Domain-specific Languages for Cellular Interactions

1. Domain-specific Languages for Cellular Interactions Bill Harrison Department of Computer Science University of Missouri at Columbia • This work partially supported by: • NIH1 R0l GM62920-04A1, • NIH1 P20 GM065762-01A1, • the Georgia Research Alliance and • the Georgia Cancer Coalition.

2. Domain-specific Languages for Cellular Interactions Bill Harrison Department of Computer Science University of Missouri at Columbia meow! • This work partially supported by: • NIH1 R0l GM62920-04A1, • NIH1 P20 GM065762-01A1, • the Georgia Research Alliance and • the Georgia Cancer Coalition.

3. Ph.D 2001, UIUC • Thesis: Modular Compilers and Their Correctness Proofs • Thesis Advisor: Sam Kamin • Post-doc, Oregon Graduate Inst. (OGI) • Three years on Programatica Project • using Haskell programming language as basis for formal methods • Assistant Professor, University of Missouri-Columbia since Fall 2003

4. Systems Biology asks… • Can static biological structure be related to dynamic biological behavior with mathematical clarity, precision, & rigor? • Can biological systems be viewed as the “sum of their parts”? • Can component-level models be integrated into precise system-level models of biological behavior? • What techniques from Mathematics and Computer Science apply to this composition problem?

5. Rhodobacter Sphaeroides • Photosynthetic bacterium • seeks out regions of greater light • Roughly the size of wavelength of light • cannot sense local light differences directly •  applies random walk

6. Simulations of Biological Systems • Simulations provide qualitative feedback, but are not models per se • how accurate/faithful is a simulation? • what does the feedback mean? • can one reason about the biological phenomenon based on the simulation? • can you identify the biology by inspecting the text of the simulation program?

7. contains 1000 LOC to understand requires expertise in C++ …and biological model …and critical system details e.g., how is concurrency implemented? R. Sphaeroides in C++ bool global_state::register_state(void *apointer) { if( number_of_states == mother_of_all_states.size()) mother_of_all_states.resize(number_of_states + 1000); mother_of_all_states[number_of_states++] = apointer; return true; }

8. Program structure does not reflect biological model can you look at the source code and recognize the underlying biology?  difficult to comprehend …and write correctly …and modify …and maintain …and re-use R. Sphaeroides in C++ bool global_state::register_state(void *apointer) { if( number_of_states == mother_of_all_states.size()) mother_of_all_states.resize(number_of_states + 1000); mother_of_all_states[number_of_states++] = apointer; return true; }

9. System Biology as Programming Language Design • The Problem: • General-purpose programming languages do not have the “right vocabulary” • Biological model: Concurrent Markov chains • C++: classes, pointers, etc. • …nor are they mathematics • Our Solution:Design small, special purpose languages with exactly the right vocabulary • called a Domain-specific Language (DSL) [Sheard99,Thiemann01,Leijen01] • Mathematical semantics of DSLs gives formal model of biology

10. Language Model of R. Sphaeroides cell1 || … || celln Executing: Produces animation:

11. Outline • Language Design and Domain-specific Languages • design, definition, and implementation • Systems Biology as Language Design • Case Study for Rhodobacter Sphaeroides • Design: what are the appropriate abstractions for R. Sphaeroides? • Definition: how do we specify exactly what R. Sphaeroides programs mean? • Implementation: how do we run R. Sphaeroides programs? • Conclusions

12. Cardinal Rule of Language Design Application Programmersshould choose languages with abstractions most suited to their task; Language designersmust provide languages with those abstractions… Domain Central Activities Reasonable Language System Programming “bit-fiddling” C Artificial Intelligence List processing LISP System Admin. Text processing, etc. PERL

13. DSLs are small languages w/ “domain abstractions” Ex: “Parsec” Parser DSL BNF for language <Stmt>  <ident> := <Expr> translates directly assignStmt :: Parser Stmt assignStmt = do{ id  ident ; symbol ":=" ; s  Expr ; return (Assign id s)} Parsec code

14. “Why a language and not a library?” • The Slogan: “What is excluded from a DSL is as important as what is included in it” • libraries in a general-purpose language still require • considerable expertise & self-discipline on the part of the programmer • Lack of generality in DSL  fewer things to “go wrong” • DSL may have desirable properties that a general-purpose language will not • e.g., implementation techniques specialized to DSL that do not apply to general-purpose languages • small size makes rigorous specification tractable

15. DSL Design DSL design for R. Sphaeroides • what are our domain abstractions? • How does this organism behave? • What modeling techniques are used by biologists to describe this behavior?

