TMT Thesis Project - Revision history

Ty M. Thomson: /* Identify and apply techniques for non-linear system identification */

Ty M. Thomson — Fri, 11 Aug 2006 17:54:22 GMT

Identify and apply techniques for non-linear system identification

←Older revision		Revision as of 17:54, 11 August 2006
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	#Model analysis tools		#Model analysis tools
	#*One basic analysis of a model is parameter sensitivity. Some people think that models should be robust to changes in parameters (reference to be filled in, since it's not cool to just state things and reference it blankly to 'some people'). I'm not so sure that is true, but either way the parameter sensitivity can in the very least tell you to what parameters your model's behavior is sensitive (critically depends on), and to what parameters it is insensitive (does not depend on).		#*One basic analysis of a model is parameter sensitivity. Some people think that models should be robust to changes in parameters (reference to be filled in, since it's not cool to just state things and reference it blankly to 'some people'). I'm not so sure that is true, but either way the parameter sensitivity can in the very least tell you to what parameters your model's behavior is sensitive (critically depends on), and to what parameters it is insensitive (does not depend on).
-	#*Another analysis would be to look at [http://www.bio.vu.nl/thb/course/tb/tb/node95.html parameter identifiability]. Essential, just because a simulation (and thus a corresponding experiment) is sensitive to a parameter (as determined by sensitivity analysis), it doesn't mean that you can successfully estimate that parameter from the relevant experimental data. A simple example is that in the steady state, the concentration of a complex is dependent on both the association and dissociation rate constants (k<sub>on</sub> and k<sub>off</sub>), but we can only successfully estimate the dissociation constant (K<sub>D</sub> = k<sub>off</sub>/k<sub>on</sub>). In order to interpret the results of parameters estimation (ie 'what do we actually know?') you need to address the issue of identifiability.

	==Other==		==Other==

Ty M. Thomson: /* Investigate the pathway with time-dependent stimulation */

Ty M. Thomson — Fri, 11 Aug 2006 17:52:58 GMT

Investigate the pathway with time-dependent stimulation

←Older revision		Revision as of 17:52, 11 August 2006
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	=== Investigate the pathway with time-dependent stimulation ===		=== Investigate the pathway with time-dependent stimulation ===

-	Examine the frequency filtering characteristics of the pheromone response pathway in order to study the limits of propagation of time-varying signals through the pathway. Use the model to form and test hypotheses generated by studying the response of the pathway to time-dependent stimulation.<br>	+	Show that using time-varying stimuli increases parameter sensitivity, and that this leads to an improvement in parameter estimation. This is really just a specific instance of hypothesis testing (where the hypothesis is the particular parameter values).
-		+
-	~~Alternative approach would be to show~~ that using time-varying stimuli increases parameter sensitivity, and that this leads to an improvement in parameter estimation. This is really just a specific instance of hypothesis testing (where the hypothesis is the particular parameter values).	+

	=== Identify and apply techniques for non-linear system identification ===		=== Identify and apply techniques for non-linear system identification ===

Ty M. Thomson: /* Build a microfluidic device for time-dependent stimulation of cells */

