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Pathway List for pkc

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 statisticspkc statisticsSource
Entry Date
1 PKC
Pathway No. 71
 Synaptic_
Network

Accession No. 16
NetworkMolecule = 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
   Related Pathway: 
220345560108123138147161181200207313330348364370376383389395401408414
420426431437443449455461467473479485491497503509515521527534540546552558
564570576582588594600606612618624630636642648654660666672678685691698703
709715721727733739745751757763769775781787793799805811817823829835841847
853859865871877883889895901907913919927932938944950956963969974981987993
999100410101016102210281034104010461052105810641104
    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.
   
This pathway is part of accession 16 and is completely specified in the file acc16.g.
There is no separate files for just this pathway.
FormatFile
Native Format (GENESIS format)    acc16.g   
GENESIS Format (Annotated version)    Anno_acc16.g   
2 PKC
Pathway No. 138
 PKC_turnover

Accession No. 26
PathwayMolecule = 19
Enzyme   = 1
Reaction  = 17
Molecule = 0
Enzyme   = 0
Reaction  = 0
In-house /
2002-01-22
   Related Pathway: 
22034556071108123147161181200207313330348364370376383389395401408414
420426431437443449455461467473479485491497503509515521527534540546552558
564570576582588594600606612618624630636642648654660666672678685691698703
709715721727733739745751757763769775781787793799805811817823829835841847
853859865871877883889895901907913919927932938944950956963969974981987993
999100410101016102210281034104010461052105810641104
    This enzyme represents an averaged PKC activity, most closely based on the alpha, beta, and gamma forms.
   
This pathway is part of accession 26 and is completely specified in the file acc26.g.
There is no separate files for just this pathway.
FormatFile
Native Format (GENESIS format)    acc26.g   
GENESIS Format (Annotated version)    Anno_acc26.g   
MATLAB format    acc26.m   
SBML format    acc26.xml   
3 PKC
Pathway No. 200
 PKC_2003

Accession No. 48
PathwayMolecule = 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
   Related Pathway: 
22034556071108123138147161181207313330348364370376383389395401408414
420426431437443449455461467473479485491497503509515521527534540546552558
564570576582588594600606612618624630636642648654660666672678685691698703
709715721727733739745751757763769775781787793799805811817823829835841847
853859865871877883889895901907913919927932938944950956963969974981987993
999100410101016102210281034104010461052105810641104
    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.
   
This pathway is part of accession 48 and is completely specified in the file acc48.g.
There is no separate files for just this pathway.
FormatFile
Native Format (GENESIS format)    acc48.g   
GENESIS Format (Annotated version)    Anno_acc48.g   
MATLAB format    acc48.m   
SBML format    acc48.xml   
4 PKC
Pathway No. 123
 Osc_Ca_
IP3metabolism

Accession No. 24
NetworkMolecule = 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
   Related Pathway: 
22034556071108138147161181200207313330348364370376383389395401408414
420426431437443449455461467473479485491497503509515521527534540546552558
564570576582588594600606612618624630636642648654660666672678685691698703
709715721727733739745751757763769775781787793799805811817823829835841847
853859865871877883889895901907913919927932938944950956963969974981987993
999100410101016102210281034104010461052105810641104
    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.
   
This pathway is part of accession 24 and is completely specified in the file acc24.g.
There is no separate files for just this pathway.
FormatFile
Native Format (GENESIS format)    acc24.g   
GENESIS Format (Annotated version)    Anno_acc24.g   
5 PKC
Pathway No. 161
 Osc_Ca_
IP3metabolism

Accession No. 32
NetworkMolecule = 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
   Related Pathway: 
22034556071108123138147181200207313330348364370376383389395401408414
420426431437443449455461467473479485491497503509515521527534540546552558
564570576582588594600606612618624630636642648654660666672678685691698703
709715721727733739745751757763769775781787793799805811817823829835841847
853859865871877883889895901907913919927932938944950956963969974981987993
999100410101016102210281034104010461052105810641104
    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.
   