16. Bacterial Commands laze die adjust speed grow divide tumble *Probability of growth varies with light concentration

17. Chapman-Kolmogorov Equation* Pi,j probability of being in state m probability of transition from i to j *Commonly used framework for modeling biological systems [Bremaud99, Dailey02, Mao02, Shah00]

18. Chapman-Kolmogorov Equation A row in the above matrix encodes the transition function from state i of a Markov chain

19. Bacteria as Markov Chains State 0 State i … State m • non-deter. state machines with probabilistic transitions • induced by the Chapman-Kolmogorov equation • Pi,j in terms of environmental factors, organism • state, etc. • executing concurrently

20. Domain Abstractions for R. Sphaeroides • Individual cells: Markov-chain abstraction choose P1 Action1 … Pn Actionn • Actions: Tumble, Divide, AdjSpeed, Laze, Grow, etc. • Concurrency: cell1 || cell2 • Environmental Factors: light,size

21. Abstract syntax for CellSys • choose is our principal domain abstraction • behaves like the Markov chain transition function • Cell-level environment variables: light,size

22. DSL Definition • Background: Programming languages are “collections of effects” • Java = OO + Threads + State +… • LISP = Higher-order Functions + … • Prolog = Backtracking + … • Corresponding to each such effect is an algebraic construction called a monad • used for the development of modular semantic theories of programming languages [Moggi89] • monads may be constructed using “monad transformers”

23. Periodic Table of Effects StateT imperative := BackT backtracking cut ResT threads step pause  StateT imperative := BackT backtracking cut ResT threads step pause  EnvT binding  @ v ErrorT exceptions raise/catch ContT continuations callcc NondetT non-determ. choose EnvT binding  @ v ErrorT exceptions raise/catch ContT continuations callcc NondetT non-determ. choose DebugT debugging rollback ReactT reactivity send,recv,… ProbT probability random DebugT debugging rollback ReactT reactivity send,recv,… • Prog. languages are collections of effects captured as monads [Moggi] • Monads assembled from constructors (monad transformers) • Our view: Systems are collections of effects captured as monads • “Systems” broadly construed: • Compilers [Harrison00,98,01,02], • Secure system software [Harrison05,03], and • Biology [Harrison04]

24. Periodic Table of Effects StateT imperative := BackT backtracking cut ResT threads step pause  EnvT binding  @ v ErrorT exceptions raise/catch ContT continuations callcc NondetT non-determ. choose ProbT probability random DebugT debugging rollback ReactT reactivity send,recv,… • Mathematical definitions for any language created by combining MTs • CellSys = StateT + ResT + ProbT + ReactT • Such definitions are flexible • modular, extensible, and easily refactored

25. In a traditional RTS threads request services like “send a message” “output on device” “consume resource” RTS mediates ensuring that the threads do not interfere global system state remains consistent schedules threads DSL definition similar to traditional RTS … Run-time System threads

26. In CellSys Cells are threads with physical components as well size, velocity, … cells request services like “consume nutrients” “move me here” “want to divide” GE mediates like RTS, also: preserves physical integrity updates global world view performs scheduling High-level view of definition … Global Enviroment cells

27. DSL Implementation • Because CellSys defined in terms of monad transformers, may be implemented directly as Haskell program • I.e., monadic language definition may be transcribed “symbol for symbol” into Haskell • Haskell implementation easily instrumented to output system “snapshots”: • prints out snapshots in POV (Persistence of Vision) format & converted into MPEG

28. Q: What are appropriate languages for modeling? • Integrate techniques from programming languages • models of concurrency • language semantics • i.e., precise, mathematical language definitions • efficient language implementation • …into special purpose language called a “Domain-Specific Language” • abstractions taken directly from biology •  comprehensible by biologists • DSLs and DSL programs • hide technical details irrelevant/uninteresting to biologists • are “tunable” by computer scientist to reflect discovery/refinement • execute to provide “reality check” by biologists

29. models of concurrency efficient implementation mathematical models of programs reasoning about programs organism structure & behavior modeling techniques cellular automata systems of PDE’s numerical techniques Bioinformatics = Computer Science + Biology Computer Science Biology  =  Hard Problem: How do you effect a technology transfer from CS  Biology?

30. Interdisciplinary Process CellSys (version 1.0) Biologist evaluates DSL model for accuracy, expressiveness, etc. feedback/discussion Language expert refactors language as needed CellSys (version 2.0)

31. Summary Large body of work providing domain abstractions & models Comprehensibility, Reusability, & Ease of Use systems biology domain specific languages modular monadic semantics Precise description of biological phenomena through DSL semantics * Harrison & Harrison, “Domain Specific Languages for Cellular Interactions” in Proceedings of the International Conference IEEE Engineering in Medicine and Biology, 2004.