Ty M. Thomson — Fri, 11 Aug 2006 17:51:38 GMT

Build a microfluidic device for time-dependent stimulation of cells

←Older revision		Revision as of 17:51, 11 August 2006
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	Design, build and characterize a device to allow for rapid variation of extracellular conditions for cells fixed in a microfluidic channel.		Design, build and characterize a device to allow for rapid variation of extracellular conditions for cells fixed in a microfluidic channel.
-	*This chip has been designed using the technology out of the Quake Lab at Stanford (formerly Caltech). See [[Protocols#Microfluidics\| protocols]] for more info on chip design. Early versions of the chip (called the [[Stimulator]]) have shown great promise. Preliminary tests have shown that I can vary the extracellular environment (with NO cells in the channel) on a sub 100ms timescale. I've also successfully adhered cells to the bottom of the channel, and had them resist detachment under fluid flow, though this needs further characterization. I made a [[Image:Cells_in_stimulator.avi~~\|movie~~]] with the most recent version showing that I can change the fluid environment of cells in the channel (video in real time, with food dye used to color one of the fluids). Please see the [[Stimulator]] page for the latest information.	+	*This chip has been designed using the technology out of the Quake Lab at Stanford (formerly Caltech). See [[Protocols#Microfluidics\| protocols]] for more info on chip design. Early versions of the chip (called the [[Stimulator]]) have shown great promise. Preliminary tests have shown that I can vary the extracellular environment (with NO cells in the channel) on a sub 100ms timescale. I've also successfully adhered cells to the bottom of the channel, and had them resist detachment under fluid flow, though this needs further characterization. I made a movie ([[Image:Cells_in_stimulator.avi]]) with the most recent version showing that I can change the fluid environment of cells in the channel (video in real time, with food dye used to color one of the fluids). Please see the [[Stimulator]] page for the latest information.

	=== Investigate the pathway with time-dependent stimulation ===		=== Investigate the pathway with time-dependent stimulation ===

Ty M. Thomson: /* Identify and apply techniques for non-linear system identification */

Ty M. Thomson — Tue, 06 Jun 2006 19:03:47 GMT

Identify and apply techniques for non-linear system identification

←Older revision		Revision as of 19:03, 6 June 2006
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	#Parameter Estimation		#Parameter Estimation
	#*My first instinct was to try to do parameter estimation using Matlab. This turned out to not be sufficient for my purposes. See my notes on [[Parameter Estimation in Matlab]].		#*My first instinct was to try to do parameter estimation using Matlab. This turned out to not be sufficient for my purposes. See my notes on [[Parameter Estimation in Matlab]].
-	#*I settled on using [http://www.numericatech.com/jacobian.htm Jacobian] for parameter estimation. The ~~current~~ version that I have is ~~still somewhat buggy, but I have been assured by one of the lead guys~~ working ~~on Jacobian that they have corrected all the problems that I identified in the new release which is due out any day now. I'll update on this as soon as I get the new release~~.	+	#*I settled on using [http://www.numericatech.com/jacobian.htm Jacobian] for parameter estimation. The newest version that I have is working well.
	#Model analysis tools		#Model analysis tools
	#*One basic analysis of a model is parameter sensitivity. Some people think that models should be robust to changes in parameters (reference to be filled in, since it's not cool to just state things and reference it blankly to 'some people'). I'm not so sure that is true, but either way the parameter sensitivity can in the very least tell you to what parameters your model's behavior is sensitive (critically depends on), and to what parameters it is insensitive (does not depend on).		#*One basic analysis of a model is parameter sensitivity. Some people think that models should be robust to changes in parameters (reference to be filled in, since it's not cool to just state things and reference it blankly to 'some people'). I'm not so sure that is true, but either way the parameter sensitivity can in the very least tell you to what parameters your model's behavior is sensitive (critically depends on), and to what parameters it is insensitive (does not depend on).
	#*Another analysis would be to look at [http://www.bio.vu.nl/thb/course/tb/tb/node95.html parameter identifiability]. Essential, just because a simulation (and thus a corresponding experiment) is sensitive to a parameter (as determined by sensitivity analysis), it doesn't mean that you can successfully estimate that parameter from the relevant experimental data. A simple example is that in the steady state, the concentration of a complex is dependent on both the association and dissociation rate constants (k<sub>on</sub> and k<sub>off</sub>), but we can only successfully estimate the dissociation constant (K<sub>D</sub> = k<sub>off</sub>/k<sub>on</sub>). In order to interpret the results of parameters estimation (ie 'what do we actually know?') you need to address the issue of identifiability.		#*Another analysis would be to look at [http://www.bio.vu.nl/thb/course/tb/tb/node95.html parameter identifiability]. Essential, just because a simulation (and thus a corresponding experiment) is sensitive to a parameter (as determined by sensitivity analysis), it doesn't mean that you can successfully estimate that parameter from the relevant experimental data. A simple example is that in the steady state, the concentration of a complex is dependent on both the association and dissociation rate constants (k<sub>on</sub> and k<sub>off</sub>), but we can only successfully estimate the dissociation constant (K<sub>D</sub> = k<sub>off</sub>/k<sub>on</sub>). In order to interpret the results of parameters estimation (ie 'what do we actually know?') you need to address the issue of identifiability.
-	#**At [http://csbi.mit.edu/icsb-2005 ICSB 2005] I discovered this program called [http://sloppycell.sourceforge.net/ SloppyCell] written by [http://www.physics.cornell.edu/~rgutenkunst/ Ryan Gutenkunst] in the [http://www.lassp.cornell.edu/sethna/sethna.html Sethna lab] at [http://www.cornell.edu/ Cornell] which addresses parameter identifiability. Basically, SloppyCell calculates the parameter sensitivities, but does so for identifiable parameter groups (which are comprised of weigthed products of the original parameters). More details on this can be found in the [http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=14525003 original publication of the algorithm], and in my [[SloppyCell]] page.
-	#**There are other ways to deal with parameter identifiability. I'm currently looking into methods that incluse linearization of the model followed by model order reduction. When I know more, I'll add details.