This pathway is part of accession 32 and is completely specified in the file acc32.g.
There is no separate files for just this pathway.
FormatFile
Native Format (GENESIS format)    acc32.g   
GENESIS Format (Annotated version)    Anno_acc32.g   
6 PKC
Pathway No. 108
 NonOsc_Ca_
IP3metabolism

Accession No. 23
NetworkMolecule = 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
   Related Pathway: 
22034556071123138147161181200207313330348364370376383389395401408414
420426431437443449455461467473479485491497503509515521527534540546552558
564570576582588594600606612618624630636642648654660666672678685691698703
709715721727733739745751757763769775781787793799805811817823829835841847
853859865871877883889895901907913919927932938944950956963969974981987993
999100410101016102210281034104010461052105810641104
    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.
   
This pathway is part of accession 23 and is completely specified in the file acc23.g.
There is no separate files for just this pathway.
FormatFile
Native Format (GENESIS format)    acc23.g   
GENESIS Format (Annotated version)    Anno_acc23.g   
7 PKC
Pathway No. 147
 NonOsc_Ca_
IP3metabolism

Accession No. 31
NetworkMolecule = 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
   Related Pathway: 
22034556071108123138161181200207313330348364370376383389395401408414
420426431437443449455461467473479485491497503509515521527534540546552558
564570576582588594600606612618624630636642648654660666672678685691698703
709715721727733739745751757763769775781787793799805811817823829835841847
853859865871877883889895901907913919927932938944950956963969974981987993
999100410101016102210281034104010461052105810641104
    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.
   
This pathway is part of accession 31 and is completely specified in the file acc31.g.
There is no separate files for just this pathway.
FormatFile
Native Format (GENESIS format)    acc31.g   
GENESIS Format (Annotated version)    Anno_acc31.g   
8 PKC
Pathway No. 1104
 mTOR_pathway

Accession No. 92
NetworkMolecule = 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
   Related Pathway: 
22034556071108123138147161181200207313330348364370376383389395401408
414420426431437443449455461467473479485491497503509515521527534540546552
558564570576582588594600606612618624630636642648654660666672678685691698
703709715721727733739745751757763769775781787793799805811817823829835841
847853859865871877883889895901907913919927932938944950956963969974981987
99399910041010101610221028103410401046105210581064
    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.
   
This pathway is part of accession 92 and is completely specified in the file acc92.g.
There is no separate file for just this pathway.
FormatFile
Native Format (GENESIS format)    acc92.g   
9 PKC
Pathway No. 34
 mkp1_feedback_
effects

Accession No. 4
NetworkMolecule = 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
   Related Pathway: 
220556071108123138147161181200207313330348364370376383389395401408414
420426431437443449455461467473479485491497503509515521527534540546552558
564570576582588594600606612618624630636642648654660666672678685691698703
709715721727733739745751757763769775781787793799805811817823829835841847
853859865871877883889895901907913919927932938944950956963969974981987993
999100410101016102210281034104010461052105810641104
    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.
   
This pathway is part of accession 4 and is completely specified in the file acc4.g.
There is no separate files for just this pathway.
FormatFile
Native Format (GENESIS format)    acc4.g   
GENESIS Format (Annotated version)    Anno_acc4.g   
MATLAB format    acc4.m   
SBML format    acc4.xml   
10 PKC
Pathway No. 207
 MAPK_network_
2003

Accession No. 50
NetworkMolecule = 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
   Related Pathway: 
22034556071108123138147161181200313330348364370376383389395401408414
420426431437443449455461467473479485491497503509515521527534540546552558
564570576582588594600606612618624630636642648654660666672678685691698703
709715721727733739745751757763769775781787793799805811817823829835841847
853859865871877883889895901907913919927932938944950956963969974981987993
999100410101016102210281034104010461052105810641104
    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
   
