11 Enzyme = 0 Reaction = 10 | Molecule = 0 Enzyme = 0 Reaction = 0 | Ajay_Bhalla_bistable_model. HFSP Journal. 2007 May;1(1):1-87/ 2006-12-08 00:00:00 | |||||||||||||||
| Related Pathway: 2, 20, 34, 55, 60, 71, 108, 123, 138, 147, 161, 181, 200, 207, 313, 330, 348, 364, 370, 376, 383, 389, 395, 401, 408 414, 420, 426, 431, 437, 443, 449, 455, 461, 467, 473, 479, 485, 491, 497, 503, 509, 515, 521, 527, 534, 540, 546, 552 558, 564, 570, 576, 582, 588, 594, 600, 606, 612, 618, 624, 630, 636, 642, 648, 654, 660, 666, 672, 678, 685, 691, 698 703, 709, 715, 721, 727, 733, 739, 745, 751, 757, 763, 769, 775, 781, 787, 793, 799, 805, 811, 817, 823, 829, 835, 841 847, 853, 859, 865, 871, 877, 883, 889, 895, 901, 907, 913, 919, 927, 932, 938, 950, 956, 963, 969, 974, 981, 987, 993 999, 1004, 1010, 1016, 1022, 1028, 1034, 1040, 1046, 1052, 1058, 1064, 1104 | |||||||||||||||||||||
| This is a 25-compartment reaction-diffusion version of the Ajay_Bhalla_2007_bistable model. The original single-compartment model is repeated 25 times.
In addition, a subset (33 out of 50) molecules can diffuse between compartments. Diffusion is implemented as a reaction between corresponding molecules in neighboring compartments. Here D = 1e-13 m^2/sec (i.e., 0.1 micron^2/sec ) so the kf and kb of this reaction for these 10 micron compartments are both 0.001/sec. The basal calcium level in this model is held at 95 nM which is rather close to threshold for the flip to the active state. This is necessary to sustain active propagation of activation. The stimulus file bis6-propgn_D1e-13_FigEF which was used for the model to replicate Figure 4E and 4F from the paper. | |||||||||||||||||||||
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| 20 | PKC Pathway No. 950 | Ajay_Bhalla_ 2007_ReacDiff3 Accession No. 84 | Network | Molecule = 11 Enzyme = 0 Reaction = 10 | Molecule = 0 Enzyme = 0 Reaction = 0 | Ajay_Bhalla_bistable_model. HFSP Journal. 2007 May;1(1):1-87/ 2006-12-08 00:00:00 | |||||||||||||||
| Related Pathway: 2, 20, 34, 55, 60, 71, 108, 123, 138, 147, 161, 181, 200, 207, 313, 330, 348, 364, 370, 376, 383, 389, 395, 401, 408 414, 420, 426, 431, 437, 443, 449, 455, 461, 467, 473, 479, 485, 491, 497, 503, 509, 515, 521, 527, 534, 540, 546, 552 558, 564, 570, 576, 582, 588, 594, 600, 606, 612, 618, 624, 630, 636, 642, 648, 654, 660, 666, 672, 678, 685, 691, 698 703, 709, 715, 721, 727, 733, 739, 745, 751, 757, 763, 769, 775, 781, 787, 793, 799, 805, 811, 817, 823, 829, 835, 841 847, 853, 859, 865, 871, 877, 883, 889, 895, 901, 907, 913, 919, 927, 932, 938, 944, 956, 963, 969, 974, 981, 987, 993 999, 1004, 1010, 1016, 1022, 1028, 1034, 1040, 1046, 1052, 1058, 1064, 1104 | |||||||||||||||||||||
| This is a 25-compartment reaction-diffusion version of the Ajay_Bhalla_2007_bistable model. The original single-compartment model is repeated 25 times.
In addition, a subset (33 out of 50) molecules can diffuse between compartments. Diffusion is implemented as a reaction between corresponding molecules in neighboring compartments. Here D = 1e-13 m^2/sec (i.e., 0.1 micron^2/sec ) so the kf and kb of this reaction for these 10 micron compartments are both 0.001/sec. The basal calcium level in this model is held at 95 nM which is rather close to threshold for the flip to the active state. This is necessary to sustain active propagation of activation. The stimulus file bis6-propgn_D1e-13_FigEF which was used for the model to replicate Figure 4E and 4F from the paper. | |||||||||||||||||||||
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indicates that ordering is done according to ascending or descending order.
or Pathway 