	==Other==		==Other==

Ty M. Thomson: /* Other */

Ty M. Thomson — Wed, 01 Feb 2006 01:08:49 GMT

Other

←Older revision		Revision as of 01:08, 1 February 2006
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	Q. I say that a time varying stimulus can drive a system to a state that it won't normally attain in response to a step increase stimulus. For what types of systems is this true?<br>		Q. I say that a time varying stimulus can drive a system to a state that it won't normally attain in response to a step increase stimulus. For what types of systems is this true?<br>
	A. I think that I can concoct systems that this is true for, but I should try to show that this is indeed true for the pheromone response pathway.		A. I think that I can concoct systems that this is true for, but I should try to show that this is indeed true for the pheromone response pathway.
		+
		+
		+	[[Parameter Sensitivity and Estimation]]

Ty M. Thomson: /* Investigate the pathway with time-dependent stimulation */

Ty M. Thomson — Tue, 31 Jan 2006 17:05:59 GMT

Investigate the pathway with time-dependent stimulation

←Older revision		Revision as of 17:05, 31 January 2006
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	=== Investigate the pathway with time-dependent stimulation ===		=== Investigate the pathway with time-dependent stimulation ===

-	Examine the frequency filtering characteristics of the pheromone response pathway in order to study the limits of propagation of time-varying signals through the pathway. Use the model to form and test hypotheses generated by studying the response of the pathway to time-dependent stimulation.</br>	+	Examine the frequency filtering characteristics of the pheromone response pathway in order to study the limits of propagation of time-varying signals through the pathway. Use the model to form and test hypotheses generated by studying the response of the pathway to time-dependent stimulation.<br>

	Alternative approach would be to show that using time-varying stimuli increases parameter sensitivity, and that this leads to an improvement in parameter estimation. This is really just a specific instance of hypothesis testing (where the hypothesis is the particular parameter values).		Alternative approach would be to show that using time-varying stimuli increases parameter sensitivity, and that this leads to an improvement in parameter estimation. This is really just a specific instance of hypothesis testing (where the hypothesis is the particular parameter values).

Ty M. Thomson: /* Identify and apply techniques for non-linear system identification */