FormatFile
Native Format (GENESIS format)    path207.g   
GENESIS Format (Annotated version)    Anno_path207.g   
MATLAB format    path207.m   
11 PKC
Pathway No. 60
 MAPK_MKP1_
oscillation

Accession No. 9
NetworkMolecule = 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
   Related Pathway: 
220345571108123138147161181200207313330348364370376383389395401408414
420426431437443449455461467473479485491497503509515521527534540546552558
564570576582588594600606612618624630636642648654660666672678685691698703
709715721727733739745751757763769775781787793799805811817823829835841847
853859865871877883889895901907913919927932938944950956963969974981987993
999100410101016102210281034104010461052105810641104
    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.
   
This pathway is part of accession 9 and is completely specified in the file acc9.g.
There is no separate files for just this pathway.
FormatFile
Native Format (GENESIS format)    acc9.g   
GENESIS Format (Annotated version)    Anno_acc9.g   
GENESIS Format (Annotated version)    Anno_acc9.g   
MATLAB format    acc9.m   
SBML format    acc9.xml   
12 PKC
Pathway No. 181
 MAPK-bistability
-fig1c

Accession No. 35
NetworkMolecule = 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
   Related Pathway: 
22034556071108123138147161200207313330348364370376383389395401408414
420426431437443449455461467473479485491497503509515521527534540546552558
564570576582588594600606612618624630636642648654660666672678685691698703
709715721727733739745751757763769775781787793799805811817823829835841847
853859865871877883889895901907913919927932938944950956963969974981987993
999100410101016102210281034104010461052105810641104
    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.
   
This pathway is part of accession 35 and is completely specified in the file acc35.g.
There is no separate files for just this pathway.
FormatFile
Native Format (GENESIS format)    acc35.g   
GENESIS Format (Annotated version)    Anno_acc35.g   
MATLAB format    acc35.m   
SBML format    acc35.xml   
13 PKC
Pathway No. 20
 fig4_synapse

Accession No. 3
NetworkMolecule = 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
   Related Pathway: 
234556071108123138147161181200207313330348364370376383389395401408414
420426431437443449455461467473479485491497503509515521527534540546552558
564570576582588594600606612618624630636642648654660666672678685691698703
709715721727733739745751757763769775781787793799805811817823829835841847
853859865871877883889895901907913919927932938944950956963969974981987993
999100410101016102210281034104010461052105810641104
    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.
   
This pathway is part of accession 3 and is completely specified in the file acc3.g.
There is no separate files for just this pathway.
FormatFile
Native Format (GENESIS format)    acc3.g   
GENESIS Format (Annotated version)    Anno_acc3.g   
14 PKC
Pathway No. 2
 fig2_egfr

Accession No. 1
NetworkMolecule = 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
   Related Pathway: 
2034556071108123138147161181200207313330348364370376383389395401408
414420426431437443449455461467473479485491497503509515521527534540546552
558564570576582588594600606612618624630636642648654660666672678685691698
703709715721727733739745751757763769775781787793799805811817823829835841
847853859865871877883889895901907913919927932938944950956963969974981987
993999100410101016102210281034104010461052105810641104
    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.
   
This pathway is part of accession 1 and is completely specified in the file acc1.g.
There is no separate files for just this pathway.
FormatFile
Native Format (GENESIS format)    acc1.g   
GENESIS Format (Annotated version)    Anno_acc1.g   
15 PKC
Pathway No. 919
 Ajay_Bhalla_
2007_ReacDiff3

Accession No. 84
NetworkMolecule = 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
   Related Pathway: 
22034556071108123138147161181200207313330348364370376383389395401408
414420426431437443449455461467473479485491497503509515521527534540546552
558564570576582588594600606612618624630636642648654660666672678685691698
703709715721727733739745751757763769775781787793799805811817823829835841
847853859865871877883889895901907913927932938944950956963969974981987993
999100410101016102210281034104010461052105810641104
    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.
   
