MODEL7896869925
type: SBMLModel
parameter: 438673
rule: 438645
parameter: 438709
rule: 438653
parameter: 438713
rule: 438649
parameter: 438701
parameter: 438658
parameter: 438691
rule: 438647
rule: 438655
parameter: 438669
name: Sobaleva2005_ProlactinRegulation
units def: 929849
compartment: 438639
parameter: 438715
units def: 929764
units def: 930018
parameter: 438703
units def: 929873
units def: 929788
parameter: 438699
area units: area
rule: 438641
parameter: 438683
volume units: metaid_0000217
parameter: 438687
parameter: 438671
units def: 929813
parameter: 438675
parameter: 438693
curated: false
parameter: 438659
parameter: 438681
parameter: 438663
units def: 929970
units def: 929921
parameter: 438717
notes: This a model from the article: Mathematical modelling of prolactin-receptor interaction and the corollary for prolactin receptor gene expression in skin Soboleva TK, Vetharaniam I, Nixon AJ, Montenegro R, Pearson AJ, Sneyd J. J Theor Biol. (2005) 234(2); 289-98 15757685 , Abstract: A mathematical model of prolactin regulating its own receptors was developed, and compared with experimental data on a qualitative level. The model incorporates the kinetics of prolactin-receptor interactions and subsequent signalling by prolactin-receptor dimers to regulate the production of receptor mRNA and hence the receptor population. The model relates changes in plasma prolactin concentration to prolactin receptor (PRLR) gene expression, and can be used for predictive purposes. The cell signalling that leads to the activation of target genes, and the mechanisms for regulation of transcription, were treated empirically in the model. The model's parameters were adjusted so that model simulations agreed with experimentally observed responses to administration of prolactin in sheep. In particular, the model correctly predicts insensitivity of receptor mRNA regulation to a series of subcutaneous injections of prolactin, versus sensitivity to prolonged infusion of prolactin. In the latter case, response was an acute down-regulation followed by a prolonged up-regulation of mRNA, with the magnitude of the up-regulation increasing with the duration of infusion period. The model demonstrates the feasibility of predicting the in vivo response of prolactin target genes to external manipulation of plasma prolactin, and could provide a useful tool for identifying optimal prolactin treatments for desirable outcomes. This model was taken from the CellML repository and automatically converted to SBML. The original model was: soboleva, vetharaniam, nixon, montenegro, pearson, sneyd, 2005, version01 The original CellML model was created by: Lloyd, Catherine, May c.lloyd(at)auckland.ac.nz The Universi…
is described by: http://identifiers.org/pubmed/15757685
substance units: 106194
rule: 438657
rule: 438643
parameter: 438695
parameter: 438705
rule: 438651
parameter: 438707
parameter: 438711
parameter: 438689
parameter: 438677
parameter: 438661
time units: 930018
parameter: 438665
parameter: 438679
parameter: 438697
parameter: 438667
length unit: length
parameter: 438685

438673
type: Parameter
constant: false
units: 929813
value: NaN
name: P

929813
type: SBMLUnitsDef
unit: 929837
unit: 929825
name: nanomolar

929837
type: SBMLUnit
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scale: 0
multipler: 1.0
kind: LITRE

929825
type: SBMLUnit
exponent: 1.0
scale: -9
multipler: 1.0
kind: MOLE

438709
type: Parameter
constant: true
units: 929921
value: 4.15
name: alpha0

929921
type: SBMLUnitsDef
unit: 929957
unit: 929945
unit: 929933
name: per_nanomolar_day

929957
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kind: SECOND

929945
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929933
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kind: MOLE

438713
type: Parameter
constant: true
units: 929849
value: 13.0
name: d01

929849
type: SBMLUnitsDef
unit: 929861
name: first_order_rate_constant

929861
type: SBMLUnit
exponent: -1.0
scale: 0
multipler: 86400.0
kind: SECOND

438701
type: Parameter
constant: true
units: 929849
value: 0.207
name: delta_x

438658
type: Parameter
constant: false
units: 929813
value: 1.0
name: R

438691
type: Parameter
constant: true
units: 929813
value: 100.0
name: b

438669
type: Parameter
constant: false
units: 929813
value: 1.0
name: B2

438639
type: Compartment
constant: true
units: litre
size: 1.0
spatial dimensions: 3.0

438715
type: Parameter
constant: true
units: 929849
value: 4720.0
name: d12

929764
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name: day

929776
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930018
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930030
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kind: SECOND

438703
type: Parameter
constant: false
units: 929873
value: NaN
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929873
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unit: 929885
name: flux

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929897
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929801
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438699
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value: 371000.0
name: s

929970
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name: nanomolar_day2

930006
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929982
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438683
type: Parameter
constant: true
units: 929764
value: 9.0
name: T

438687
type: Parameter
constant: true
units: 929873
value: 358000.0
name: a

438671
type: Parameter
constant: true
units: 929849
value: 50.0
name: delta_b2

438675
type: Parameter
constant: true
units: 929813
value: 20.55
name: PE

438693
type: Parameter
constant: true
units: 929813
value: 263.0
name: b0

438659
type: Parameter
constant: true
units: 929849
value: 1.905
name: delta_R

438681
type: Parameter
constant: true
units: 929764
value: 1.0
name: ti

438663
type: Parameter
constant: true
units: 929849
value: 7.5
name: delta_U

438717
type: Parameter
constant: true
units: 929813
value: 0.25
name: P0

438695
type: Parameter
constant: false
units: 929873
value: 1.0
name: x

438705
type: Parameter
constant: true
units: 929873
value: 240000.0
name: kappa

438707
type: Parameter
constant: true
units: 929813
value: 6550.0
name: kappa0

438711
type: Parameter
constant: true
units: 929921
value: 3.02
name: alpha1

438689
type: Parameter
constant: true
units: 929873
value: 23300.0
name: a0

438677
type: Parameter
constant: false
units: dimensionless
value: NaN
name: q

438661
type: Parameter
constant: false
units: 929813
value: 1.0
name: U

438665
type: Parameter
constant: false
units: 929813
value: 1.0
name: B1

438679
type: Parameter
constant: true
units: 929849
value: 35.6
name: G

438697
type: Parameter
constant: true
units: 929813
value: 20.0
name: P1

438667
type: Parameter
constant: true
units: 929849
value: 7.5
name: delta_b1

438685
type: Parameter
constant: false
units: 929873
value: NaN
name: f1