Ty M. Thomson — Tue, 31 Jan 2006 16:57:35 GMT

Identify and apply techniques for non-linear system identification

←Older revision		Revision as of 16:57, 31 January 2006
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	#Model analysis tools		#Model analysis tools
	#*One basic analysis of a model is parameter sensitivity. Some people think that models should be robust to changes in parameters (reference to be filled in, since it's not cool to just state things and reference it blankly to 'some people'). I'm not so sure that is true, but either way the parameter sensitivity can in the very least tell you to what parameters your model's behavior is sensitive (critically depends on), and to what parameters it is insensitive (does not depend on).		#*One basic analysis of a model is parameter sensitivity. Some people think that models should be robust to changes in parameters (reference to be filled in, since it's not cool to just state things and reference it blankly to 'some people'). I'm not so sure that is true, but either way the parameter sensitivity can in the very least tell you to what parameters your model's behavior is sensitive (critically depends on), and to what parameters it is insensitive (does not depend on).
-	#*Another analysis would be to look at [http://www.bio.vu.nl/thb/course/tb/tb/node95.html parameter identifiability]. Essential, just because a simulation (and thus a corresponding experiment) is sensitive to a parameter (as determined by sensitivity analysis), it doesn't mean that you can successfully estimate that parameter from the relevant experimental data. A simple example is that in the steady state, the concentration of a complex is dependent on both the association and dissociation rate constants (k<sub>on</sub> and k<sub>off</sub>), but we can only successfully estimate the dissociation constant (K<sub>D</sub> = k<sub>off</sub>/k<sub>on</sub>).	+	#*Another analysis would be to look at [http://www.bio.vu.nl/thb/course/tb/tb/node95.html parameter identifiability]. Essential, just because a simulation (and thus a corresponding experiment) is sensitive to a parameter (as determined by sensitivity analysis), it doesn't mean that you can successfully estimate that parameter from the relevant experimental data. A simple example is that in the steady state, the concentration of a complex is dependent on both the association and dissociation rate constants (k<sub>on</sub> and k<sub>off</sub>), but we can only successfully estimate the dissociation constant (K<sub>D</sub> = k<sub>off</sub>/k<sub>on</sub>). In order to interpret the results of parameters estimation (ie 'what do we actually know?') you need to address the issue of identifiability.
	#**At [http://csbi.mit.edu/icsb-2005 ICSB 2005] I discovered this program called [http://sloppycell.sourceforge.net/ SloppyCell] written by [http://www.physics.cornell.edu/~rgutenkunst/ Ryan Gutenkunst] in the [http://www.lassp.cornell.edu/sethna/sethna.html Sethna lab] at [http://www.cornell.edu/ Cornell] which addresses parameter identifiability. Basically, SloppyCell calculates the parameter sensitivities, but does so for identifiable parameter groups (which are comprised of weigthed products of the original parameters). More details on this can be found in the [http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=14525003 original publication of the algorithm], and in my [[SloppyCell]] page.		#**At [http://csbi.mit.edu/icsb-2005 ICSB 2005] I discovered this program called [http://sloppycell.sourceforge.net/ SloppyCell] written by [http://www.physics.cornell.edu/~rgutenkunst/ Ryan Gutenkunst] in the [http://www.lassp.cornell.edu/sethna/sethna.html Sethna lab] at [http://www.cornell.edu/ Cornell] which addresses parameter identifiability. Basically, SloppyCell calculates the parameter sensitivities, but does so for identifiable parameter groups (which are comprised of weigthed products of the original parameters). More details on this can be found in the [http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=14525003 original publication of the algorithm], and in my [[SloppyCell]] page.
	#**There are other ways to deal with parameter identifiability. I'm currently looking into methods that incluse linearization of the model followed by model order reduction. When I know more, I'll add details.		#**There are other ways to deal with parameter identifiability. I'm currently looking into methods that incluse linearization of the model followed by model order reduction. When I know more, I'll add details.
-

	==Other==		==Other==

Ty M. Thomson: /* Identify and apply techniques for non-linear system identification */

Ty M. Thomson — Tue, 31 Jan 2006 16:51:41 GMT

Identify and apply techniques for non-linear system identification

←Older revision		Revision as of 16:51, 31 January 2006
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		+	==Other==

	''' Relevant questions '''		''' Relevant questions '''

Ty M. Thomson: /* Research Goals */

Ty M. Thomson — Tue, 31 Jan 2006 16:44:57 GMT

Research Goals

Ty M. Thomson: /* Identify and apply techniques for non-linear system identification */

