25,365 research outputs found
Topological transition in disordered planar matching: combinatorial arcs expansion
In this paper, we investigate analytically the properties of the disordered
Bernoulli model of planar matching. This model is characterized by a
topological phase transition, yielding complete planar matching solutions only
above a critical density threshold. We develop a combinatorial procedure of
arcs expansion that explicitly takes into account the contribution of short
arcs, and allows to obtain an accurate analytical estimation of the critical
value by reducing the global constrained problem to a set of local ones. As an
application to a toy representation of the RNA secondary structures, we suggest
generalized models that incorporate a one-to-one correspondence between the
contact matrix and the RNA-type sequence, thus giving sense to the notion of
effective non-integer alphabets.Comment: 28 pages, 6 figures, published versio
Identifying and Analyzing RNA Pseudoknots based on Graph-theoretical Properties of Dual Graphs: a Partitioning Approach
In this paper we propose the study of properties of RNA secondary structures modeled as dual graphs, by partitioning these graphs into topological components denominated blocks. We give a full characterization of possible topological configurations of these blocks, and, in particular we show that an RNA secondary structure contains a pseudoknot if and only if its corresponding dual graph contains a block having a vertex of degree at least 3. Once a dual graph has been partitioned via computationally-efficient well-known graph-theoretical algorithms, this characterization allow us to identify these sub-topologies and physically isolate pseudoknots from RNA secondary structures and analyze them for specific combinatorial properties (e.g., connectivity)
Controlled non uniform random generation of decomposable structures
Consider a class of decomposable combinatorial structures, using different
types of atoms \Atoms = \{\At_1,\ldots ,\At_{|{\Atoms}|}\}. We address the
random generation of such structures with respect to a size and a targeted
distribution in of its \emph{distinguished} atoms. We consider two
variations on this problem. In the first alternative, the targeted distribution
is given by real numbers \TargFreq_1, \ldots, \TargFreq_k such that 0 <
\TargFreq_i < 1 for all and \TargFreq_1+\cdots+\TargFreq_k \leq 1. We
aim to generate random structures among the whole set of structures of a given
size , in such a way that the {\em expected} frequency of any distinguished
atom \At_i equals \TargFreq_i. We address this problem by weighting the
atoms with a -tuple \Weights of real-valued weights, inducing a weighted
distribution over the set of structures of size . We first adapt the
classical recursive random generation scheme into an algorithm taking
\bigO{n^{1+o(1)}+mn\log{n}} arithmetic operations to draw structures from
the \Weights-weighted distribution. Secondly, we address the analytical
computation of weights such that the targeted frequencies are achieved
asymptotically, i. e. for large values of . We derive systems of functional
equations whose resolution gives an explicit relationship between \Weights
and \TargFreq_1, \ldots, \TargFreq_k. Lastly, we give an algorithm in
\bigO{k n^4} for the inverse problem, {\it i.e.} computing the frequencies
associated with a given -tuple \Weights of weights, and an optimized
version in \bigO{k n^2} in the case of context-free languages. This allows
for a heuristic resolution of the weights/frequencies relationship suitable for
complex specifications. In the second alternative, the targeted distribution is
given by a natural numbers such that
where is the number of undistinguished atoms.
The structures must be generated uniformly among the set of structures of size
that contain {\em exactly} atoms \At_i (). We give
a \bigO{r^2\prod_{i=1}^k n_i^2 +m n k \log n} algorithm for generating
structures, which simplifies into a \bigO{r\prod_{i=1}^k n_i +m n} for
regular specifications
Combinatorial RNA Design: Designability and Structure-Approximating Algorithm
In this work, we consider the Combinatorial RNA Design problem, a minimal
instance of the RNA design problem which aims at finding a sequence that admits
a given target as its unique base pair maximizing structure. We provide
complete characterizations for the structures that can be designed using
restricted alphabets. Under a classic four-letter alphabet, we provide a
complete characterization of designable structures without unpaired bases. When
unpaired bases are allowed, we provide partial characterizations for classes of
designable/undesignable structures, and show that the class of designable
structures is closed under the stutter operation. Membership of a given
structure to any of the classes can be tested in linear time and, for positive
instances, a solution can be found in linear time. Finally, we consider a
structure-approximating version of the problem that allows to extend bands
(helices) and, assuming that the input structure avoids two motifs, we provide
a linear-time algorithm that produces a designable structure with at most twice
more base pairs than the input structure.Comment: CPM - 26th Annual Symposium on Combinatorial Pattern Matching, Jun
2015, Ischia Island, Italy. LNCS, 201
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