production management: new lessons from...
TRANSCRIPT
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Production Management: New Lessons from Biology
James E. Metherall, Ph.D., M.B.A.
Associate Professor of Human Genetics
University of Utah
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Major Points1) Metabolic Regulation is an Extremely Complex
Operations Management Problem
1) Data Collection is NOT the Problem
1) Data Analysis is the Problem: Attempting to Understand Metabolic Regulation Through Simulation
1) Sharing Tools and Concepts: Beginning the Discussion
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Enzyme: Glucokinase (2.7.1.1)
Enzymatic Transformations
Substrate Product
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Simplifi ed View of Metabolic Pathways
Sigma-Aldrich
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Simplified View of Metabolic Pathways
Sigma-Aldrich
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Glossary of TermsProduction MetabolismTransformation Process Reaction
Raw Material Precursor/Substrate
Inline Inventory Intermediate
Product Product
Workstation Enzyme
Tool Cofactor
Workstation Blueprint Gene
Workgroup Multienzyme Complex
Organizational Layout Subcellular Compartmentation
Transport Transport
Outsourcing Dining
Operations Management Metabolic Regulation
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Simplified View of Metabolic Pathways
Sigma-Aldrich
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Major Points1) Metabolic Regulation is an Extremely Complex
Operations Management Problem
1) Data Collection is NOT the Problem
1) Data Analysis is the Problem: Attempting to Understand Metabolic Regulation Through Simulation
1) Sharing Tools and Concepts: Beginning the Discussion
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Gene Expression: Making Enzymes
Transcription Translation
Gene DNA
mRNA Enzyme
Transcription
Gene DNA
On
Off
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Gene Expression Microarrays
Hybridize Synthetic Probe
mRNA
Annealed
ExtendFlourescentNucleotides
Polymerase
**
**
*************
Destroy mRNA ** * ***** *
* * **
** * ****
* ** * **
** * ****
* ** * **
Microchip
Hybridize
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Photolithography
www.affymetrix.com
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Affymetrix Chips
www.affymetrix.com
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Affymetrix Gene Chip System
www.affymetrix.com
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Affymetrix Results
www.affymetrix.com
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Gene Expression: Making Enzymes
Transcription Translation
Gene DNA
mRNA Enzyme
Transcription
Gene DNA
On
Off
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Simplified View of Metabolic Pathways
Sigma-Aldrich
-
Major Points1) Metabolic Regulation is an Extremely Complex
Operations Management Problem
1) Data Collection is NOT the Problem
1) Data Analysis is the Problem: Attempting to Understand Metabolic Regulation Through Simulation
1) Sharing Tools and Concepts: Beginning the Discussion
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HierarchicalClustering
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Regulation of Cellular Cholesterol Metabolism
Acetyl CoA + Acetoacetyl CoA
HMG CoA
Mevalonate
CholesterolLDL
HMG CoAReductase
LDLReceptor
7-DHC
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Acetyl CoA + Acetoacetyl CoA
HMG CoA
Mevalonate
CholesterolLDL
HMG CoAReductase
LDLReceptor
Transcriptional
7-DHC
Regulation of Cellular Cholesterol Metabolism
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Sterol-Regulated GenesRab GGP TransferaseHMG CoA SynthaseCyclin B1Proteosome Subunit XRibosomal Subunit S19b-Amyloid PrecursorNADP TranshydrogenaseCOX-2Acetyl CoA CarboxylaseLDL ReceptorCdc2-related ProteinLeguainRibosomal Subunit L18AFerritin Heavy ChainDisinigrinFPP SynthaseStearoyl DesaturaseRibosomal Subunit L37G3P Acyl-transferaseMLN64 (STar-related)
CalmodulinDermatanCullin 3HMG CoA ReductaseMerF1 ATPase Subunit 6Ribosomal Subunit S247-DHC ReductaseF1 ATPase Subunit dIPP IsomeraseSqualene SynthaseUbiquinone OxidoreductaseLysosomal LipaseElectron Transfer FlavoproteinFatty Acid SynthaseNonsense-mediated Decay ProteinActivin Type BCox-3Squalene EpoxidaseStearoyl DesaturaseCathepsin L
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Regulation of Cellular Cholesterol Metabolism
Acetyl CoA + Acetoacetyl CoA
HMG CoA
Mevalonate
CholesterolLDL
HMG CoAReductase
LDLReceptor
Rate Limiting
7-DHC
Acetyl CoA + Acetoacetyl CoA
HMG CoA
Mevalonate
CholesterolLDL
HMG CoAReductase
LDLReceptor
7-DHC
Multivalent Control
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A I C
L
Si Sa
N
E1 EN
EL
Ex
nuc
mRNAaa
Simulating Cholesterol Homeostasis
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0
10000
20000
30000
40000
0 400 800 1200 1600
Time (sec)
[L]
- LDL
+ LDL
Simulating Homeostasis
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Multivalent Control Maintains Intermediate Concentrations
[I3]ss [I10]ss Model - LDL + LDL - LDL + LDL
steady state concentration (arbitrary units)
Rate limiting 124 0 183 0 Multivalent 989 999 800 929
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0
5000
10000
0 25 50 75 100
Time
[C] s
s6
A. Regulatory Oscillations
h = 8
7
Regulatory Oscillations
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Metabolic Simulation: GUI
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Metabolic Simulation: Toolbox
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Metabolic Simulation: GUI
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Metabolic Simulation: Architecture1) Relational Database
– All Model and Simulation Parameters – All Result Data
2) Computational Strategy– Multithreaded
• Reactions Calculate their own Propensities and “Fire” Themselves• Metabolites Inform Dependent Reactions of Changes
– Distributed (Screen Saver) • Look Up Simulation To Run from Database• Run Simulation• Return Data to Database
3) Hardware– Processors
• Dual Core CPU: 2 Cores, 4 Threads• GPU: 240 Cores; >1000 Threads
– GPU Development Tools - NVIDIA Cuda• Windows, Mac, Linux• Direct Calls - Visual Basic, C, C#, C++, Java • Free, Open Source Development
– GPU Servers• Desktop Monitors Flicker• 960 Cores, 4000 Threads per 1U Unit
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Major Points1) Metabolic Regulation is an Extremely Complex
Operations Management Problem
1) Data Collection is NOT the Problem
1) Data Analysis is the Problem: Attempting to Understand Metabolic Regulation Through Simulation
1) Sharing Tools and Concepts: Beginning the Discussion
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Summary1) Production Management and Metabolism Share the
Same Goal• Satisfy Demand• Efficiently Convert Raw Materials into Products• Series of Transformations
2) Both Processes Must be Efficient: They are Subject to the Law of Survival-of-the-Fittest
• Efficiencies are Necessary to Ensure Survival of the Organization and Organism, Respectively
3) While Operation Managers Strive to Create Efficient Processes, Biologists Strive to Understand Efficient Processes
• Share Tools and Concepts• Can Metabolic Regulation Instruct Production Management
Practice?• Why not emulate what evolution has perfected?• Why not emulate what God has created?
Production Management: New Lessons from BiologyMajor PointsEnzymatic TransformationsSlide 4Slide 5Glossary of TermsSlide 7Slide 8Gene Expression: Making EnzymesGene Expression MicroarraysPhotolithographyAffymetrix ChipsAffymetrix Gene Chip SystemAffymetrix ResultsSlide 15Slide 16Slide 17Slide 18Slide 19Slide 20Slide 21Slide 22Slide 23Slide 24Slide 25Slide 26Metabolic Simulation: GUIMetabolic Simulation: ToolboxSlide 29Metabolic Simulation: ArchitectureSlide 31Summary