Ty M. Thomson — Tue, 31 Jan 2006 16:43:47 GMT

Identify and apply techniques for non-linear system identification

←Older revision		Revision as of 16:43, 31 January 2006
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	*#Model analysis tools		*#Model analysis tools
	#One basic analysis of a model is parameter sensitivity. Some people think that models should be robust to changes in parameters (reference to be filled in, since it's not cool to just state things and reference it blankly to 'some people'). I'm not so sure that is true, but either way the parameter sensitivity can in the very least tell you to what parameters your model's behavior is sensitive (critically depends on), and to what parameters it is insensitive (does not depend on).		#One basic analysis of a model is parameter sensitivity. Some people think that models should be robust to changes in parameters (reference to be filled in, since it's not cool to just state things and reference it blankly to 'some people'). I'm not so sure that is true, but either way the parameter sensitivity can in the very least tell you to what parameters your model's behavior is sensitive (critically depends on), and to what parameters it is insensitive (does not depend on).
-	#At [http://csbi.mit.edu/icsb-2005 ICSB 2005] I discovered this ~~great~~ program called [http://sloppycell.sourceforge.net/ SloppyCell] written by [http://www.physics.cornell.edu/~rgutenkunst/ Ryan Gutenkunst] in the [http://www.lassp.cornell.edu/sethna/sethna.html Sethna lab] at [http://www.cornell.edu/ Cornell]. Basically, SloppyCell calculates the parameter sensitivities, but does so for identifiable parameter groups. More details on this can be found in the [http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=14525003 original publication of the algorithm], and in my [[SloppyCell]] page.	+	#Another analysis would be to look at [http://www.bio.vu.nl/thb/course/tb/tb/node95.html parameter identifiability]. Essential, just because a simulation (and thus a corresponding experiment) is sensitive to a parameter (as determined by sensitivity analysis), it doesn't mean that you can successfully estimate that parameter from the relevant experimental data. A simple example is that in the steady state, the concentration of a complex is dependent on both the association and dissociation rate constants (k<sub>on</sub> and k<sub>off</sub>), but we can only successfully estimate the dissociation constant (K<sub>D</sub> = k<sub>off</sub>/k<sub>on</sub>).
		+	#*At [http://csbi.mit.edu/icsb-2005 ICSB 2005] I discovered this program called [http://sloppycell.sourceforge.net/ SloppyCell] written by [http://www.physics.cornell.edu/~rgutenkunst/ Ryan Gutenkunst] in the [http://www.lassp.cornell.edu/sethna/sethna.html Sethna lab] at [http://www.cornell.edu/ Cornell] which addresses parameter identifiability. Basically, SloppyCell calculates the parameter sensitivities, but does so for identifiable parameter groups (which are comprised of weigthed products of the original parameters). More details on this can be found in the [http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=14525003 original publication of the algorithm], and in my [[SloppyCell]] page.
		+	#*There are other ways to deal with parameter identifiability. I'm currently looking into methods that incluse linearization of the model followed by model order reduction. When I know more, I'll add details.

←Older revision		Revision as of 16:44, 31 January 2006
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	=== Build a model of the pheromone response pathway ===		=== Build a model of the pheromone response pathway ===

-	*Develop a model of the pheromone response pathway that can be used in conjunction with time-dependent stimulation and analysis of the pathway to propose and test hypotheses. Once completed, this model can be used as a predictive tool for pathway response.	+	Develop a model of the pheromone response pathway that can be used in conjunction with time-dependent stimulation and analysis of the pathway to propose and test hypotheses. Once completed, this model can be used as a predictive tool for pathway response.
-	**This model is largely already built (with instances in Matlab and [http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=15637632&query_hl=1 Moleculizer]). Also, using [http://cellsignaling.lanl.gov/bionetgen/ BioNetGen2] I have generated an SBML version of my model, which can be read as input by [http://www.numericatech.com/jacobian.htm Jacobian], [http://sloppycell.sourceforge.net/ SloppyCell], and the [http://www.mathworks.com/products/simbiology/ SimBio] toolbox in Matlab.	+	*This model is largely already built (with instances in Matlab and [http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=15637632&query_hl=1 Moleculizer]). Also, using [http://cellsignaling.lanl.gov/bionetgen/ BioNetGen2] I have generated an SBML version of my model, which can be read as input by [http://www.numericatech.com/jacobian.htm Jacobian], [http://sloppycell.sourceforge.net/ SloppyCell], and the [http://www.mathworks.com/products/simbiology/ SimBio] toolbox in Matlab.
-	**The model needs to be further refined using data from the literature, and data that I will generate myself.	+	*The model needs to be further refined using data from the literature, and data that I will generate myself.

