A Domain-Specific Language for Programming in the Tile Assembly Model

Doty, David; Patitz, Matthew J.

doi:10.1007/978-3-642-10604-0_3

Cited by 17 publications

(8 citation statements)

References 15 publications

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“…A computer scientist's way to look at these biomolecular calculi could be as "a domain specific language for modeling biomolecular "things," rather than a general purpose programming language like Python, C, or Java. The same connection can be seen in the title of [45] -A Domain-Specific Language for Programming in the Tile Assembly Modelfor modeling "tiles" which can be used to direct DNA self-assembly into tile structure (similar to Winfree's approach [127]). …”

Section: Process Calculus and Formal Methodologymentioning

confidence: 89%

Computational Biology: A Programming Perspective

Hartmann

Jones

Simonsen

et al. 2011

Formal Modeling: Actors, Open Systems, Biological Systems

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Abstract. Computation via biological devices has been the subject of close scrutiny since von Neumann's early work some 60 years ago. In spite of the many relevant works in this field, the notion of programming biological devices seems to be, at best, ill-defined. While many devices are claimed or proved to be computationally universal in some sense, the full step to a bona fide programming language is rarely taken, and one question is noticeable by its absence: If the device is universal, where are the programs?We begin with an extensive review of the literature on programmingrelated biocomputing; and briefly identify some strengths and shortcomings from a programming perspective. To show concretely what one could see as programming in biocomputing, we outline (from recent work) a computation model and a small programming language that are biologically more plausible than existing silicon-inspired models. Whether or not the model is biologically plausible in an absolute sense, we believe it sets a standard for a biological device that can be both universal and programmable. ContextThe terms "biocomputing" and "systems biology", taken in their broadest senses, span many fields and areas of research: biology, chemistry, physics, mathematics, electrical engineering and computer science among others. Two major subareas:-Computer modeling of biological and biomolecular processes -Biological hardware for computationThe terms "biomolecular computation" and "biomolecular computational model" occur with both meanings in the literature (see Section 4), sometimes referring to the one and sometimes the other subarea. This paper emphasises the second. More precisely: we take a synthetic viewpoint, concerned with building things as in the engineering and computer sciences. This is in contrast to the inevitable and ubiquitous analytic viewpoint common to the natural sciences, concerned with finding out how naturally evolved things work. We ask: What can be done or built or constructed; and not: how does nature work? (Caveat: just as in engineering, one will need to understand nature's cause-and-effect sufficiently well to be able to modulate it, i.e., to use nature to effectively serve our purposes.) A Theme: Biological Problem-SolvingOur main aim is thus to use the biological world as a computational medium. From a programming perspective, the main goal is problem-solving by writing programs. This section thus refers to solving problems by biology, not solving problems about biology or in biology.Given: a computational problem. To find: a biological solution. Further, problem-solving by a program means finding a general solution (and not just one run of one algorithm on one input data instance).A top-down approach is to devise a model of computation that -satisfies requirements for computer science/engineering -that could conceivably be realised in a biological medium -in which programs are clearly visible, and programming can be done -is a framework in which it is possible, at least in principle, to say when a problem has be...

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Section: Process Calculus and Formal Methodologymentioning

confidence: 89%

Computational Biology: A Programming Perspective

Hartmann

Jones

Simonsen

et al. 2011

Formal Modeling: Actors, Open Systems, Biological Systems

View full text Add to dashboard Cite

show abstract

“…While the general question, "Given tile assembly system T , is it locally deterministic?" is undecidable, there is an open question in the literature whether there might exist an efficient test to catch the failure of local determinism [5], much as programmers of concurrent systems design tests for race conditions. We answer this question affirmatively in this section.…”

Section: Testing For Local Determinismmentioning

confidence: 99%

Formal Verification of Self-Assembling Systems

Sterling

2010

Preprint

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This paper introduces the theory and practice of formal verification of self-assembling systems. We interpret a well-studied abstraction of nanomolecular self assembly, the Abstract Tile Assembly Model (aTAM), into Computation Tree Logic (CTL), a temporal logic often used in model checking. We then consider the class of "rectilinear" tile assembly systems. This class includes most aTAM systems studied in the theoretical literature, and all (algorithmic) DNA tile self-assembling systems that have been realized in laboratories to date. We present a polynomial-time algorithm that, given a tile assembly system T as input, either provides a counterexample to T 's rectilinearity or verifies whether T has a unique terminal assembly. Using partial order reductions, the verification search space for this algorithm is reduced from exponential size to O(n 2 ), where n × n is the size of the assembly surface. That reduction is asymptotically the best possible. We report on experimental results obtained by translating tile assembly simulator files into a Petri net format manipulable by the SMART model checking engines devised by Ciardo et al. The model checker runs in O(|T | • n 4 ) time, where |T | is the number of tile types in tile assembly system T , and n × n is the surface size. Atypical for a model checking problem-in which the practical limit usually is insufficient memory to store the state spacethe limit in this case was the amount of memory required to represent the rules of the model. (Storage of the state space and of the reachability graph were small by comparison.) We discuss how to overcome this obstacle by means of a front end tailored to the characteristics of self-assembly.

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“…"T is locally deterministic" is an undecidable property, as the standard tile assembly Turing machine simulation is locally deterministic, and it could be modified to do something not locally deterministic iff a machine achieves a halting state. Nevertheless, it would be useful to test for that property when programming-and debugging-a tile assembly system, hence self-assembly simulation and programming tools have attempted to include that functionality [20] [21]. Theorem 3 classifies this problem precisely, and indicates that programming techniques to ensure [22], and detect [23], data-race freedom and concurrent-write freedom in parallel systems can be used productively to program self-assembling agents.…”

Section: The Network Topology Ofmentioning

confidence: 99%

Memory Consistency Conditions for Self-Assembly Programming

Sterling

2009

Preprint

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Perhaps the two most significant theoretical questions about the programming of selfassembling agents are: (1) necessary and sufficient conditions to produce a unique terminal assembly, and (2) error correction. We address both questions, by reducing two well-studied models of tile assembly to models of distributed shared memory (DSM), in order to obtain results from the memory consistency systems induced by tile assembly systems when simulated in the DSM setting. The Abstract Tile Assembly Model (aTAM) can be simulated by a DSM system that obeys causal consistency, and the locally deterministic tile assembly systems in the aTAM correspond exactly to the concurrent-write free programs that simulate tile assembly in such a model. Thus, the detection of the failure of local determinism (which had formerly been an open problem) reduces to the detection of data races in simulating programs. Further, the Kinetic Tile Assembly Model can be simulated by a DSM system that obeys GWO, a memory consistency condition defined by Steinke and Nutt. (To our knowledge, this is the first natural example of a DSM system that obeys GWO, but no stronger consistency condition.) We combine these results with the observation that self-assembly algorithms are local algorithms, and there exists a fast conversion of deterministic local algorithms into deterministic self-stabilizing algorithms. This provides an "immediate" generalization of a theorem by Soloveichik et al. about the existence of tile assembly systems that simultaneously perform two forms of self-stabilization: proofreading and selfhealing. Our reductions and proof techniques can be extended to the programming of self-assembling agents in a variety of media, not just DNA tiles, and not just two-dimensional surfaces.

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A Domain-Specific Language for Programming in the Tile Assembly Model

Cited by 17 publications

References 15 publications

Computational Biology: A Programming Perspective

Computational Biology: A Programming Perspective

Formal Verification of Self-Assembling Systems

Memory Consistency Conditions for Self-Assembly Programming

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