This pathway is part of accession 84 and is completely specified in the file acc84.g.
There is no separate file for just this pathway.
FormatFile
Native Format (GENESIS format)    acc84.g   
16 PKC
Pathway No. 927
 Ajay_Bhalla_
2007_ReacDiff3

Accession No. 84
NetworkMolecule = 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
   Related Pathway: 
22034556071108123138147161181200207313330348364370376383389395401408
414420426431437443449455461467473479485491497503509515521527534540546552
558564570576582588594600606612618624630636642648654660666672678685691698
703709715721727733739745751757763769775781787793799805811817823829835841
847853859865871877883889895901907913919932938944950956963969974981987993
999100410101016102210281034104010461052105810641104
    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.
   
This pathway is part of accession 84 and is completely specified in the file acc84.g.
There is no separate file for just this pathway.
FormatFile
Native Format (GENESIS format)    acc84.g   
17 PKC
Pathway No. 932
 Ajay_Bhalla_
2007_ReacDiff3

Accession No. 84
NetworkMolecule = 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
   Related Pathway: 
22034556071108123138147161181200207313330348364370376383389395401408
414420426431437443449455461467473479485491497503509515521527534540546552
558564570576582588594600606612618624630636642648654660666672678685691698
703709715721727733739745751757763769775781787793799805811817823829835841
847853859865871877883889895901907913919927938944950956963969974981987993
999100410101016102210281034104010461052105810641104
    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.
   
This pathway is part of accession 84 and is completely specified in the file acc84.g.
There is no separate file for just this pathway.
FormatFile
Native Format (GENESIS format)    acc84.g   
18 PKC
Pathway No. 938
 Ajay_Bhalla_
2007_ReacDiff3

Accession No. 84
NetworkMolecule = 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
   Related Pathway: 
22034556071108123138147161181200207313330348364370376383389395401408
414420426431437443449455461467473479485491497503509515521527534540546552
558564570576582588594600606612618624630636642648654660666672678685691698
703709715721727733739745751757763769775781787793799805811817823829835841
847853859865871877883889895901907913919927932944950956963969974981987993
999100410101016102210281034104010461052105810641104
    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.
   
This pathway is part of accession 84 and is completely specified in the file acc84.g.
There is no separate file for just this pathway.
FormatFile
Native Format (GENESIS format)    acc84.g   
19 PKC
Pathway No. 944
 Ajay_Bhalla_
2007_ReacDiff3

Accession No. 84
NetworkMolecule = 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
   Related Pathway: 
22034556071108123138147161181200207313330348364370376383389395401408
414420426431437443449455461467473479485491497503509515521527534540546552
558564570576582588594600606612618624630636642648654660666672678685691698
703709715721727733739745751757763769775781787793799805811817823829835841
847853859865871877883889895901907913919927932938950956963969974981987993
999100410101016102210281034104010461052105810641104
    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.
   
This pathway is part of accession 84 and is completely specified in the file acc84.g.
There is no separate file for just this pathway.
FormatFile
Native Format (GENESIS format)    acc84.g   
20 PKC
Pathway No. 950
 Ajay_Bhalla_
2007_ReacDiff3

Accession No. 84
NetworkMolecule = 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
   Related Pathway: 
22034556071108123138147161181200207313330348364370376383389395401408
414420426431437443449455461467473479485491497503509515521527534540546552
558564570576582588594600606612618624630636642648654660666672678685691698
703709715721727733739745751757763769775781787793799805811817823829835841
847853859865871877883889895901907913919927932938944956963969974981987993
999100410101016102210281034104010461052105810641104
    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.
   
This pathway is part of accession 84 and is completely specified in the file acc84.g.
There is no separate file for just this pathway.
FormatFile
Native Format (GENESIS format)    acc84.g   

 
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Database compilation and code copyright (C) 2005, Upinder S. Bhalla and NCBS/TIFR
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