	=== Build a microfluidic device for time-dependent stimulation of cells ===		=== Build a microfluidic device for time-dependent stimulation of cells ===

-	*Design, build and characterize a device to allow for rapid variation of extracellular conditions for cells fixed in a microfluidic channel.	+	Design, build and characterize a device to allow for rapid variation of extracellular conditions for cells fixed in a microfluidic channel.
-	**This chip has been designed using the technology out of the Quake Lab at Stanford (formerly Caltech). See [[Protocols#Microfluidics\| protocols]] for more info on chip design. Early versions of the chip (called the [[Stimulator]]) have shown great promise. Preliminary tests have shown that I can vary the extracellular environment (with NO cells in the channel) on a sub 100ms timescale. I've also successfully adhered cells to the bottom of the channel, and had them resist detachment under fluid flow, though this needs further characterization. I made a [[Image:Cells_in_stimulator.avi\|movie]] with the most recent version showing that I can change the fluid environment of cells in the channel (video in real time, with food dye used to color one of the fluids). Please see the [[Stimulator]] page for the latest information.	+	*This chip has been designed using the technology out of the Quake Lab at Stanford (formerly Caltech). See [[Protocols#Microfluidics\| protocols]] for more info on chip design. Early versions of the chip (called the [[Stimulator]]) have shown great promise. Preliminary tests have shown that I can vary the extracellular environment (with NO cells in the channel) on a sub 100ms timescale. I've also successfully adhered cells to the bottom of the channel, and had them resist detachment under fluid flow, though this needs further characterization. I made a [[Image:Cells_in_stimulator.avi\|movie]] with the most recent version showing that I can change the fluid environment of cells in the channel (video in real time, with food dye used to color one of the fluids). Please see the [[Stimulator]] page for the latest information.

	=== Investigate the pathway with time-dependent stimulation ===		=== Investigate the pathway with time-dependent stimulation ===

-	*Examine the frequency filtering characteristics of the pheromone response pathway in order to study the limits of propagation of time-varying signals through the pathway. Use the model to form and test hypotheses generated by studying the response of the pathway to time-dependent stimulation.	+	Examine the frequency filtering characteristics of the pheromone response pathway in order to study the limits of propagation of time-varying signals through the pathway. Use the model to form and test hypotheses generated by studying the response of the pathway to time-dependent stimulation.</br>
-	*Alternative approach would be to show that using time-varying stimuli increases parameter sensitivity, and that this leads to an improvement in parameter estimation. This is really just a specific instance of hypothesis testing (where the hypothesis is the particular parameter values).	+
		+	Alternative approach would be to show that using time-varying stimuli increases parameter sensitivity, and that this leads to an improvement in parameter estimation. This is really just a specific instance of hypothesis testing (where the hypothesis is the particular parameter values).

	=== Identify and apply techniques for non-linear system identification ===		=== Identify and apply techniques for non-linear system identification ===

