89 research outputs found
Use of Chemical Modification To Elucidate RNA Folding Pathways
As discussed in this overview, chemical modification is sensitive to the accessibility of a nucleotide to the solvent, and many nucleotides become less accessible as an RNA folds into its structured form. Chemical modification reagents are therefore suitable for following RNA folding, and can be used to study the kinetics of structure formation on time scales ranging from minutes to hours.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/143596/1/cpnc1109.pd
Lynx: A Programmatic SAT Solver for the RNA-folding Problem
15th International Conference, Trento, Italy, June 17-20, 2012. ProceedingsThis paper introduces Lynx, an incremental programmatic SAT solver that allows non-expert users to introduce domain-specific code into modern conflict-driven clause-learning (CDCL) SAT solvers, thus enabling users to guide the behavior of the solver.
The key idea of Lynx is a callback interface that enables non-expert users to specialize the SAT solver to a class of Boolean instances. The user writes specialized code for a class of Boolean formulas, which is periodically called by Lynx’s search routine in its inner loop through the callback interface. The user-provided code is allowed to examine partial solutions generated by the solver during its search, and to respond by adding CNF clauses back to the solver dynamically and incrementally. Thus, the user-provided code can specialize and influence the solver’s search in a highly targeted fashion. While the power of incremental SAT solvers has been amply demonstrated in the SAT literature and in the context of DPLL(T), it has not been previously made available as a programmatic API that is easy to use for non-expert users. Lynx’s callback interface is a simple yet very effective strategy that addresses this need.
We demonstrate the benefits of Lynx through a case-study from computational biology, namely, the RNA secondary structure prediction problem. The constraints that make up this problem fall into two categories: structural constraints, which describe properties of the biological structure of the solution, and energetic constraints, which encode quantitative requirements that the solution must satisfy. We show that by introducing structural constraints on-demand through user provided code we can achieve, in comparison with standard SAT approaches, upto 30x reduction in memory usage and upto 100x reduction in time
Large Deviations for Random Trees
We consider large random trees under Gibbs distributions and prove a Large
Deviation Principle (LDP) for the distribution of degrees of vertices of the
tree. The LDP rate function is given explicitly. An immediate consequence is a
Law of Large Numbers for the distribution of vertex degrees in a large random
tree. Our motivation for this study comes from the analysis of RNA secondary
structures.Comment: 10 page
Distribution of graph-distances in Boltzmann ensembles of RNA secondary structures
Large RNA molecules often carry multiple functional domains whose spatial
arrangement is an important determinant of their function. Pre-mRNA splicing,
furthermore, relies on the spatial proximity of the splice junctions that can
be separated by very long introns. Similar effects appear in the processing of
RNA virus genomes. Albeit a crude measure, the distribution of spatial
distances in thermodynamic equilibrium therefore provides useful information on
the overall shape of the molecule can provide insights into the interplay of
its functional domains. Spatial distance can be approximated by the
graph-distance in RNA secondary structure. We show here that the equilibrium
distribution of graph-distances between arbitrary nucleotides can be computed
in polynomial time by means of dynamic programming. A naive implementation
would yield recursions with a very high time complexity of O(n^11). Although we
were able to reduce this to O(n^6) for many practical applications a further
reduction seems difficult. We conclude, therefore, that sampling approaches,
which are much easier to implement, are also theoretically favorable for most
real-life applications, in particular since these primarily concern long-range
interactions in very large RNA molecules.Comment: Peer-reviewed and presented as part of the 13th Workshop on
Algorithms in Bioinformatics (WABI2013
Exact Fourier expansion in cylindrical coordinates for the three-dimensional Helmholtz Green function
A new method is presented for Fourier decomposition of the Helmholtz Green
Function in cylindrical coordinates, which is equivalent to obtaining the
solution of the Helmholtz equation for a general ring source. The Fourier
coefficients of the Helmholtz Green function are split into their half
advanced+half retarded and half advanced-half retarded components. Closed form
solutions are given for these components in terms of a Horn function and a
Kampe de Feriet function, respectively. The systems of partial differential
equations associated with these two-dimensional hypergeometric functions are
used to construct a fourth-order ordinary differential equation which both
components satisfy. A second fourth-order ordinary differential equation for
the general Fourier coefficent is derived from an integral representation of
the coefficient, and both differential equations are shown to be equivalent.
Series solutions for the various Fourier coefficients are also given, mostly in
terms of Legendre functions and Bessel/Hankel functions. These are derived from
the closed form hypergeometric solutions or an integral representation, or
both. Numerical calculations comparing different methods of calculating the
Fourier coefficients are presented
Long range forces and limits on unparticle interactions
Couplings between standard model particles and unparticles from a nontrivial
scale invariant sector can lead to long range forces. If the forces couple to
quantities such as baryon or lepton (electron) number, stringent limits result
from tests of the gravitational inverse square law. These limits are much
stronger than from collider phenomenology and astrophysics.Comment: 7 pages, revtex; v2 minor changes and added reference
Simultaneous alignment and folding of protein sequences
Accurate comparative analysis tools for low-homology proteins remains a difficult challenge in computational biology, especially sequence alignment and consensus folding problems. We presentpartiFold-Align, the first algorithm for simultaneous alignment and consensus folding of unaligned protein sequences; the algorithm’s complexity is polynomial in time and space. Algorithmically,partiFold-Align exploits sparsity in the set of super-secondary structure pairings and alignment candidates to achieve an effectively cubic running time for simultaneous pairwise alignment and folding. We demonstrate the efficacy of these techniques on transmembrane β-barrel proteins, an important yet difficult class of proteins with few known three-dimensional structures. Testing against structurally derived sequence alignments,partiFold-Align significantly outperforms state-of-the-art pairwise sequence alignment tools in the most difficult low sequence homology case and improves secondary structure prediction where current approaches fail. Importantly, partiFold-Align requires no prior training. These general techniques are widely applicable to many more protein families. partiFold-Align is available at http://partiFold.csail.mit.edu
A Combinatorial Framework for Designing (Pseudoknotted) RNA Algorithms
We extend an hypergraph representation, introduced by Finkelstein and
Roytberg, to unify dynamic programming algorithms in the context of RNA folding
with pseudoknots. Classic applications of RNA dynamic programming energy
minimization, partition function, base-pair probabilities...) are reformulated
within this framework, giving rise to very simple algorithms. This
reformulation allows one to conceptually detach the conformation space/energy
model -- captured by the hypergraph model -- from the specific application,
assuming unambiguity of the decomposition. To ensure the latter property, we
propose a new combinatorial methodology based on generating functions. We
extend the set of generic applications by proposing an exact algorithm for
extracting generalized moments in weighted distribution, generalizing a prior
contribution by Miklos and al. Finally, we illustrate our full-fledged
programme on three exemplary conformation spaces (secondary structures,
Akutsu's simple type pseudoknots and kissing hairpins). This readily gives sets
of algorithms that are either novel or have complexity comparable to classic
implementations for minimization and Boltzmann ensemble applications of dynamic
programming
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