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PML: Toward a High-Level Formal Language for Biological Systems. Bor-Yuh Evan Chang and Manu Sridharan Computer Science Division University of California, Berkeley BioConcur, Marseille September 6, 2003. Why Formal Models for Biology?. - PowerPoint PPT Presentation
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PML: Toward a High-Level Formal Language for Biological
SystemsBor-Yuh Evan Chang and Manu Sridharan
Computer Science DivisionUniversity of California, Berkeley
BioConcur, MarseilleSeptember 6, 2003
9/6/2003 PML: Toward a High-Level Formal Language for Biological Systems
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Why Formal Models for Biology?• Experiments have led to an enormous
wealth of (detailed) knowledge but in a fragmented form– serve as a common language for sharing
• modular, compositional, varying levels of abstraction• Much information described through prose
or graph-like diagrams with loose semantics– make assumptions explicit
• Mathematical abstraction convenient for reasoning and simulation
9/6/2003 PML: Toward a High-Level Formal Language for Biological Systems
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Previous Abstractions• Chemical kinetic models
– can derive differential equations– well-studied, with considerable
theoretical basis– variables do not directly correspond with
biological entities– may become difficult to see how multiple
equations relate to each other
9/6/2003 PML: Toward a High-Level Formal Language for Biological Systems
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Previous Abstractions• Pathway Databases (e.g., EcoCyc, KEGG)
– store information in a symbolic form and provide ways to query the database
– behavior of biological entities not directly described
• Petri nets– place = particular state of a molecular
specie, token = molecule, transition = reaction
9/6/2003 PML: Toward a High-Level Formal Language for Biological Systems
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Previous Abstractions• Concurrent computational processes
– each biological entity is a process that may carry some state and interacts with other processes
– each biological entity described by a “program”
– prior proposals based on process algebras, such as the -calculus [Regev et al. ’01]
– we take this view
9/6/2003 PML: Toward a High-Level Formal Language for Biological Systems
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Modeling in the -calculus• The -calculus is concise and compact,
yet powerful [Milner ’90]– take this as the underlying machine
model– not looking for another machine model
• However, it is far too low-level for direct modeling (ad-hoc structuring)
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Informal Graphical Diagrams
Protein
Enzyme Protein Enzyme
Enzyme
Proteink
k-1
kcatsites
domains
rules
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PML: EnzymeEnzymebind_substrate
parameterized
declared in outer scope
interactions within the complex
9/6/2003 PML: Toward a High-Level Formal Language for Biological Systems
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PML: ProteinProtein Proteinbind_substrate bind_product
9/6/2003 PML: Toward a High-Level Formal Language for Biological Systems
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PML: A Simple System
9/6/2003 PML: Toward a High-Level Formal Language for Biological Systems
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Compartments• Critical part of biological pathways
– prevents interactions that would otherwise occur
• Description of the behavior of a molecule should not depend on the compartment
• Regev et al. use “private” channels in the -calculus for both complexing and compartmentalization
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PML: Simple Compartments Example
MolAMolB
bind_a bind_a
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PML: Simple Compartments Example
MolAMolB
ER Cytosol
CytERBridge
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PML: Simple Compartments Example
MolB
ER Cytosol
CytERBridge MolA
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PML: Summary• Domains
– set of mutually dependent binding sites– defines at the lowest-level the reactions a
biological entity can undergo• Groups
– static structure for controlling namespace– may represent a large biological entity
• large complex, a system, etc.• Compartments
– special groups that define boundaries
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Semantics of PML• Defined in terms of the -calculus via
two translations– from PML to CorePML
• “flattens” compartments, removes bridges
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Semantics of PML– from CorePML to the -calculus
9/6/2003 PML: Toward a High-Level Formal Language for Biological Systems
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Larger Models• Modeled a general description of ER
cotranslational-translocation– unclearly or incompletely specified
aspects became apparent• e.g., can the signal sequence and translocon
bind without SRP? Yes [Herskovits and Bibi ’00]
• Extended to model targeting ER membrane with minor modifications
9/6/2003 PML: Toward a High-Level Formal Language for Biological Systems
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Benefits of PML• Easier to write and understand
because of a more direct biological metaphor
• Block structure for controlling namespace and modularity
• Special syntax for compartments– separate complexing from
compartmentalization
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Future Work• Naming?• Proximity of molecules• Integrating quantitative information
(reaction rates, etc.)– start from work by Priami et al.
• Compartment fusion and fission• Type checking PML specifications• Exceptional / higher-level specifications• Graphical and simulation tools
Syntax of PML
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Syntax of PML
9/6/2003 PML: Toward a High-Level Formal Language for Biological Systems
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Syntax of PML
The -calculus
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The -calculus• Syntax
• Operational Semantics
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The -calculus• Congruence
Example: Cotranslational Translocation
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Example: Cotranslational Translocation• Ribosome translates mRNA exposing a
signal sequence• Signal sequence attracts SRP stopping
translation• SRP receptor (on ER membrane) attracts
SRP• Signal sequence interacts with translocon,
SRP disassociates resuming translation• Signal peptidase cleaves the signal
sequence in the ER lumen, Hsc70 chaperones aid in protein folding
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Example: Cotranslational Translocation
9/6/2003 PML: Toward a High-Level Formal Language for Biological Systems
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Example: Cotranslational Translocation
9/6/2003 PML: Toward a High-Level Formal Language for Biological Systems
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Example: Cotranslational Translocation
9/6/2003 PML: Toward a High-Level Formal Language for Biological Systems
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Example: Cotranslational Translocation
9/6/2003 PML: Toward a High-Level Formal Language for Biological Systems
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Example: Cotranslational Translocation
9/6/2003 PML: Toward a High-Level Formal Language for Biological Systems
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Example: Cotranslational Translocation
9/6/2003 PML: Toward a High-Level Formal Language for Biological Systems
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Example: Cotranslational Translocation
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Computer Systems vs. Biological Processes• Similarities
– elementary pieces build-up components that in turn build-up large components and so forth to create highly complex systems
– all systems seem to have similar cores but exhibit great diversity
• Differences!– theory of computation and computer
systems are purely man-made (controlled-design) but biology is observational
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Model of Concurrent Computation• Must choose a machine model as a
basis– The -calculus [Milner ’90 and others]
• A formalism aimed at capturing the essence of concurrent computation.
– focuses on communication by message passing• System composed of processes• Communication on channels
– send: send message m on channel c– receive: receive message on channel
c, call it x– Many variants—the stochastic -calculus