-	*Identify and apply tools developed for other fields to the analysis of signaling pathways, particularly with respect to time-dependent stimulation. This can be divided into into two thrusts, parameter estimation and other analysis tools.	+	Identify and apply tools developed for other fields to the analysis of signaling pathways, particularly with respect to time-dependent stimulation. This can be divided into into two thrusts, parameter estimation and other analysis tools.
-	*#Parameter Estimation	+	#Parameter Estimation
-	#My first instinct was to try to do parameter estimation using Matlab. This turned out to not be sufficient for my purposes. See my notes on [[Parameter Estimation in Matlab]].	+	#*My first instinct was to try to do parameter estimation using Matlab. This turned out to not be sufficient for my purposes. See my notes on [[Parameter Estimation in Matlab]].
-	#I settled on using [http://www.numericatech.com/jacobian.htm Jacobian] for parameter estimation. The current version that I have is still somewhat buggy, but I have been assured by one of the lead guys working on Jacobian that they have corrected all the problems that I identified in the new release which is due out any day now. I'll update on this as soon as I get the new release.	+	#*I settled on using [http://www.numericatech.com/jacobian.htm Jacobian] for parameter estimation. The current version that I have is still somewhat buggy, but I have been assured by one of the lead guys working on Jacobian that they have corrected all the problems that I identified in the new release which is due out any day now. I'll update on this as soon as I get the new release.
-	*#Model analysis tools	+	#Model analysis tools
-	#One basic analysis of a model is parameter sensitivity. Some people think that models should be robust to changes in parameters (reference to be filled in, since it's not cool to just state things and reference it blankly to 'some people'). I'm not so sure that is true, but either way the parameter sensitivity can in the very least tell you to what parameters your model's behavior is sensitive (critically depends on), and to what parameters it is insensitive (does not depend on).	+	#*One basic analysis of a model is parameter sensitivity. Some people think that models should be robust to changes in parameters (reference to be filled in, since it's not cool to just state things and reference it blankly to 'some people'). I'm not so sure that is true, but either way the parameter sensitivity can in the very least tell you to what parameters your model's behavior is sensitive (critically depends on), and to what parameters it is insensitive (does not depend on).
-	#Another analysis would be to look at [http://www.bio.vu.nl/thb/course/tb/tb/node95.html parameter identifiability]. Essential, just because a simulation (and thus a corresponding experiment) is sensitive to a parameter (as determined by sensitivity analysis), it doesn't mean that you can successfully estimate that parameter from the relevant experimental data. A simple example is that in the steady state, the concentration of a complex is dependent on both the association and dissociation rate constants (k<sub>on</sub> and k<sub>off</sub>), but we can only successfully estimate the dissociation constant (K<sub>D</sub> = k<sub>off</sub>/k<sub>on</sub>).	+	#*Another analysis would be to look at [http://www.bio.vu.nl/thb/course/tb/tb/node95.html parameter identifiability]. Essential, just because a simulation (and thus a corresponding experiment) is sensitive to a parameter (as determined by sensitivity analysis), it doesn't mean that you can successfully estimate that parameter from the relevant experimental data. A simple example is that in the steady state, the concentration of a complex is dependent on both the association and dissociation rate constants (k<sub>on</sub> and k<sub>off</sub>), but we can only successfully estimate the dissociation constant (K<sub>D</sub> = k<sub>off</sub>/k<sub>on</sub>).
-	#*At [http://csbi.mit.edu/icsb-2005 ICSB 2005] I discovered this program called [http://sloppycell.sourceforge.net/ SloppyCell] written by [http://www.physics.cornell.edu/~rgutenkunst/ Ryan Gutenkunst] in the [http://www.lassp.cornell.edu/sethna/sethna.html Sethna lab] at [http://www.cornell.edu/ Cornell] which addresses parameter identifiability. Basically, SloppyCell calculates the parameter sensitivities, but does so for identifiable parameter groups (which are comprised of weigthed products of the original parameters). More details on this can be found in the [http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=14525003 original publication of the algorithm], and in my [[SloppyCell]] page.	+	#**At [http://csbi.mit.edu/icsb-2005 ICSB 2005] I discovered this program called [http://sloppycell.sourceforge.net/ SloppyCell] written by [http://www.physics.cornell.edu/~rgutenkunst/ Ryan Gutenkunst] in the [http://www.lassp.cornell.edu/sethna/sethna.html Sethna lab] at [http://www.cornell.edu/ Cornell] which addresses parameter identifiability. Basically, SloppyCell calculates the parameter sensitivities, but does so for identifiable parameter groups (which are comprised of weigthed products of the original parameters). More details on this can be found in the [http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=14525003 original publication of the algorithm], and in my [[SloppyCell]] page.
-	#*There are other ways to deal with parameter identifiability. I'm currently looking into methods that incluse linearization of the model followed by model order reduction. When I know more, I'll add details.	+	#**There are other ways to deal with parameter identifiability. I'm currently looking into methods that incluse linearization of the model followed by model order reduction. When I know more, I'll add details.