14,153 research outputs found
An O(n^5) algorithm for MFE prediction of kissing hairpins and 4-chains in nucleic acids
Efficient methods for prediction of minimum free energy (MFE) nucleic secondary structures are widely used, both to better understand structure and function of biological RNAs and to design novel nano-structures. Here, we present a new algorithm for MFE secondary structure prediction, which significantly expands the class of structures that can be handled in O(n^5) time. Our algorithm can handle H-type pseudoknotted structures, kissing hairpins, and chains of four overlapping stems, as well as nested substructures of these types
Synthesis of Stochastic Flow Networks
A stochastic flow network is a directed graph with incoming edges (inputs)
and outgoing edges (outputs), tokens enter through the input edges, travel
stochastically in the network, and can exit the network through the output
edges. Each node in the network is a splitter, namely, a token can enter a node
through an incoming edge and exit on one of the output edges according to a
predefined probability distribution. Stochastic flow networks can be easily
implemented by DNA-based chemical reactions, with promising applications in
molecular computing and stochastic computing. In this paper, we address a
fundamental synthesis question: Given a finite set of possible splitters and an
arbitrary rational probability distribution, design a stochastic flow network,
such that every token that enters the input edge will exit the outputs with the
prescribed probability distribution.
The problem of probability transformation dates back to von Neumann's 1951
work and was followed, among others, by Knuth and Yao in 1976. Most existing
works have been focusing on the "simulation" of target distributions. In this
paper, we design optimal-sized stochastic flow networks for "synthesizing"
target distributions. It shows that when each splitter has two outgoing edges
and is unbiased, an arbitrary rational probability \frac{a}{b} with a\leq b\leq
2^n can be realized by a stochastic flow network of size n that is optimal.
Compared to the other stochastic systems, feedback (cycles in networks)
strongly improves the expressibility of stochastic flow networks.Comment: 2 columns, 15 page
Designing Network Protocols for Good Equilibria
Designing and deploying a network protocol determines the rules by which end users interact with each other and with the network. We consider the problem of designing a protocol to optimize the equilibrium behavior of a network with selfish users. We consider network cost-sharing games, where the set of Nash equilibria depends fundamentally on the choice of an edge cost-sharing protocol. Previous research focused on the Shapley protocol, in which the cost of each edge is shared equally among its users. We systematically study the design of optimal cost-sharing protocols for undirected and directed graphs, single-sink and multicommodity networks, and different measures of the inefficiency of equilibria. Our primary technical tool is a precise characterization of the cost-sharing protocols that induce only network games with pure-strategy Nash equilibria. We use this characterization to prove, among other results, that the Shapley protocol is optimal in directed graphs and that simple priority protocols are essentially optimal in undirected graphs
Reducing facet nucleation during algorithmic self-assembly
Algorithmic self-assembly, a generalization of crystal growth, has been proposed as a mechanism for bottom-up fabrication of complex
nanostructures and autonomous DNA computation. In principle, growth can be programmed by designing a set of molecular tiles with binding
interactions that enforce assembly rules. In practice, however, errors during assembly cause undesired products, drastically reducing yields.
Here we provide experimental evidence that assembly can be made more robust to errors by adding redundant tiles that "proofread" assembly.
We construct DNA tile sets for two methods, uniform and snaked proofreading. While both tile sets are predicted to reduce errors during
growth, the snaked proofreading tile set is also designed to reduce nucleation errors on crystal facets. Using atomic force microscopy to
image growth of proofreading tiles on ribbon-like crystals presenting long facets, we show that under the physical conditions we studied the
rate of facet nucleation is 4-fold smaller for snaked proofreading tile sets than for uniform proofreading tile sets
Pattern overlap implies runaway growth in hierarchical tile systems
We show that in the hierarchical tile assembly model, if there is a
producible assembly that overlaps a nontrivial translation of itself
consistently (i.e., the pattern of tile types in the overlap region is
identical in both translations), then arbitrarily large assemblies are
producible. The significance of this result is that tile systems intended to
controllably produce finite structures must avoid pattern repetition in their
producible assemblies that would lead to such overlap. This answers an open
question of Chen and Doty (SODA 2012), who showed that so-called
"partial-order" systems producing a unique finite assembly *and" avoiding such
overlaps must require time linear in the assembly diameter. An application of
our main result is that any system producing a unique finite assembly is
automatically guaranteed to avoid such overlaps, simplifying the hypothesis of
Chen and Doty's main theorem
- …